Major/Minor Areas
Code | Title | Units |
---|---|---|
Human-Computer Interaction | ||
Introduction to User Experience Design | 4 | |
User Experience Research | 3 | |
Human-Computer Interaction (HCI) Research | 3 | |
Information Visualization and Presentation | 4 | |
Theory and Practice of Tangible User Interfaces | 4 | |
Interface Aesthetics | 3 | |
Special Topics in Information (Advanced HCI Research and Interaction Design only) | 1-4 | |
Special Topics in Technology (Biosensory Computing only) | 2-4 | |
Plus outside courses upon approval of your advisor | ||
Information Economics and Policy | ||
Information Technology Economics, Strategy, and Policy | 3 | |
Plus outside courses upon approval of your advisor | ||
Information Law and Policy | ||
Information Law and Policy | 3 | |
Technology and Delegation | 3 | |
Public Interest Cybersecurity: The Citizen Clinic Practicum | 3 | |
Special Topics in Social Science and Policy (Introduction to Politics of Information and Seminar in the Politics of Information only) | 2-4 | |
Plus outside courses upon approval of your advisor | ||
Information Organization and Retrieval | ||
Information Organization and Retrieval | 3 | |
Information Visualization and Presentation | 4 | |
Applied Machine Learning | 4 | |
Applied Natural Language Processing | 3 | |
Data Engineering | 4 | |
Natural Language Processing | 4 | |
Plus outside courses upon approval of your advisor | ||
Information Systems Design | ||
Introduction to Programming and Computation | 2 | |
Introduction to Data Structures and Analytics | 2 | |
Applied Machine Learning | 4 | |
Front-End Web Architecture | 3 | |
Back-End Web Architecture | 3 | |
Privacy Engineering | 3 | |
Data Engineering | 4 | |
Applied Natural Language Processing | 3 | |
Natural Language Processing | 4 | |
Plus outside courses upon approval of your advisor | ||
Social Aspects of Information | ||
Research Design and Applications for Data and Analysis | 3 | |
Social Issues of Information | 3 | |
User Experience Research | 3 | |
Concepts of Information | 3 | |
Leadership and Management | 3 | |
Social Psychology and Information Technology | 3 | |
Experiments and Causal Inference | 3 | |
Quantitative Research Methods for Information Systems and Management | 3 | |
Qualitative Research Methods for Information Systems and Management | 3 | |
Big Data and Development | 3 | |
Plus outside courses upon approval of your advisor | ||
Information and Communication Technologies and Devleopment | ||
Social Issues of Information | 3 | |
Introduction to User Experience Design | 4 | |
User Experience Research | 3 | |
Information and Communications Technology for Development | 3 | |
Big Data and Development | 3 | |
Plus outside courses upon approval of your advisor |
Info 201 research design and applications for data and analysis 3 units.
Terms offered: Fall 2024, Spring 2024, Fall 2023 Introduces the data sciences landscape, with a particular focus on learning data science techniques to uncover and answer the questions students will encounter in industry. Lectures, readings, discussions, and assignments will teach how to apply disciplined, creative methods to ask better questions, gather data, interpret results, and convey findings to various audiences. The emphasis throughout is on making practical contributions to real decisions that organizations will and should make. Course must be taken for a letter grade to fulfill degree requirements. Research Design and Applications for Data and Analysis: Read More [+]
Hours & Format
Fall and/or spring: 15 weeks - 1.5 hours of lecture per week
Additional Format: One and one-half hours of lecture per week.
Additional Details
Subject/Course Level: Information/Graduate
Grading: Letter grade.
Research Design and Applications for Data and Analysis: Read Less [-]
Terms offered: Fall 2024, Fall 2023, Fall 2022 This course introduces the intellectual foundations of information organization and retrieval: conceptual modeling, semantic representation, vocabulary and metadata design, classification, and standardization, as well as information retrieval practices, technology, and applications, including computational processes for analyzing information in both textual and non-textual formats. Information Organization and Retrieval: Read More [+]
Rules & Requirements
Prerequisites: Students should have a working knowledge of the Python programming language
Fall and/or spring: 15 weeks - 3 hours of lecture per week
Additional Format: Three hours of lecture per week.
Information Organization and Retrieval: Read Less [-]
Terms offered: Spring 2024, Spring 2023, Spring 2022 This course is designed to be an introduction to the topics and issues associated with information and information technology and its role in society. Throughout the semester we will consider both the consequence and impact of technologies on social groups and on social interaction and how society defines and shapes the technologies that are produced. Students will be exposed to a broad range of applied and practical problems, theoretical issues, as well as methods used in social scientific analysis. The four sections of the course are: 1) theories of technology in society, 2) information technology in workplaces 3) automation vs. humans, and 4) networked sociability. Social Issues of Information: Read More [+]
Social Issues of Information: Read Less [-]
Terms offered: Spring 2024, Spring 2023, Spring 2022 This course uses examples from various commercial domains—retail, health, credit, entertainment, social media, and biosensing/quantified self—to explore legal and ethical issues including freedom of expression, privacy, research ethics, consumer protection, information and cybersecurity, and copyright. The class emphasizes how existing legal and policy frameworks constrain, inform, and enable the architecture, interfaces, data practices, and consumer facing policies and documentation of such offerings; and, fosters reflection on the ethical impact of information and communication technologies and the role of information professionals in legal and ethical work. Information Law and Policy: Read More [+]
Prerequisites: Consent of instructor required for nonmajors
Instructor: Mulligan
Information Law and Policy: Read Less [-]
Terms offered: Fall 2024, Fall 2023, Fall 2022 This course introduces the basics of computer programming that are essential for those interested in computer science, data science, and information management. Students will write their own interactive programs (in Python) to analyze data, process text, draw graphics, manipulate images, and simulate physical systems. Problem decomposition, program efficiency, and good programming style are emphasized throughout the course. Introduction to Programming and Computation: Read More [+]
Fall and/or spring: 7.5 weeks - 4 hours of lecture per week
Additional Format: Four hours of lecture per week for seven and one-half weeks.
Instructor: Farid
Introduction to Programming and Computation: Read Less [-]
Terms offered: Fall 2024, Fall 2023, Fall 2022 The ability to represent, manipulate, and analyze structured data sets is foundational to the modern practice of data science. This course introduces students to the fundamentals of data structures and data analysis (in Python). Best practices for writing code are emphasized throughout the course. This course forms the second half of a sequence that begins with INFO 106. It may also be taken as a stand-alone course by any student that has sufficient Python experience. Introduction to Data Structures and Analytics: Read More [+]
Prerequisites: INFO 206A or equivalent, or permission of instructor
Credit Restrictions: Course must be completed for a letter grade to fulfill degree requirements.
Formerly known as: Information 206
Introduction to Data Structures and Analytics: Read Less [-]
Terms offered: Fall 2024, Fall 2023, Fall 2022 This course will provide an introduction to the field of Human-Computer Interaction (HCI). Students will learn to apply design thinking to User Experience (UX) design, prototyping, & evaluation. The course will also cover special topic areas within HCI. Introduction to User Experience Design: Read More [+]
Introduction to User Experience Design: Read Less [-]
Terms offered: Spring 2024, Spring 2023, Spring 2022 This course addresses concepts and methods of user experience research, from understanding and identifying needs, to evaluating concepts and designs, to assessing the usability of products and solutions. We emphasize methods of collecting and interpreting qualitative data about user activities, working both individually and in teams, and translating them into design decisions. Students gain hands-on practice with observation, interview, survey , focus groups, and expert review. Team activities and group work are required during class and for most assignments. Additional topics include research in enterprise, consulting, and startup organizations, lean/agile techniques, mobile research approaches, and strategies for communicating findings. User Experience Research: Read More [+]
Additional Format: Three hours of Lecture per week for 15 weeks.
User Experience Research: Read Less [-]
Terms offered: Fall 2024, Fall 2023 This course will give participants hands-on digital product design experience oriented around current industry practice. The course will be project-based with an emphasis on iteration, practice, and critique. During the course, participants will work on a series of design projects through a full design process, including developing appropriate design deliverables, gathering feedback, and iterating on designs. Product Design Studio: Read More [+]
Objectives & Outcomes
Course Objectives: The course objective is to provide students interested in web and mobile Product Design with skills, practice, and experience that will prepare them for careers in product design and design-related roles.
Prerequisites: DES INV 15 or COMPSCI 160 or INFO 213 AND INFO 214; or permission of the instructor. Students can take INFO 214 and INFO 215 concurrently, but students may not drop INFO 214 and remain in INFO 215
Formerly known as: Information Systems and Management 215
Product Design Studio: Read Less [-]
Terms offered: Spring 2024, Fall 2021, Fall 2020 This course is a graduate-level introduction to HCI research. Students will learn to conduct original HCI research by reading and discussing research papers while collaborating on a semester-long research project. Each week the class will focus on a theme of HCI research and review foundational and cutting-edge research relevant to that theme. The class will focus on the following areas of HCI research: ubiquitous computing , social computing, critical theory, and human-AI interaction. In addition to these research topics the class will introduce common qualitative and quantitative methodologies in HCI research. Human-Computer Interaction (HCI) Research: Read More [+]
Instructor: Salehi
Human-Computer Interaction (HCI) Research: Read Less [-]
Terms offered: Spring 2024, Spring 2022, Spring 2020 As it's generally used, "information" is a collection of notions, rather than a single coherent concept. In this course, we'll examine conceptions of information based in information theory, philosophy, social science, economics, and history. Issues include: How compatible are these conceptions; can we talk about "information" in the abstract? What work do these various notions play in discussions of literacy, intellectual property, advertising, and the political process? And where does this leave "information studies" and "the information society"? Concepts of Information: Read More [+]
Prerequisites: Graduate standing
Instructors: Duguid, Nunberg
Concepts of Information: Read Less [-]
Terms offered: Fall 2024, Fall 2023, Fall 2021 This course focuses on the practice of leadership, collaboration, and people management in contemporary, distributed, information and technology-rich organizations. Not just for potential people managers, this course is derived from the premise that a foundation in leadership, management, and collaboration is essential for individuals in all roles, at any stage of their career. To build this foundation we will take a hybrid approach, engaging literature from disciplines such as social psychology, management, and organizational behavior, as well as leveraging case studies and practical exercises. The course will place a special emphasis on understanding and reacting to social dynamics in workplace hierarchies and teams. Leadership and Management: Read More [+]
Leadership and Management: Read Less [-]
Terms offered: Fall 2024, Spring 2013, Spring 2011 This class is for graduate students interested in getting an advanced understanding of judgments and decisions made with predictive algorithms. The course will survey the vast literature on the psychology of how people arrive at judgments and make decisions with the help of statistical information, focused mostly on experimental lab evidence from cognitive and social psychology. Then study the burgeoning evidence on how people use statistical algorithms in practice, exploring field evidence from a range of settings from criminal justice and healthcare to housing and labor markets. Special attention is paid to psychological principles that impact the effectiveness and fairness of algorithms deployed at scale. Decisions and Algorithms: Read More [+]
Course Objectives: Help students understand systematic human errors and explore potential algorithmic solutions.
Decisions and Algorithms: Read Less [-]
Terms offered: Spring 2024, Spring 2023, Spring 2022 Discusses application of social psychological theory and research to information technologies and systems; we focus on sociological social psychology, which largely focuses on group processes, networks, and interpersonal relationships. Information technologies considered include software systems used on the internet such as social networks, email, and social games, as well as specific hardware technologies such as mobile devices, computers , wearables, and virtual/augmented reality devices. We examine human communication practices, through the lens of different social psychology theories, including: symbolic interaction, identity theories, social exchange theory, status construction theory, and social networks and social structure theory. Social Psychology and Information Technology: Read More [+]
Instructor: Cheshire
Social Psychology and Information Technology: Read Less [-]
Terms offered: Spring 2024, Spring 2022, Spring 2021 This course applies economic tools and principles, including game theory, industrial organization, information economics, and behavioral economics, to analyze business strategies and public policy issues surrounding information technologies and IT industries. Topics include: economics of information goods, services, and platforms; economics of information and asymmetric information; economics of artificial intelligence, cybersecurity, data privacy, and peer production; strategic pricing; strategic complements and substitutes; competition and antitrust; Internet industry structure and regulation; network cascades, network formation, and network structure. Information Technology Economics, Strategy, and Policy: Read More [+]
Course Objectives: INFO234 is a graduate level course in the school's topical area of Information Economics and Policy, and can be taken by the masters and doctoral students to satisfy their respective degree requirements.
Student Learning Outcomes: Students will learn to identify, describe, and analyze business strategies and public policy issues of particular relevance to the information industry. Students will learn and apply economic tools and principles to analyze phenomena such as platform competition, social epidemics, and peer production, and current policy issues such as network neutrality and information privacy. Through integrated assignments and project work, the students will apply the theoretical concepts and analytic tools learned in lectures and readings to develop and evaluate a business model, product, or service of their choosing, e.g., a start-up idea they are pursuing.
Instructor: Chuang
Information Technology Economics, Strategy, and Policy: Read Less [-]
Terms offered: Fall 2021, Fall 2019, Fall 2018 The introduction of technology increasingly delegates responsibility to technical actors, often reducing traditional forms of transparency and challenging traditional methods for accountability. This course explores the interaction between technical design and values including: privacy, accessibility, fairness, and freedom of expression. We will draw on literature from design, science and technology studies, computer science, law, and ethics, as well as primary sources in policy, standards and source code. We will investigate approaches to identifying the value implications of technical designs and use methods and tools for intentionally building in values at the outset. Technology and Delegation: Read More [+]
Technology and Delegation: Read Less [-]
Terms offered: Fall 2024, Spring 2024, Fall 2022 This course introduces students to experimentation in data science. Particular attention is paid to the formation of causal questions, and the design and analysis of experiments to provide answers to these questions. This topic has increased considerably in importance since 1995, as researchers have learned to think creatively about how to generate data in more scientific ways, and developments in information technology has facilitated the development of better data gathering. Experiments and Causal Inference: Read More [+]
Experiments and Causal Inference: Read Less [-]
Terms offered: Spring 2023, Spring 2022, Spring 2021 The design and presentation of digital information. Use of graphics, animation, sound, visualization software, and hypermedia in presenting information to the user. Methods of presenting complex information to enhance comprehension and analysis. Incorporation of visualization techniques into human-computer interfaces. Course must be completed for a letter grade to fulfill degree requirements. Information Visualization and Presentation: Read More [+]
Prerequisites: INFO 206B or knowledge of programming and data structures with consent of instructor
Fall and/or spring: 15 weeks - 3 hours of lecture and 1 hour of laboratory per week
Additional Format: Three hours of lecture and one hour of laboratory per week.
Instructor: Hearst
Information Visualization and Presentation: Read Less [-]
Terms offered: Spring 2024, Spring 2023, Spring 2022 Provides a theoretical and practical introduction to modern techniques in applied machine learning. Covers key concepts in supervised and unsupervised machine learning, including the design of machine learning experiments, algorithms for prediction and inference, optimization, and evaluation. Students will learn functional, procedural, and statistical programming techniques for working with real-world data. Applied Machine Learning: Read More [+]
Student Learning Outcomes: • Effectively design, execute, and critique experimental and non-experimental methods from statistics, machine learning, and econometrics. • Implement basic algorithms on structured and unstructured data, and evaluate the performance of these algorithms on a variety of real-world datasets. • Understand the difference between causal and non-causal relationships, and which situations and methods are appropriate for both forms of analysis. • Understand the principles, advantages, and disadvantages of different algorithms for supervised and unsupervised machine learning.
Prerequisites: INFO 206B , or equivalent course in Python programming; INFO 271B , or equivalent graduate-level course in statistics or econometrics; or permission of instructor
Fall and/or spring: 15 weeks - 3 hours of lecture and 1 hour of discussion per week
Additional Format: Three hours of lecture and one hour of discussion per week.
Instructor: Blumenstock
Applied Machine Learning: Read Less [-]
Terms offered: Fall 2024, Fall 2023, Fall 2022 This course is a survey of technologies that power the user interfaces of web applications on a variety of devices today, including desktop, mobile, and tablet devices. This course will delve into some of the core Front-End languages and frameworks (HTML/CSS/JS/React/Redux), as well as the underlying technologies enable web applications (HTTP, URI, JSON). The goal of this course is to provide an overview of the technical issues surrounding user interfaces powered by the web today, and to provide a solid and comprehensive perspective of the Web's constantly evolving landscape. Front-End Web Architecture: Read More [+]
Prerequisites: Introductory programming
Fall and/or spring: 15 weeks - 2 hours of lecture and 1 hour of laboratory per week
Additional Format: Two hours of lecture and one hour of laboratory per week.
Formerly known as: Information 253
Front-End Web Architecture: Read Less [-]
Terms offered: Spring 2024, Spring 2023, Spring 2022 This course is a survey of web technologies that are used to build back-end systems that enable rich web applications. Utilizing technologies such as Python, Flask, Docker, RDBMS/NoSQL databases, and Spark, this class aims to cover the foundational concepts that drive the web today. This class focuses on building APIs using micro-services that power everything from content management systems to data engineering pipelines that provide insights by processing large amounts of data. The goal of this course is to provide an overview of the technical issues surrounding back-end systems today, and to provide a solid and comprehensive perspective of the web's constantly evolving landscape. Back-End Web Architecture: Read More [+]
Back-End Web Architecture: Read Less [-]
Terms offered: Spring 2024, Spring 2023 The course overviews a broad number of paradigms of privacy from a technical point of view. The course is designed to assist system engineers and information systems professionals in getting familiar with the subject of privacy engineering and train them in implementing those mechanisms. In addition, the course is designed to coach those professionals to critically think about the strengths and weaknesses of the different privacy paradigms. These skills are important for cybersecurity professionals and enable them to effectively incorporate privacy-awareness in the design phase of their products. Privacy Engineering: Read More [+]
Course Objectives: Critique the strengths and weaknesses of the different privacy paradigms Describe the different technical paradigms of privacy that are applicable for systems engineering Implement such privacy paradigms, and embed them in information systems during the design process and the implementation phase Stay updated about the state of the art in the field of privacy engineering
Credit Restrictions: Students will receive no credit for INFO 255 after completing INFO 255 . A deficient grade in INFO 255 may be removed by taking INFO 255 .
Privacy Engineering: Read Less [-]
Terms offered: Fall 2024, Fall 2023, Fall 2021 This course examines the use of natural language processing as a set of methods for exploring and reasoning about text as data, focusing especially on the applied side of NLP — using existing NLP methods and libraries in Python in new and creative ways. Topics include part-of-speech tagging, shallow parsing, text classification, information extraction, incorporation of lexicons and ontologies into text analysis, and question answering. Students will apply and extend existing software tools to text-processing problems. Applied Natural Language Processing: Read More [+]
Prerequisites: INFO 206A and INFO 206B or proficient programming in Python (programs of at least 200 lines of code). Proficient with basic statistics and probabilities
Instructor: Bamman
Applied Natural Language Processing: Read Less [-]
Terms offered: Spring 2024, Fall 2022 This course will cover the principles and practices of managing data at scale, with a focus on use cases in data analysis and machine learning. We will cover the entire life cycle of data management and science, ranging from data preparation to exploration, visualization and analysis, to machine learning and collaboration, with a focus on ensuring reliable, scalable operationalization. ensuring reliable, scalable operationalization. Data Engineering: Read More [+]
Prerequisites: INFO 206B or equivalent college-level course in computer science in Python with a C- or better AND COMPSCI C100/ DATA C100 / STAT C100 or COMPSCI 189 or INFO 251 or DATA 144 or equivalent college-level course in data science with a C- or better
Instructors: Hellerstein, Parameswaran, Jain
Data Engineering: Read Less [-]
Terms offered: Spring 2024, Spring 2023, Spring 2022 This course introduces students to natural language processing and exposes them to the variety of methods available for reasoning about text in computational systems. NLP is deeply interdisciplinary, drawing on both linguistics and computer science, and helps drive much contemporary work in text analysis (as used in computational social science, the digital humanities, and computational journalism). We will focus on major algorithms used in NLP for various applications (part-of-speech tagging, parsing, coreference resolution, machine translation) and on the linguistic phenomena those algorithms attempt to model. Students will implement algorithms and create linguistically annotated data on which those algorithms depend. Natural Language Processing: Read More [+]
Prerequisites: Familiarity with data structures, algorithms, linear algebra, and probability
Natural Language Processing: Read Less [-]
Terms offered: Fall 2024, Fall 2023, Fall 2022 This course explores the theory and practice of Tangible User Interfaces, a new approach to Human Computer Interaction that focuses on the physical interaction with computational media. The topics covered in the course include theoretical framework, design examples, enabling technologies, and evaluation of Tangible User Interfaces. Students will design and develop experimental Tangible User Interfaces using physical computing prototyping tools and write a final project report. Theory and Practice of Tangible User Interfaces: Read More [+]
Instructor: Ryokai
Also listed as: NWMEDIA C262
Theory and Practice of Tangible User Interfaces: Read Less [-]
Terms offered: Spring 2024, Spring 2023, Spring 2022 This course will cover new interface metaphors beyond desktops (e.g., for mobile devices, computationally enhanced environments, tangible user interfaces) but will also cover visual design basics (e.g., color, layout, typography, iconography) so that we have systematic and critical understanding of aesthetically engaging interfaces. Students will get a hands-on learning experience on these topics through course projects, design critiques , and discussions, in addition to lectures and readings. Interface Aesthetics: Read More [+]
Also listed as: NWMEDIA C265
Interface Aesthetics: Read Less [-]
Terms offered: Fall 2024, Fall 2023, Fall 2022 Introduction to many different types of quantitative research methods, with an emphasis on linking quantitative statistical techniques to real-world research methods. Introductory and intermediate topics include: defining research problems, theory testing, casual inference, probability, and univariate statistics. Research design and methodology topics include: primary/secondary survey data analysis, experimental designs, and coding qualitative data for quantitative analysis. Quantitative Research Methods for Information Systems and Management: Read More [+]
Prerequisites: Introductory statistics recommended
Quantitative Research Methods for Information Systems and Management: Read Less [-]
Terms offered: Fall 2024, Fall 2023, Fall 2022 Theory and practice of naturalistic inquiry. Grounded theory. Ethnographic methods including interviews, focus groups, naturalistic observation. Case studies. Analysis of qualitative data. Issues of validity and generalizability in qualitative research. Qualitative Research Methods for Information Systems and Management: Read More [+]
Instructor: Burrell
Qualitative Research Methods for Information Systems and Management: Read Less [-]
Terms offered: Spring 2024, Spring 2023, Spring 2022 This seminar reviews current literature and debates regarding Information and Communication Technologies and Development (ICTD). This is an interdisciplinary and practice-oriented field that draws on insights from economics, sociology, engineering, computer science, management, public health, etc. Information and Communications Technology for Development: Read More [+]
Fall and/or spring: 15 weeks - 3 hours of seminar per week
Additional Format: Three hours of seminar per week.
Instructor: Saxenian
Formerly known as: Information C283
Information and Communications Technology for Development: Read Less [-]
Terms offered: Spring 2024, Spring 2021, Spring 2019 As new sources of digital data proliferate in developing economies, there is the exciting possibility that such data could be used to benefit the world’s poor. Through a careful reading of recent research and through hands-on analysis of large-scale datasets, this course introduces students to the opportunities and challenges for data-intensive approaches to international development. Students should be prepared to dissect, discuss, and replicate academic publications from several fields including development economics, machine learning, information science, and computational social science. Students will also conduct original statistical and computational analysis of real-world data. Big Data and Development: Read More [+]
Prerequisites: Students are expected to have prior graduate training in machine learning, econometrics, or a related field
Big Data and Development: Read Less [-]
Terms offered: Fall 2024, Spring 2024, Fall 2023 This course provides students with real-world experience assisting politically vulnerable organizations and persons around the world to develop and implement sound cybersecurity practices. In the classroom, students study basic theories and practices of digital security, intricacies of protecting largely under-resourced organizations, and tools needed to manage risk in complex political, sociological, legal, and ethical contexts. In the clinic , students work in teams supervised by Clinic staff to provide direct cybersecurity assistance to civil society organizations. We emphasize pragmatic, workable solutions that take into account the unique needs of each partner organization. Public Interest Cybersecurity: The Citizen Clinic Practicum: Read More [+]
Repeat rules: Course may be repeated for credit with instructor consent.
Public Interest Cybersecurity: The Citizen Clinic Practicum: Read Less [-]
Terms offered: Fall 2024, Spring 2024, Fall 2023 Specific topics, hours, and credit may vary from section to section, year to year. Special Topics in Information: Read More [+]
Repeat rules: Course may be repeated for credit when topic changes. Students may enroll in multiple sections of this course within the same semester.
Fall and/or spring: 8 weeks - 2-8 hours of lecture per week 15 weeks - 1-4 hours of lecture per week
Summer: 10 weeks - 1.5-6 hours of lecture per week
Additional Format: One to four hours of lecture per week. One and one-half to six hours of lecture per week for 10 weeks. Two to eight hours of lecture per week for 8 weeks.
Special Topics in Information: Read Less [-]
Terms offered: Fall 2024, Spring 2024, Fall 2023 Specific topics, hours, and credit may vary from section to section and year to year. Special Topics in Management: Read More [+]
Additional Format: One to four hours of lecture per week. Two to eight hours of lecture per week for 8 weeks.
Special Topics in Management: Read Less [-]
Terms offered: Fall 2024, Fall 2023, Spring 2023 Specific topics, hours, and credit may vary from section to section and year to year. Special Topics in Social Science and Policy: Read More [+]
Fall and/or spring: 8 weeks - 4-8 hours of lecture per week 15 weeks - 2-4 hours of lecture per week
Additional Format: Two to four hours of lecture per week. Four to eight hours of lecture per week for 8 weeks.
Special Topics in Social Science and Policy: Read Less [-]
Terms offered: Spring 2024, Fall 2023, Spring 2023 Specific topics, hours, and credit may vary from section to section and year to year. Special Topics in Technology: Read More [+]
Special Topics in Technology: Read Less [-]
Terms offered: Prior to 2007 Specific topics, hours, and credit may vary from section to section, year to year. Special Topics in Information: Read More [+]
Repeat rules: Course may be repeated for credit when topic changes.
Fall and/or spring: 15 weeks - 1-4 hours of lecture per week
Additional Format: One to four hours of lecture per week.
Grading: Offered for satisfactory/unsatisfactory grade only.
Instructor: Hoofnagle
Terms offered: Fall 2016, Summer 2016 10 Week Session, Spring 2016 This course is designed to help School of Information graduate students maximize their internship, practicum, or independent research experiences. Information Management Practicum: Read More [+]
Course Objectives: Experience the practical application of your academic knowledge to real-world professional contexts; Gain insight into an organization and how one might make a valuable contribution; Reflect on the information the experience has provided, to see if it fits within one’s personal value set and work/life manifestos. Try out various professional activities to see when you are in ‘flow’;
Student Learning Outcomes: Assess the organizational culture of a company, governmental body, or non-governmental organization Connect academic knowledge about information management to real-world professional contexts Evaluate the effectiveness of a variety of information science techniques when deployed in organizational situations Integrate the student's own individual professional goals with the organization's needs relevant to the internship or practicum Reflect critically on the internship or practicum experience
Prerequisites: Consent of a Head Graduate Adviser for the School of Information
Repeat rules: Course may be repeated for credit without restriction.
Fall and/or spring: 15 weeks - 1 hour of internship per week
Summer: 10 weeks - 1.5 hours of internship per week
Additional Format: One hour of internship per week. One and one-half hours of internship per week for 10 weeks.
Information Management Practicum: Read Less [-]
Terms offered: Spring 2024, Spring 2023, Spring 2022 An intensive weekly discussion of current and ongoing research by Ph.D. students with a research interest in issues of information (social, legal, technical, theoretical, etc.). Our goal is to focus on critiquing research problems, theories, and methodologies from multiple perspectives so that we can produce high-quality, publishable work in the interdisciplinary area of information research. Circulated material may include dissertation chapters , qualifying papers, article drafts, and/or new project ideas. We want to have critical and productive discussion, but above all else we want to make our work better: more interesting, more accessible, more rigorous, more theoretically grounded, and more like the stuff we enjoy reading. Doctoral Research and Theory Workshop: Read More [+]
Prerequisites: PhD students only
Fall and/or spring: 15 weeks - 2 hours of workshop per week
Additional Format: Two hours of workshop per week.
Doctoral Research and Theory Workshop: Read Less [-]
Terms offered: Fall 2024, Fall 2023, Spring 2023 Colloquia, discussion and readings designed to introduce students to the range of interests of the school. Doctoral Colloquium: Read More [+]
Prerequisites: Ph.D. standing in the School of Information
Fall and/or spring: 15 weeks - 1 hour of colloquium per week
Additional Format: One hour of colloquium per week.
Doctoral Colloquium: Read Less [-]
Terms offered: Fall 2024, Spring 2024, Fall 2023 Topics in information management and systems and related fields. Specific topics vary from year to year. Seminar: Read More [+]
Prerequisites: Consent of instructor
Fall and/or spring: 15 weeks - 2-4 hours of seminar per week
Additional Format: Two to Four hours of Seminar per week for 15 weeks.
Seminar: Read Less [-]
Terms offered: Fall 2019, Spring 2016, Fall 2015 Group projects on special topics in information management and systems. Directed Group Study: Read More [+]
Credit Restrictions: Students will receive no credit for INFO 298 after completing INFOSYS 298.
Fall and/or spring: 15 weeks - 1-4 hours of directed group study per week
Summer: 8 weeks - 1.5-7.5 hours of directed group study per week
Additional Format: One to four hours of directed group study per week. One and one-half to seven and one-half hours of directed group study per week for 8 weeks.
Directed Group Study: Read Less [-]
Terms offered: Spring 2022, Spring 2016, Spring 2015 The final project is designed to integrate the skills and concepts learned during the Information School Master's program and helps prepare students to compete in the job market. It provides experience in formulating and carrying out a sustained, coherent, and significant course of work resulting in a tangible work product; in project management, in presenting work in both written and oral form; and, when appropriate, in working in a multidisciplinary team. Projects may take the form of research papers or professionally-oriented applied work. Directed Group Work on Final Project: Read More [+]
Prerequisites: Consent of instructor. Course must be taken for a letter grade to fulfill degree requirements
Additional Format: One to four hours of directed group study per week.
Directed Group Work on Final Project: Read Less [-]
Terms offered: Fall 2023, Summer 2016 8 Week Session, Spring 2016 Individual study of topics in information management and systems under faculty supervision. Individual Study: Read More [+]
Fall and/or spring: 15 weeks - 1-12 hours of independent study per week
Summer: 8 weeks - 2-22.5 hours of independent study per week
Additional Format: Format varies.
Individual Study: Read Less [-]
Terms offered: Spring 2024, Fall 2021, Fall 2020 Discussion, reading, preparation, and practical experience under faculty supervision in the teaching of specific topics within information management and systems. Does not count toward a degree. Teaching Assistance Practicum: Read More [+]
Fall and/or spring: 15 weeks - 2 hours of lecture per week
Additional Format: Two hours of lecture per week.
Subject/Course Level: Information/Professional course for teachers or prospective teachers
Instructor: Duguid
Teaching Assistance Practicum: Read Less [-]
Terms offered: Spring 2016, Fall 2015, Spring 2015 Individual study in consultation with the major field adviser, intended to provide an opportunity for qualified students to prepare themselves for the various examinations required of candidates for the Ph.D. degree. Individual Study for Doctoral Students: Read More [+]
Fall and/or spring: 15 weeks - 1-5 hours of independent study per week
Additional Format: One to Five hour of Independent study per week for 15 weeks.
Subject/Course Level: Information/Graduate examination preparation
Individual Study for Doctoral Students: Read Less [-]
School of information.
102 South Hall
Phone: 510-642-1464
Siu Yung Wong
Julia Sprague
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MIS is an academic discipline that explores how information systems and data-centric applications in businesses and organizations are designed and how they affect society, behavior, and the economy. The study of MIS as a discipline includes topics such as neuroIS, technology acceptance, behavioral decision making, information technology governance, digital ethics, artificial intelligence and business analytics. Major supporting disciplines include psychology, economics, operations research and computer science. Request Information
Completion of the program requires a minimum of 60 semester credit hours beyond a bachelor's degree, not including dissertation hours from BA 8000. Students with a limited background in business will also be required to take additional leveling courses.
Typically, students complete all credit hours in residence at Texas Tech. Twenty-one semester credit hours must be taken in residence during a 12-month period. Generally, only three credit hours from outside institutions (provided there is an equivalent course at Texas Tech) may be counted toward the required 60 credit hours, if approved by the area's doctoral coordinator.
As part of the required 60 credit hours, students must complete Advanced Statistical Methods (ISQS 5347) and Practicum in Higher Education for Business (BA 5395).
To excel in the Area of MIS, students must possess scholarly competence and actively contribute to the advancement of the management field through research efforts. This implies a broad knowledge of the subject and its literature, as well as a detailed understanding of current research in a specific sub-area of MIS. Students will complete both core MIS courses and specialized courses, which can be tailored to meet individual objectives and interests with the guidance of a faculty advisor.
All students are expected to have adequate familiarity with MIS basics. These are defined by the following courses:
ISQS 7342 Advanced Topics in Information Systems and Quantitative Sciences
ISQS 7346 Seminar in Cognitive and Behavioral MIS Research
ISQS 7347 Seminar in Managerial and Organizational MIS Research
With the consent of their faculty advisors, students can choose a content-area concentration that matches their interests and career aspirations, such as getting hired, promoted or tenured. Seminar courses will touch each on content areas depending on the particular specializations of each faculty member teaching the course.
To ensure advanced development of analytical and research skills, students must pursue research methods as a supporting field. A minimum of nine credit hours (three courses) of supporting field coursework in research methods is required. Below is a non-exclusive list of potential research method courses.
ISQS 5349 Regression Analysis
ISQS 6348 Applied Multivariate Analysis
BA 6300 Advanced Business Research Methods; Structural Equation Modeling (SEM)
MGT 6381 Qualitative Methods & the Philosophies of Science
MGT 6381 Publishing Empirical Research and Scholarly Writing
BA 7000 Special Topics on Research Methods and Analysis
To reach the 60-hour requirement, students will work with faculty to determine the appropriate mix of elective and/or independent research coursework. Enrollment in these courses is associated with a student's preparation for their doctoral dissertation proposal or other research projects. Because doctoral proposals and other independent research require substantial faculty resources, enrollment will reflect the time required of faculty.
Upon completion of coursework, students are prepared for intensive examinations. The Qualifying Exam will cover material from all doctoral seminars, research seminar series and may also include material from the supporting fields. Students are expected to go beyond courses through intensive self-study of the research literature. The Qualifying Exam is composed of two components: a written exam and an oral exam.
After successfully completing the qualifying examination, students are admitted to candidacy. The dissertation represents the culmination of the doctoral program in which a student learns and demonstrates the ability to conduct independent research.
Students should select a Doctoral Dissertation Committee as early as possible during their studies. Generally, most dissertation committees are composed of three or four total faculty members. The committee must include a chair who is typically chosen before the completion of coursework once the student has identified an area of interest. The committee chair may assist in refining a topic, suggesting potential committee members, and establishing a timeline and structure for the dissertation. Additionally, the committee must include one additional tenured or tenure-track faculty member from the Area of ISQS.
Catering to students with diverse backgrounds, interests, and expertise, our program offers flexibility and choice in curriculum, allowing students to choose courses that match their research interests.
Our program aims to cultivate scholars who can conduct significant research in their chosen field. To enhance their research skills and develop strong competencies for conducting state-of-the-art research, students work closely with faculty in small classes, colloquiums, departmental workshops and seminars.
Students are also encouraged to interact with the professional community by attending and presenting papers at professional meetings. When possible, the Area of ISQS will provide financial support for this purpose.
Our alumni have secured competitive faculty positions at prestigious institutions across the globe.
The following is a detailed list of the initial placements and dissertation topics of our recent doctoral graduates over the last five years.
Kevin Harmon Dissertation Title: The Impact of System Latency on User Experience and Performance Dissertation Chair: Eric Walden Original placement: University of Arkansas
Ross Niswanger Dissertation Title: Oversharing on Social Network Sites: Self-Disclosure That Leads to Regret Dissertation Chair: Jaeki Song Original placement: University of Houston–Clear Lake
Report Your Placement
Inaiya Armeen Dissertation Title: Exploiting User Participation to Enhance User Experiment (UX): An Emotional Approach Dissertation Chair: Eric Walden Original placement: University of Alabama
Weihong Ning Dissertation Title: Impact of Social Network Sites (SNS) Addiction on College Student's Cognitive Performance Dissertation Chair: Fred Davis Original placement: Central Connecticut State University (Associate Professor)
Nakul Padalkar Dissertation Title: Evaluation of Blockchain Technology for Cycle Counting in Supply Chains with Information Discrepancies Dissertation Chair: Donald R. Jones Original placement: Georgetown University
Timothy Kaskela Dissertation Title: The Effects of Frames on People's Responses on Social Networks Dissertation Chair: Jaeki Song Original placement: Oregon State University
Yixiu Yu Dissertation Title: Three Essays on User Satisfaction, Dissatisfaction, Ambivalence, and Post-Adoption Behavior Dissertation Chair: Fred Davis Original placement: Ball State University
Gabriel Silva Cogo Dissertation Title: Understanding DevOps: From its Enablers to Impact on IT Performance Dissertation Chair: Donald Jones Original Placement: Fundacao Getulio Vargas (FGV) - Brazil
Saman Bina Dissertation Title: Information Avoidance in Requirements Determination Dissertation Chair: Dr. Glenn Browne Original Placement: Baylor University
Ying Wang Dissertation Title: Online Review and Product Sales: A Longitudinal Investigation in the Mulitlevel User-Generated Content Dissertation Chair: Jaeki Song, Miguel I. Aguirre-Urreta Original Placement: Northern Illinois University Current Position: Northern Illinois University Report Your Placement
Keas, Jacob "Jake"
PhD Student
Khasraghi , Bahar Javadi
PhD Candidate
Lee, Hansol
PhD Student Candidate
Nosrati, Saeed
Sanders, Yorick
Shaha, Dipu
Tahvildar, Ala
Please contact Shuo Yu with any questions about specializing in MIS as part of our doctoral program.
America needs transformative leaders in preK–12 education whose passion for education quality and equity is matched by a knowledge of learning and development, the organizational management skills to translate visionary ideas into practical success, and a firm grasp of the role of context and politics in shaping leadership. Graduates of the three-year, multidisciplinary Doctor of Education Leadership (Ed.L.D.) Program at the Harvard Graduate School of Education will be prepared to become those leaders.
The Ed.L.D Program — taught by faculty from the Harvard Graduate School of Education, the Harvard Business School, and the Harvard Kennedy School — will train you for system-level leadership positions in school systems, state and federal departments of education, and national nonprofit organizations. Ed.L.D. is a full-time, three-year program built on a cohort learning model. Cohorts consist of up to 25 students from diverse professional backgrounds (including district/charter management leaders, nonprofit directors, principals, teachers, and policy researchers) who progress through the program together.
All Ed.L.D. students receive a full tuition funding package plus stipends, work opportunities, and a paid third-year residency at a partner organization.
The Ed.L.D. Program prepares graduates to do work for the public good in the American public education sector, whether that be at the system or state level. Specifically, the program is designed to accelerate the progress graduates make toward achieving meaningful impact in influential roles and/or crossing boundaries in the following spaces in the public education sector:
The Ed.L.D. curriculum is a balance of multidisciplinary coursework and practice-based learning. Core courses and electives are taught by recognized leaders from across Harvard’s graduate programs in fields like data-based education reform, organizational change and innovation, and effective leadership strategies for urban schools. You will develop and test your leadership skills through team projects and an immersive third-year residency.
All students in the cohort take the same classes in four foundational content areas: learning and teaching, leadership and organizational change, politics and policy, adult development, and leadership inside and out (including one-on-one executive coaching). Courses taken during the first-year focus on practice-based learning and serve as the framework of your first-year experience.
View all courses in the Academic Catalog.
Each cohort member works with program advisers to choose an individualized sequence of electives from any of the Harvard graduate schools. You will work closely with the program faculty and staff during your second year to determine the best match with a partner organization for your third-year residency. Matches are driven by mutual interest between the resident and the partner organization, and each student's career and learning goals and geographic preferences.
You will take part in a 10-month paid residency at one of our partner organizations. There, you will work on a strategic project which synthesizes your experience and learning into a written Capstone project. You will stay connected to your Ed.L.D. cohort and HGSE through technology and by returning to Harvard periodically for intensive workshops.
Our partner organizations include school systems and departments of education, as well as some of the nation's most influential and dynamic nonprofit, mission-based for-profit, and philanthropic organizations.
You will be intentionally pushed out of your comfort zones and asked to work systemically and make a significant contribution to the partner organization. In addition, the residency will provide you with the professional mentoring, practical experiences, and network of connections they need to position themselves as future leaders in the education sector.
You will define (with supervisors from your partner organization) a strategic project on which to focus. You will have the opportunity to lead one or two major efforts on behalf of the organization, such as the creation or implementation of current initiatives. The project allows you to practice and improve leadership skills, add important value to the mission and strategy of the partner organization, work systemically, and hold high-level accountability.
During the residency period, you will produce a written Capstone. The Capstone is a descriptive, analytic, and reflective account of your third-year leadership contributions to a strategic project within an Ed.L.D. partner organization. It is a demonstration of your ability to engage others, develop strategy to successfully address and diagnose challenges, work toward a vision and goals, and learn from the results.
Sample Topics
Sample Summaries
GSE Theses and Dissertations from Digital Access to Scholarship at Harvard (DASH)
Ed.L.D. students learn with renowned faculty from the Harvard Graduate School of Education, Harvard Business School, and Harvard Kennedy School. Faculty from the three schools share their individual expertise in the Ed.L.D. Program and work collaboratively to provide a challenging and coherent experience for students. Faculty who teach in the Ed.L.D. core curriculum and advise Ed.L.D. students include:
Frank Barnes is faculty director of the Doctor of Education Leadership Program. He has over 30 years experience as an educator, researcher, and organizer. As a chief accountability officer, he led turnaround efforts for large public school districts, including Boston Public Schools and Charlotte-Mecklenburg Schools.
Deborah helsing.
Martin west.
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After a trip to meet with the Dalai Lama, an Ed.L.D. student says we do
As post-COVID absenteeism rates continue unabated, a look at how strong family-school engagement can help
Umgc offers online master’s degrees in today’s most in‑demand fields..
Unlock your potential with an online master’s degree from University of Maryland Global Campus. Gain workplace-ready skills in high-demand subject areas, and build graduate-level leadership , management , and communication skills to help take your career to the next level. Most of our programs are rounded out by a research or capstone experience that allows you to put your knowledge into practice. And with more than 40 master’s degrees and concentrations, you can start building your professional value right away.
You can get a head start on many of our master's degrees if you’ve taken the appropriate undergraduate coursework or earned a graduate certificate at UMGC.
Did you know eligible active-duty military students, reserves, and their spouses and dependents who enroll in most master's programs could save 30 percent per credit with a low-cost tuition rate? Learn about our military tuition rate eligibility .
Accounting & Financial Management
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Biotechnology: Biosecurity & Biodefense
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Biotechnology: Biotechnology Regulatory Affairs
Business Administration (MBA)
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CyberAccounting
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Distance Education & E-Learning
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Healthcare Administration
IT: Database Systems Technology
IT: Homeland Security Management
IT: Informatics
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IT: Systems Engineering
Instructional Technology
Learning Design & Technology
Management: Accounting
Management: Criminal Justice Management
Management: Emergency Management
Management: Financial Management
Management: Homeland Security Management
Management: Human Resource Management
Management: Information Systems
Management: Intelligence Management
Management: Interdisciplinary Studies in Management
Management: Marketing
Management: Project Management
Strategic Communications
Transformational Leadership
With a variety of innovative, career-focused online master’s degrees to choose from, UMGC is a great choice for the next step in your education journey.
Compare programs online: Evaluate up to three degrees , concentrations, and certificates side by side. Explore program descriptions, cost, transfer credit, program formats, course content, and more.
Estimate your costs: Found your program? Estimate your tuition , fees, other costs, and graduation date using our helpful online tools.
Gain lifetime career services: UMGC has relationships with many employers and offers virtual recruiting events with companies who are actively seeking to fill current openings.
Learn at a respected university: Take courses online knowing that your education is backed by the reputation of a public state university .
In addition to the specific course requirements outlined on each master's degree webpage, UMGC maintains certain requirements for all master’s degrees.
Fast-track a master's degree at UMGC by completing an eligible undergraduate program that maps to the graduate program requirements.
Through the dual degree option at UMGC, you may be able to earn a second master's degree with only a few courses.
Jessica P, .Bowie, MD Doctor of Business Administration (DBA)
Natalie A. MS in Management: Human Resource Management
Eric S. MS in Healthcare Administration and MBA
At UMGC, we want you to be happy with the investment you make in your education. UMGC’s online graduate programs provide flexibility and convenience for working adults, and we provide the student support and resources you need to succeed. We offer high-quality, relevant coursework delivered online from an accredited state university backed by the reputation of the University System of Maryland and work hard to make higher education accessible and affordable for everyone. If you don't want to commit to a master's degree just yet, consider starting with a certificate. The graduate certificates can be completed in as few as 12 to 18 credits and can then be applied to the related master's degree.
Several of our online master's degrees carry program-specific accreditations. At the university level, University of Maryland Global Campus (UMGC) is accredited by the Middle States Commission on Higher Education (MSCHE) , an institutional accrediting agency recognized by the U.S. Secretary of Education and the Council for Higher Education Accreditation. This accreditation means that UMGC meets the standards for quality and integrity set by the accrediting agency.
The length of time it takes to complete an online master's degree at UMGC varies depending on a number of factors, including the specific program you choose, the number of credits required, the number of transfer credits you have , and the number of credits you are able to fit into your schedule each term. At UMGC, master’s programs are generally 36 credits. UMGC’s online Master of Business Administration can be completed in 18 months.
UMGC focuses on helping busy professionals like you earn the credit you deserve so you can graduate sooner, save money, and prepare for your next success. While UMGC offers generous transfer credit policies for working adults , opportunities to apply transfer credits to graduate coursework are more limited than opportunities to apply transfer credits to undergraduate coursework. Once you have applied to UMGC and are ready to start your graduate program, you can submit a graduate transfer credit evaluation form to see if your credits may transfer.
Our helpful admissions advisors can help you choose an academic program to fit your career goals, estimate your transfer credits, and develop a plan for your education costs that fits your budget. If you’re a current UMGC student, please visit the Help Center .
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Exponential growth in data has translated into a demand for data scientists that outpaces how fast universities can train them. But what are the best options if you’re looking to break into data science and don’t have time for in-person classes? To answer that question, Fortune built our second ranking of online data science graduate programs. This ranking was last updated January 2023.
23. pace university.
Pursuing a master’s degree in the fast-growing field of data science can help you to advance your career in a wide variety of tech-related roles. Expect to learn a broad set of skills, including how to use computer programming languages and about applied statistics, database systems, and machine learning. The skills and concepts you learn in a master’s degree program will prepare you for a career in data science to help organizations make strategic decisions based on the data they collect. There’s no significant difference between online and on-campus data science programs—schools typically offer the same courses that are taught by the same professors, regardless of the format.
You can expect a comprehensive curriculum in an online master’s degree program in data science that draws on both statistical and computational methods. Programs will emphasize the real-world application of these knowledge and skills, while offering a multidisciplinary approach to the field that also draws on statistics, computer science, and law. Data science is about more than numbers, however; you will also learn “soft skills” about how to effectively communicate the lessons learned and collaborate with others to learn how to best utilize information in an ethical way . Core coursework at many data science programs covers the following topics:
Beyond the core and advanced-level coursework that are common among all data science programs, some schools also offer mandatory or optional project-based learning opportunities. These projects focus on the real-world application of the skills learned in the program, and can be an opportunity for students to display the skills learned during a program to potential employers. The master’s degree programs at both the University of California-Berkeley and Bay Path University , for example, both include a culminating capstone project that draws upon the skills learned throughout the course of the program. Such projects may extend the length of a master’s degree program, however.
While the core coursework required for completing a master’s degree in data science is intentionally comprehensive, many programs offer specializations or concentrations so students can carve out a niche within this field. The University of Illinois at Urbana-Champaign offers advanced coursework in cloud computing and scientific visualization, while Texas Tech University has advanced coursework in multivariate analysis and project management. Concentration options may include:
While admissions requirements can vary by school, graduate degree programs require the following of aspiring data scientists :
A majority of online master’s degree programs in data science have waived GRE or GMAT score requirements and, in fact, only two schools on Fortune’s ranking still require applicants to submit scores as part of that application process. That said, you may submit this information particularly if you want to provide additional supporting information that’s helpful in the admissions process. Moreover, GPA requirements also vary by school and may be waived with sufficient work experience.
While admissions officers strive to take a holistic approach when evaluating candidates, they will be particularly interested in your educational background and work experience in a data-related field. Applicants to some data science programs, like the University of Wisconsin-Madison and the University of Connecticut , must show they’ve completed particular quantitative college-level coursework, while other programs like Syracuse University place a greater emphasis on the personal essay and what applicants emphasize they’re looking for in the program, why they chose it, and what their goals are.
Online learning has been growing in popularity in recent years, and students considering a master’s degree program in data science can often choose between an in-person or online option within the same school. Data science programs may offer a mix of both synchronous and asynchronous learning, meaning courses that either need to be attended live at a particular time or at the student’s convenience, and could include some limited in-person elements.
For the most part, students can expect to participate in class discussions via video conferencing or using other technology. And because of the online format, many students who pursue a master’s degree in data science are working while attending school with a goal of either switching careers or advancing their current career in data science.
Fortune’s ranking of online master’s degree programs in data science is a good starting place when comparing various programs. We emphasize selectivity (schools with top-notch faculty that attract some of the brightest students) and demand (based on the size of the student body), since the people you meet in graduate school could be transformative to your future career.
That said, prospective students should also consider how a particular program will help you achieve your goals and advance in the field of data science. Other factors that may be important include cost, a school’s prestige, its curriculum, and the years of work experience schools may require of applicants.
As data science programs have grown in popularity, schools have beefed up the number of start dates they offer. The University of Illinois and UC Berkeley, the No. 1 and No. 2 ranked programs, both offer three start dates throughout the year. Students may have some flexibility in choosing their schedule and how long it takes to complete the program of their choice, though two years is common.
As indicated, some data science programs include project-based learning opportunities that focus on the real-world application of skills taught in the program. Because these projects can be useful to show potential employers, career switchers may want to consider prioritizing schools with project-based learning opportunities—even if they could extend the program’s length.
As you think about your career goals post-graduation, you should also consider the concentrations offered by various data science programs. By carving out a specialty within data science, that may make you a more attractive job candidate for some employers—and it could increase your earning potential. People with the title of “data scientist” can earn up to $170,000, while manager-level professionals in the field could fetch salaries of as much as $250,000.
The cost of a data science program is undoubtedly a factor to consider when applying to school—and tuition varies widely. Students may be able to pay one-year tuition of about $20,000 (or less) at schools like the University of Illinois Urbana-Champaign, Loyola University Maryland, the University of Missouri-Columbia, and CUNY School of Professional Studies. That said, the cost of tuition exceeds $50,000 at UC Berkeley, Syracuse University, and the University of Denver.
The more students a data science program has, the larger its alumni network. This is important to consider during your selection process, not only because your cohort can be a defining characteristic of your grad school experience even if you’re attending classes online. What’s more, the network and a school’s ability to connect you with alumni may help you when looking for jobs—and particularly if you’re not already working in the field.
Because many data science programs are seeking out applicants who already have relevant work experience, it may be useful to see how your experience compares. What’s more, the amount of work experience will inherently influence how advanced your fellow students are in their careers. Worcester Polytechnic Institute reports that students have an average of 8 years of work experience, while roughly half of the master’s degree students in New York University’s program enroll straight out of undergrad.
There’s a hot job market for data scientists thanks to robust demand—and that means many graduates of master’s degree programs are fielding multiple, six-digit salary offers. Big tech companies are a likely career path for many data scientists. A survey of more than 11,000 data scientists found that the companies with the largest teams of data scientists are Microsoft, Facebook, and IBM. And Apple, for example, pays as much as $182,000 for data scientists.
If your goal of obtaining a master’s degree in data science is to advance within your current company, then your employer may help pay for the cost of the program. New York University grants tuition scholarships to some master’s degree students, while UC Berkeley offers several fellowships of varying amounts.
You may also want to seek out a growing number of scholarship or fellowship opportunities from private organizations. Some examples that are available to master’s degree students include:
Finally, current members of the military or veterans may want to consider covering the cost of your data science program with Post-9/11 GI Bill benefits or the Yellow Ribbon Program , which can cover any tuition and fees not covered by those benefits.
While still relatively new, data science is a field that incorporates preparing and analyzing data to draw conclusions. Data scientists design and build new processes for data modeling by using algorithms, prototypes, predictive models, and custom analysis. People should pursue data science if they’re interested in asking questions and creating algorithms and statistical models to estimate the unknown.
All of the data in the world is projected to grow to a staggering 181 zettabytes by 2025. And this growth has translated into high demand for data scientists—even outpacing the speed with which colleges and universities can train them. Data scientist ranks No. 3 among the 50 best occupations in the U.S., according to Glassdoor’s list of the best jobs for 2022 , and was beat out only by the roles of enterprise architect and full stack engineer.
Some people may choose to follow a step-by-step guide to become a data scientist. First, you may want to pursue an undergraduate degree that focuses on technical skills like programming or statistics. Then, you should identify an area of specialization and hone this specialization by enrolling in a master’s degree program in data science. Finally, you should showcase your data science experience when applying for jobs.
In addition to high demand, people with a master’s degree in data science can expect to enter a rapidly-growing field with solid salary prospects. Through 2026, the U.S. Bureau of Labor Statistics (BLS) projects data science jobs will grow by 28% per year . Even before graduation, some data science students in master’s degree programs are fielding offers of $125,000 and up .
As with any career, pay prospects can vary by company and role. Data scientists made a median salary of $164,500 in 2020, according to a 2021 survey of engineering professionals by the Institute of Electrical and Electronics Engineers (IEEE).
The median base salary for data scientists is $120,000, according to figures from Glassdoor, though the likely range for positions goes as high as $294,000. Some tech companies are even paying in excess of $300,000 for senior-level data scientist roles.
The sky’s the limit for job opportunities for data scientists, including careers in tech, entertainment, pharmaceuticals, telecom, sports, consulting, or even as a company executive who understands data. What’s more, new job titles are likely to be created, particularly related to ethical concerns with sensitive data and as companies look for new ways to utilize their massive data sets and emerging technologies such as cloud computing, A.I., and machine learning.
In 2012, Harvard Business Review called the role of a data scientist “ the sexiest job of the 21st century .” Ten years later, data science remains a good career field for many people thanks to the wide range of jobs available now and in the future, along with robust demand and six-figure salary prospects.
The class of 2022 from master’s degree programs in data science were fielding job offers, with competitive salaries, months ahead of graduation. Demand for data scientists is growing faster than colleges and universities can train them. Even so, job applicants should still expect a rigorous interview process that often entails showcasing examples of work or a commitment to staying up-to-date in a rapidly changing industry.
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Higher education in the U.S. is experiencing a resurgence in international student enrollment, leading institutions to look closer at how best to appeal to the students and accommodate their unique needs. Just four years ago, colleges and universities across the nation were dealt a major blow to international student enrollment with the arrival of the COVID-19 pandemic. Travel restrictions, Visa delays and concerns over in-person learning caused the steepest decline yet (12%) in new international students enrollment in the U.S.
If you’re considering charting a course towards a career in business, it’s good to know that the breadth of the field offers so many options in terms of industries you can work in and what kinds of roles you can consider pursuing. But with so many options, how do you know you’re taking the right path? When pursuing a bachelor’s degree in business, how do you know whether a bachelor’s in business administration vs. business management is the right degree program for you?
What types of certificate and degree programs does devry offer.
We offer associate, bachelor’s and master’s degree programs as well as undergraduate and graduate certificate programs. Our programs cover an array of topics in business, technology, healthcare, media arts and liberal arts. With a degree or certificate from DeVry , you might pursue careers in areas such as accounting, finance, information technology, project management, cyber security, marketing, medical billing and coding, healthcare administration, networking and more.
Yes. DeVry University is accredited by The Higher Learning Commission (HLC, www.hlcommission.org ) and our Keller Graduate School of Management is included in this accreditation. HLC accreditation is recognized by both the U.S. Department of Education and the Council for Higher Education Accreditation. Earning your degree from an accredited university is important because it signifies that DeVry has met high standards of quality and is committed to helping you get the education you deserve.
Scholarships, grants, loans and more – when it comes to financing your education , there are many options to explore. Since each student’s needs are unique, we recommend speaking with a DeVry Representative to determine the best solution for you. Earning your degree may be more cost-effective than you might think.
Online college classes offer you the flexibility to study at a time and place that works for you. In most courses, the syllabus is separated into 8 one-week increments, allowing you a full week to complete the work. Each class is taught in our online course platform by a professor who is experienced in their field of study and allows for plenty of peer interaction. You’ll also have access to an array of student resources such as tutoring support, an e-library and career services.
Yes. Prior learning credit gives you the opportunity to earn college credit based on your previous qualifying work experience or training. If you think you may have qualifying experience, your Student Support Advisor will work with you to complete the evaluation process.
To enroll at DeVry, you must meet our standard admissions requirements for the program you want to pursue. If you have transfer credits from a previous school, our Admissions Team can help you submit your transcripts for evaluation. Any qualifying credits can be applied to your new program, potentially saving you time and tuition costs as you complete your degree. Visit our transfer student page to learn more about our transfer credit process and the many
Contact us today to take the first step and get connected with a Representative. Our Admissions Team will walk you through the process of finding the right program for you, exploring financing options and enrolling in your first class.
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*This amount will be determined based on prevailing tuition rates at the time funds are awarded. 1 DeVry University is accredited by The Higher Learning Commission (HLC), www.hlcommission.org. The University’s Keller Graduate School of Management is included in this accreditation. 2 Each student is allotted a set number of hours of tutoring per academic session through www.Tutor.com (available 24/7). Additional tutoring services are also available through www.DeVryTutors.com.
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In New York, DeVry University operates as DeVry College of New York. DeVry University is accredited by The Higher Learning Commission (HLC), www.hlcommission.org . The University’s Keller Graduate School of Management is included in this accreditation. DeVry is certified to operate by the State Council of Higher Education for Virginia. Arlington Campus: 1400 Crystal Dr., Ste. 120, Arlington, VA 22202. DeVry University is authorized for operation as a postsecondary educational institution by the Tennessee Higher Education Commission, www.tn.gov/thec . Lisle Campus: 4225 Naperville Rd, Suite 400, Lisle, IL 60532. Unresolved complaints may be reported to the Illinois Board of Higher Education through the online complaint system https://complaints.ibhe.org/ . View DeVry University’s complaint process https://www.devry.edu/compliance/student-complaint-procedure.html Program availability varies by location. In site-based programs, students will be required to take a substantial amount of coursework online to complete their program.
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COMMENTS
Graduate Tuition/Fees: $7,165. One of the top schools with PhD in management information systems online programs is the University of North Texas. This accredited university offers a PhD in information science, which offers a flexible format and learning plan that can be tailored for most students.
In this specialization, you will explore an integrative approach to all aspects of organizations, including people, processes, technology, systems, and management. Focus your studies on developing knowledge, systems integration and application, and teaching to yield maximum benefits from systems architectures, big data, cloud computing, and ...
Per-credit tuition rates for the 10 qualifying Ph.D. programs in our guide range from. $450 to $1,575. Over the course of a typical 60-credit Ph.D. program, this translates to between $27,000 and ...
Ph.D. in Systems Engineering. George Washington University has an online PhD in Systems Engineering program that we have ranked among the best management information systems online PhD programs. This program requires a minimum of 54 credit hours for graduation and is designed to be completed in just three years.
Why Dakota State University Has the Best Online PhD Program in Management Information Systems. Dakota State University has the best online PhD program because it is affordable and can be completed by students who don't have a master's degree. Tuition is only $470.45 per credit for residents or $580.60 per credit for non-residents, while ...
National University is accredited by the WASC Senior College and University Commission. 12. Nova Southeastern University. Nova Southeastern University's PhD in Information Systems program is a 67 credit program that requires seven core courses, two doctoral research courses, and a final dissertation to complete.
The PhD in Business Administration with a focus in Management Information Systems is a five-year full-time program. Consistently ranked among the best information systems PhD programs worldwide, the program is known for its cutting-edge research and support from actively publishing faculty. The program prepares future information systems ...
An Online Management PhD Program That Prepares You to Make an Impact. ... These specializations include Organizational Design and Innovation, Information Systems Management, 21st Century Finance, Leadership and Organizational Strategy, and Human Resource Management. The Self-Designed option gives you the opportunity to create your own PhD in ...
At Heinz, we live and work at the critical nexus of information technology and public policy. Our Ph.D. in Information Systems & Management was created to train scholars to conduct innovative research that cuts across disciplines in order to address significant challenges in IT theory, strategy, management, and design as it relates to business and policy settings.
The School of Information offers four degrees: The Master of Information Management and Systems (MIMS) program educates information professionals to provide leadership for an information-driven world.. The Master of Information and Data Science (MIDS) is an online degree preparing data science professionals to solve real-world problems. The 5th Year MIDS program is a streamlined path to a MIDS ...
Information systems level: expert. Master, develop, and support new IT innovations with a flexible doctoral program. Online, on-campus, part-time or full: it's your call. This gratifying degree prepares you for a career in research, teaching, or administration. Choose from three specializations: analytics, security, or health care.
Management Information Systems. The PhD program in MIS is designed to produce world-class scholars in Management Information Systems. We measure our goal in the ability to place our PhD students in institutions where research, teaching, and service are encouraged and rewarded. In line with this objective, we train our PhD students to recognize ...
The MIS PhD program starts with a solid foundation in research methodology, then builds on this with a synthesis of state-of-the-art technologies and approaches that span multiple disciplines. Through a mix of hands-on and theoretical work, you'll master skills and subjects valued in academia and the private sector. Explore The Plan of Study.
Earning an Online Ph.D. in Management Information Systems. If coming up with creative ways to improve business functions while making a six-figure income sounds appealing to you, consider earning an online Ph.D. in management information systems (MIS). This degree equips graduates to earn the credentials to lead successful companies.
This online PhD in management information systems degree provides students with the training needed to work in information assurance. A total of 60 credit hours are needed to complete this program of study. The University of the Cumberlands has received accreditation for this program from the Southern Association of Colleges and Schools ...
Online Doctor of Business Administration in Management Information Systems The online DBA in Management Information Systems is a low-residency program. Website. Tuition: $54,900. The low-cost Ph.D. in Management Information Systems online degree that is offered by Baker College is focused on business administration through the perspective of ...
The Information Systems Doctoral program at the Naveen Jindal School of Management offers an outstanding opportunity for research in the Information Systems discipline. Our faculty's research productivity usually ranks at the top in the world. More importantly, we work at the forefront of a variety of research topics and methodologies.
PhD in Information Systems. NU's Information Systems specialization is designed for students who want to know how computers work together to maintain, store and process information most efficiently and effectively. With this broad-based, but foundational perspective on technology information management, you may find yourself in high demand.
What is Management Information Systems? MIS faculty teach and research about the application of information systems in organizations. This includes the study of social networks, cloud computing, IT consumerization, virtual reality, negotiation systems, collaboration technologies, office automation, electronic payments, strategic information systems, electronic commerce, collective intelligence ...
Learn about the Information Systems and Technology Management doctoral program at the George Washington University School of Business. ... (three-credits) courses to meet the required 45 credit hours for the PhD degree. The ISTM Ph.D. Program requires students to take a minimum of 45 credits during their program, including 27 credits in core ...
The PhD program in information systems (IS) prepares students for an academic career of scholarly research and university-level teaching.From studying human-computer interaction, online reviews and social media design, to IS implementations and strategy, doctoral students explore real-world IS problems using a variety of methods, including surveys, experiments, archival data analysis, and ...
To be eligible to apply to the PhD in Information Management and Systems program, applicants must meet the following requirements: A bachelor's degree or its recognized equivalent from an accredited institution. Superior scholastic record, normally well above a 3.0 GPA. Indication of appropriate research goals, described in the Statement of ...
PhD in Business Administration Specialization in Management Information Systems (MIS) MIS is an academic discipline that explores how information systems and data-centric applications in businesses and organizations are designed and how they affect society, behavior, and the economy.
The Ed.L.D Program — taught by faculty from the Harvard Graduate School of Education, the Harvard Business School, and the Harvard Kennedy School — will train you for system-level leadership positions in school systems, state and federal departments of education, and national nonprofit organizations. Ed.L.D. is a full-time, three-year ...
UMGC offers online master's degrees in today's most in‑demand fields. Unlock your potential with an online master's degree from University of Maryland Global Campus. Gain workplace-ready skills in high-demand subject areas, and build graduate-level leadership, management, and communication skills to help take your career to the next level.
Master of Science in Electrical Engineering. #5 in Best Online Master's in Electrical Engineering Programs (Guide to Online Schools, 2020) Application due June 13, 2024. Illinois Tech.
The University of Houston strives to provide affordable and accessible education to a diverse student body, including first-generation college students. UH offers over 250 undergraduate and graduate degree programs across a wide range of disciplines, including business, engineering, education, health, law and the arts. About UH. 20 24.
10. University of California-Los Angeles. Los Angeles, CA. The University of California—Los Angeles requires applicants to its online master's in data science program to submit a GRE score ...
These programs marry technical curriculum with a background in professional skills like management, finance and communication. READ MORE. # 1. Massachusetts Institute of Technology. Cambridge, MA ...
Online College Degrees at DeVry University. Whether you're hoping to advance in your industry, explore a new career field or accomplish your next education goal, the chance to pursue your dreams as an online university student is waiting for you at DeVry. With on-demand tutoring and a virtual library available 24/7 2 , along with caring faculty ...