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Master of Science in Applied Data Science
Curriculum
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Innovative Curriculum Tailored to the Needs of Industries and Employers
The Master of Science in Applied Data Science (MS-ADS) curriculum is designed to equip graduates with the technical strategies and skills they will use to apply powerful and modern analytical tools to real-world applications.
The program culminates in a Capstone experience that pairs them with fellow students, instructors and potential industry partners on an in-depth project that hones their ability to apply their skills in the workplace.
Designed to be completed in 20 months over five semesters, the program requires students to complete 30 academic units plus 6 prerequisite units (note: the prerequisites may be waived depending on a candidate’s education and experience in mathematics, engineering, programming, computer science and analytics). Of the 30 academic units:
- 6 units focus on introductory topics and fundamentals
- 21 units cover technical aspects essential to the field of data science
- 3 units are dedicated to the comprehensive Data Science Capstone Project
Each course is seven weeks long (except for the Capstone), with two courses offered each semester; the entire program can be completed in 20 months. The master’s degree you will earn as an online graduate student is the same as that earned by campus-based students.
The MS-ADS program has been developed by data science experts in close collaboration with key industry and government stakeholders to provide in-depth practical and technical training designed to position graduates for career success in this vitally important and fast-growing field.
All courses in the program are instructor-led and asynchronous, enabling you to work on your assignments on your own schedule while still meeting deadlines. If you are balancing coursework with a full-time job or other time commitments, asynchronous learning offers you a great deal of flexibility. Materials needed for assignments are readily accessible so you can access them and do your classwork when the time is right for you.
The courses are specially designed for online learning with the course content prepared by your professor with input and support from the academic director and the program’s board of advisors. In addition, professors may choose to offer live virtual events such as office hours; however, such events are optional, and all live sessions will be recorded. Attendance during live events is always optional in consideration of students who may not be available during those designated times. Students will interact with their peers asynchronously through weekly discussion posts, and some courses may include practical team projects.
20
Average number of months it takes to graduate from the program
15–18
Average number of hours of coursework to expect each week
Program Learning Outcomes
- Successfully create, apply, and practice the mastery of data science methods, tools, and programming abilities (technical skill sets) for the analysis of structured and/or unstructured datasets.
- Learn, develop, and demonstrate non-technical skill sets, such as problem-solving, statistical thinking, creativity, critical thinking, storytelling, presentation ability (written and oral), and other soft skills in addressing data-driven projects. Build high-performing and compelling data science teams.
- Apply data science and data engineering related to AI, machine learning, and predictive modeling for the development of data-driven products, business strategies, and actionable insights.
- Evaluate ways data science positively impacts enterprise and society. Recommend strategies for partitioning and protecting data based on ethics, regulatory, and other requirements.
- Serve as active leaders and managers of data science multiple functions within organizations.
fACULTY PERSPECTIVE
Master of Science in Applied Data Science Courses
| Course | Units |
|---|---|
|
This orientation course introduces students to the University of San Diego and provides important information about the program. Throughout … |
0 |
|
This course is an introduction to probability and statistical concepts and their applications in solving real-world problems. This prerequis… |
3 |
|
This course is an introduction to fundamental concepts of programming and problem-solving techniques for data science. Python and R are the … |
3 |
|
This course covers an introduction to the methods, concepts, and ethical considerations found and practiced in the field of professional dat… |
3 |
|
Data Mining is one of the most important topics in the data science field. This course discusses theoretical concepts and practical algorith… |
3 |
|
This course provides a working knowledge of applied predictive modeling. Students will obtain a broad understanding of model training, evalu… |
3 |
|
This course covers the study of supervised and unsupervised algorithms in the Machine Learning context. Emphasis on formulating, choosing, a… |
3 |
|
Data science skills are in high demand across a wide variety of industries. This course focuses on real-world use cases of data mining appli… |
3 |
|
Many datasets naturally have a time series component: records collected over time, financial data, biological data signals such as brain wav… |
3 |
|
In this course, students will learn about the discipline of data engineering. They will learn what data engineers are, what they do and how … |
3 |
|
This course covers the fundamental concepts of cloud computing as it impacts the field of data science. Course topics include cloud economic… |
3 |
|
This course focuses on natural language processing and data mining of text using Python. Topics include collecting and preparing text data, … |
3 |
|
The purpose of this Capstone Project is for students to apply their acquired theoretical knowledge obtained during the Applied Data Science … |
3 |
MS-ADS Degree plan
Degree candidates are admitted throughout the year to begin their program during one of three terms (spring, summer or fall). Students will take two courses during each 14-week term, focusing on one seven-week course at a time. This master’s degree program can be completed, on average, in five terms (20 months).
Download a PDF of your degree plan that corresponds with your start term.
Important dates for your starting term will be found in the degree plan. Important dates for subsequent terms can be found in your student success center after acceptance.
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