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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:

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.


Program Learning Outcomes


fACULTY PERSPECTIVE


At a Glance

Earn your master’s fully online in 20-24 months.

Summer, Fall & Spring start dates

20-24 Months
30-36 Units
$965
May 7
April 8
Choose Format

Master of Science in Applied Data Science

Orientation

Course Units

This orientation course introduces students to the University of San Diego and provides important information about the program. Throughout …

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0

Semester 1

7 weeks per course

Course Units

This course is an introduction to probability and statistical concepts and their applications in solving real-world problems. This prerequis…

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3

This course is an introduction to fundamental concepts of programming and problem-solving techniques for data science. Python and R are the …

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3

Semester 2

7 weeks per course

Course Units

This course covers an introduction to the methods, concepts, and ethical considerations found and practiced in the field of professional dat…

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3

Data Mining is one of the most important topics in the data science field. This course discusses theoretical concepts and practical algorith…

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3

Semester 3

7 weeks per course

Course Units

This course provides a working knowledge of applied predictive modeling. Students will obtain a broad understanding of model training, evalu…

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3

This course covers the study of supervised and unsupervised algorithms in the Machine Learning context. Emphasis on formulating, choosing, a…

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3

Semester 4

7 weeks per course

Course Units

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…

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3

Many datasets naturally have a time series component: records collected over time, financial data, biological data signals such as brain wav…

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3

Semester 5

7 weeks per course

Course Units

In this course, students will learn about the discipline of data engineering. They will learn what data engineers are, what they do and how …

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3

This course covers the fundamental concepts of cloud computing as it impacts the field of data science. Course topics include cloud economic…

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3

Semester 6

7 weeks per course

Course Units

This course focuses on natural language processing and data mining of text using Python. Topics include collecting and preparing text data, …

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3

The purpose of this Capstone Project is for students to apply their acquired theoretical knowledge obtained during the Applied Data Science …

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3

Calendar

Interested in a Data Science Career?

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MADS webinar cover for High Paying Careers in a fast growing field