Post-Baccalaureate Certificate in Computational Data Science

Certificate Level: Graduate
Admission Requirements: Bachelor's degree
Certificate Type: Post-Baccalaureate
Number of Credits to Completion: 15.0
Instructional Delivery: Online; Campus
Calendar Type: Quarter
Expected Time to Completion: 1 year
Financial Aid Eligibility: Aid eligible*
Classification of Instructional Program (CIP) Code: 11.0701
Standard Occupational Classification (SOC) Code: 11-3021

*The current plan of study for this program would only allow for federal financial aid (including Federal Direct Student Loans) for terms that are at least a minimum of 4.5 credits for graduate courses and 6.0 credits for undergraduate courses. This is based on current regulations from the U.S. Department of Education.

About the Program

The Post-Baccalaureate Certificate in Computational Data Science accepts applicants who hold bachelor degrees in computer science or completed a Post-Baccalaureate Certificate in Computer Science Foundations, and offers them opportunities to learn the fundamentals of artificial intelligence and machine learning. The aim is to provide a strong foundation in this emerging area, with a focus on mathematical foundations, algorithms, and real-world applications.

Admission Requirements

Please visit the College of Computing & Informatics website to learn more about admission requirements.

Program Requirements

Required Core Courses
DSCI 511Data Acquisition and Pre-Processing3.0
DSCI 521Data Analysis and Interpretation3.0
Elective Courses9.0
Choose 3 from the following:
Fundamentals of Databases
Introduction to Artificial Intelligence
Introduction to Computer Vision
Machine Learning
Deep Learning
Data Analysis at Scale
Responsible Data Analysis
Total Credits15.0

Sample Plan of Study 

First Year
FallCreditsWinterCreditsSpringCredits
DSCI 5113.0Electives6.0Elective3.0
DSCI 5213.0  
 6 6 3
Total Credits 15

Additional Information

For more information about this program, please visit the College of Computing & Informatics website.

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