Computational Data Science, Certificate
The Computational Data Science certificate program provides students/professionals with the skills and training to tackle real-world data analysis challenges. Students obtain in-depth knowledge of data science through lectures and hands-on studies of motivating real-world cases.
The curriculum consists of a total of five courses, including two required core courses and three electives. The core courses cover fundamental big data programming skills, statistical and mathematical concepts, essential data analysis techniques including data wrangling, data organization, and data visualization, as well as application and implementation of machine learning algorithms. The electives allow students to dive further into data analytics and address data challenges in their desired direction of study.
The program is designed for motivated graduate students and professionals holding a bachelor's degree who have an interest in data science, especially in the computational aspect of data science. Students must have a strong foundation in programming and experience with computational data handling.
Admission Requirements
Students must hold a bachelor's degree, and have a strong foundation in programming and experience with computational data handling.
Summary
Code | Title | Hours |
---|---|---|
Data Science Core | 6 | |
Data Science Electives | 9 | |
Total Hours | 15 |
Data Science Core
Code | Title | Hours |
---|---|---|
CPSC:515 | Big Data Programming | 3 |
CPSC:536 | Applied Machine Learning | 3 |
Total Hours | 6 |
Data Science Electives
Code | Title | Hours |
---|---|---|
Complete nine credits from the following: | 9 | |
CPSC:535 | Algorithms | 3 |
CPSC:545 | Introduction to Bioinformatics | 3 |
CPSC:560 | Artificial Intelligence & Heuristic Programming | 3 |
CPSC:575 | Database Management | 3 |
CPSC:576 | Introduction to NoSQL Data Management | 3 |
CPSC:577 | Introduction to Parallel Processing | 3 |
CPSC:635 | Advanced Algorithms | 3 |
CPSC:636 | Graph Analytics | 3 |
CPSC:658 | Visualization | 3 |
CPSC:676 | Data Mining | 3 |
CPSC:677 | Parallel Processing | 3 |
CPSC:678 | Data Integration | 3 |
CPSC:680 | Software Engineering Methodologies | 3 |
CPSC:689 | Advanced Topics in Computer Science | 1-3 |
Graduate course outside the CS department 1 | 3 |
- 1
For a graduate course outside the Department of Computer Science to be used towards the certificate, it must be on a topic related to Computational Data Science, and must be approved by the Department. At most three credits of Data Science Elective may be from outside Computer Science.