Curriculum for MS in Data Science and Analytics
Total credit hours of the program in MS in Data Science & Analytics are 40 and the credit distribution is as described below:
A. Core Courses 28C
B. Elective Courses 12C
----------------------------
40C
A. Core Courses (28C)
Students must take all 8 courses listed below:
|
Credit Hours
|
Course Number & Title
|
|---|---|
|
3
|
DSA5001: Statistical & Mathematical Methods
|
|
3
|
DSA5002: Programming for Data Science
|
|
3
|
DSA5003: Database Management Systems
|
|
3
|
DSA5004: Regression Analysis
|
|
3
|
DSA5005: Multivariate Statistical Analysis
|
|
3
|
DSA5006: Machine Learning
|
|
3
|
DSA5007: Big Data & Cloud Computing
|
|
7
|
DSA5099: Research Project
|
|
28
|
<= Total
|
B. Elective Courses (4 courses 12C)
Students must choose any 4 courses from the following list of courses.
|
Credit Hours
|
Course Number & Title
|
|---|---|
|
3
|
DSA5011: AI & Deep Learning
|
|
3
|
DSA5021: Time Series Analysis & Forecasting
|
|
3
|
DSA5041: Applied Econometrics
|
|
3
|
DSA5043: Business Process Analytics
|
|
3
|
DSA5045: Machine Learning for Finance
|
|
3
|
DSA5047: Data Analytics for Finance
|
|
3
|
DSA5061: Environmental Data Analysis and Climate Change
|
|
3
|
DSA5063: Bioinformatics
|
|
3
|
DSA5065: Biostatistics & Epidemiology
|
|
3
|
DSA5071: Generalized Linear Models
|
|
3
|
DSA5073: Categorical Data Analysis
|
|
3
|
DSA5075: Design of Experiment
|
|
3
|
DSA5077: Actuarial Data Analysis
|
|
12
|
<= Total
|
Course Flowchart for MS in Data Science & Analytics (MS in DSA)
|
Semester |
Courses |
Pre-req |
|
Semester 1 |
DSA5001 – Statistical & Mathematical Methods |
None |
|
DSA5002 – Programming for Data Science |
None |
|
|
DSA5003 – Database Management Systems |
None |
|
|
DSA5004 – Regression Analysis |
None |
|
|
Semester 2 |
DSA5005 – Multivariate Statistical Analysis |
DSA5001, DSA5002 |
|
DSA5006 – Machine Learning |
DSA5001, DSA5002 |
|
|
DSA5007 – Big Data & Cloud Computing |
DSA5001, DSA5003 |
|
|
Elective I DSA5011 – AI & Deep Learning |
DSA5002, DSA5004 |
|
|
Semester 3 |
Any TWO courses from the following (Elective II & Elective III) DSA5021 – Time Series Analysis DSA5061 – Environmental Data Analysis & Climate Change DSA5041 – Applied Econometrics DSA5063 – Bioinformatics DSA5065-Biostatistics and Epidemiology |
DSA5001, DSA5002 DSA5001, DSA5002 |
|
DSA5002, DSA5003 DSA5002, DSA5003 |
||
|
DSA5099A –Research Project-Part I |
DSA5002, DSA5006 |
|
|
Semester 4 |
Any ONE course from the following (Elective IV) DSA5043 – Business Process Analytics DSA5045- Machine Learning for Finance DSA5047-Data Analytics for Finance |
|
|
DSA5002, DSA5006 DSA5002, DSA5006 |
||
|
DSA5099B – Research Project-Part II |
DSA5099A |
- DSA5099A (3 Credits) and DSA5099B (4 Credits) constitute the Research Project Course DSA5099 (7 credits).
Description of Courses of Master of Science in Data Science & Analytics
List of Faculty members:
Ahmed Wasif Reza, PhD; Professor; AI & Deep Learning
Sohel Rana, PhD; Professor; Multivariate Statistical Analysis
Pintu Chandra Shill, PhD; Professor; Adjunct, Programming for Data Science, AI & Deep Learning
Syed Akhter Hossain, PhD; Professor, Adjunct, Database Systems, Big Data & Cloud Computing
Zakir Hossain, PhD; Professor, Adjunct, Statistical Methods, Probability Theory
Rezaul Karim, PhD; Professor, Adjunct, Machine Learning & Big Data, Multivariate Statistical Analysis
Anamul Haque Sajib, PhD; Professor, Adjunct, Applied Econometrics, Regression Analysis, Bioinformatics
Mohammad Nazmol Hasan, PhD; Professor, Adjunct, Bioinformatics
Md. Nayem Dewan, Adjunct, Machine Learning for Finance
Mostofa Kamal Rasel, PhD; Assistant Professor; Database System
Muntasir Chaudhury, PhD; Assistant Professor; Applied Econometrics
M. Rifat A. Rashid, PhD; Assistant Professor; Programming for Data Science
