The MS (DS) program has been designed to give students the option to be part of a data science endeavour that begins with the identification of business processes, determination of data provenance and data ownership, understanding the ecosystem of the business decisions, skill sets and tools that shape the data, making data amenable to analytics, identifying sub-problems, recognizing the technology matrix required for problem resolution, creating incrementally-complex data-driven models and then maintaining them to ultimately leverage them for business growth.
The amount of data is growing so rapidly and their significance in the emerging societal set ups such as the pervasive Internet of Things. The way one imagines data is going to change in the coming years. Both Big Data Analytics and pervasive computing hinge on the principle axis of data analytics. MS (DS) program is going to be relevant in terms of job creation and artisanal smart business generation. Graduates from this program would definitely avail the early-bird advantage.
Data science experts are needed in virtually every job sector—not just in technology. In fact, the five biggest tech companies—Google, Amazon, Apple, Microsoft, and Facebook. However—in order to break into these high-paying, in-demand roles—an advanced education is generally required. Here are some of the leading data science careers you can break into with anf advanced degree. Data Scientist, Machine Learning Scientist, Application Architect, Enterprise Architect, Data Architect, Business Intelligence, Statistician, Free lancing Data scientist, Marketing Analyst, health data Analyst, and of course the path to Ph.D. degree
Code |
Course Title |
Credit Hours |
Labs |
Total |
COMP-### |
Applied Programming |
NC |
|
|
COMP-### |
Tools and Techniques for Data Science |
2 |
1 |
3 |
COMP-### |
Statistical and Mathematical Methods for Data Analysis |
3 |
|
3 |
COMP-### |
Elective-1 |
3 |
|
3 |
Code |
Course Title |
Credit Hours |
Labs |
Total |
COMP-### |
Machine Learning for Data Science |
3 |
|
3 |
COMP-### |
Specialized Core I |
3 |
|
3 |
COMP-### |
Specialized Core II |
3 |
|
3 |
SS-821 |
Research Methodology |
NC |
|
0 |
Code |
Course Title |
Credit Hours |
Labs |
Total |
COMP-899 |
MS Thesis |
6 |
|
6 |
COMP-### |
Elective-II |
3 |
|
3 |
Code |
Course Title |
Credit Hours |
Labs |
|
COMP-### |
Elective-III |
3 |
|
3 |
Code |
Course Title |
COMP-830 |
Advanced Big Data Analytics |
COMP-828 |
Deep Learning |
COMP-831 |
Natural Language Processing |