Course Structure
- All courses, including lectures, tutorials and lab sessions, if any, will be held online, using a video conferencing service. All course materials and video recordings of lectures and lab sessions will be available online for students of the course.
- Course credits are given as N:M, where N is the number of lecture contact hours per week with the faculty, and M is the expected hours of hands-on activity that is either led by an instructor or done independently by the student. E.g., a 3:1 course may have 3 hours of lectures each week along with 1 hour of tutorials or hands-on assignments.
- Core courses will be offered every year, with each course offered in one of the two Aug or Jan terms.
- Elective courses will be offered selectively each year, and will be announced at the start of each academic year. Not all electives will be offered in all years, and the faculty offering them may change.
- The Capstone project may be taken in the second or later years, after completing the core-course requirements. It lasts for two terms, with 12 project credits in the first and 20 project credits in the second. It has to be completed within a 12-month period, e.g., Aug+Jan, Jan+Aug or Summer+Aug terms.
- In addition to courses offered in the DSBA program, students may also take external elective courses from a list of pre-approved courses offered by other Online M.Tech. programs. This list will be updated once the courses for other programs are finalized.
Tentative Course List
The following courses are tentatively expected to be offered in the academic year 2021-2022. Pre-requisite courses are mandatory to be taken and completed in a previous term in order to take a course. Some pre-requisite courses may be listed as optional. Students not satisfying optional pre-requisites need prior permission from the instructor.
| Code | Title | Core/Elective | Credits | Term | Instructor | Pre-requisites |
|---|---|---|---|---|---|---|
| DA202-O | Introduction to Data Science | Core | 3:1 | Aug | SG/DS | None |
| DA231-O | Data Engineering at Scale | Core | 3:1 | Aug | YS | None |
| DA203-O | Introduction to Computing for AI/ML | Core | 3:1 | Jan | SG | DA202-O |
| DA224-O | Practical Machine Learning | Elective | 3:1 | Jan | DS | DA202-O |
| DA212-O | Hardware-aware AI & Machine Learning | Elective | 3:1 | Summer | SG | DA202-O |
| DA225-O | Deep Learning | Elective | 3:1 | Summer | DS | DA202-O |
| DA199 | Capstone Project | Core | 0:12, 0:20 | Aug/ Jan/ Summer | Faculty Mentor | Core courses completed |
| DA201 | Financial Analytics | Elective | 3:1 | TBD | SJ | None |
| DA203 | Data Mining | Elective | 3:1 | TBD | PR | DA102. DB131 optional. |
| DA204 | Deep Learning and Computer Vision | Elective | 3:1 | TBD | VB/AC | TBD |
| DA223-O | Applied Operations Research | Elective | 3:1 | Jan 2022 | MMR | None |
Course Description
Please see the IKEN Website for course details and schedule
Pre-approved External Elective Courses
Courses offered by other Online M.Tech. programs may be taken to satisfy the elective course credit requirements for the DSBA program, with prior approval from the PCC.