The Master of Technology (Online) programme in Artificial Intelligence will be offered by the Division of Electrical, Electronics, and Computer Sciences. The vision of the programme is to impart rigorous training in the foundations and deep technology of Artificial Intelligence to early-career professionals with 2-8 years of experience to upskill them to become technology and business leaders in information-driven enterprises. These learnings are coupled with a unique capstone project that applies the learnings to a hands-on project relevant to the industry. Faculty from the Division of EECS, the Department of CDS, and the RBCCPS will offer contemporary courses in AI through online lectures and tutorials and will provide mentorship on capstone projects.
- Core courses (14 credits): These are typically taken in the first and second semesters.
- Random Processes
- Linear Algebra
- Linear and Non-linear Optimization
- Machine Learning
- Sample Elective courses (at least 23 credits):
- Foundations of Robotics
- Digital Image Processing
- Reinforcement Learning
- Deep Learning for Computer Vision
- Speech Information Processing
- Data Analytics
- Machine Learning and Edge Computing
- Advanced Deep Learning
- Spectral Methods for Pattern Analysis
- Machine Learning in Neuroscience
Project (27 credits):This involves a summer plus 1 semester project as per the following plan: Summer (6 credits), Mid-term (9 credits), Final (12 credits). The student can register for project after successfully completing four core courses plus one elective. The student should have monthly one-hour meetings with the assigned faculty mentor. The faculty mentor will provide feedback on whether the project expectations are met. The faculty mentor will evaluate in all the three stages. An additional faculty member will evaluate in the mid-term and final stages.
Applications Open: 26 April 2021
Applications Ends: 08 May 2021
Intimation of Selection: 10 May 2021
- Minimum Eligibility: All sponsor-nominated candidates must meet these eligibility requirements:
- BE/BTech in CSE/ECE/EE
- At least 70% of marks or equivalent CGPA in all degrees, and
- Two years of industrial experience.
- Selection: Online written test. (This will evaluate the technical ability of the candidate to succeed in the coursework and may include topics such as mathematics, basic programming, problem-solving, etc. at the undergraduate level.)