Artificial Intelligence (AI), Machine Learning (ML), and Deep Learning (DL) are the buzz words in today’s world, be it for working professionals, academicians or students. These fields of computational science, have made a spectacular impact in divergent areas, such as Advertising, Asset Management, Automobile, Aviation, Defense, Education, Energy, EPC, Finance, Healthcare, Human Resources & Recruitment, Manufacturing, Transportation, and Space.
IIT Bombay brings to the academia, industry, and individuals an introductory course on ML and DL. The objective of the course is to provide a broad overview of the area. The emphasis is on providing insight and feels for each technique, rather than the theory (there is hardly any theory in the course). A crucial part of this course is the practicals, i.e., the hands-on sessions.
About half the course time is spent on the hands-on sessions. The hands-on sessions show how to program and implement various machine and deep learning techniques in different real-world applications.
- Overview of Machine learning and Deep learning
- Data preparation and visualization
- Regression ‐ Linear and Nonlinear
- Classification and Clustering Techniques
- Introduction to Neural Networks
- Back propagation and Gradient Descent
- Training, Testing, Over-fitting, and Under-fitting
- Introduction to Deep Learning
- Recurrent Neural Networks (RNN)
About 50% of the course is for the hands-on sessions. The hands-on sessions are based on popular software libraries in Python / Matlab. Data generation and live demonstrations of key techniques are based on the Gas turbine, boiler, hybrid two-tank, and DC Motor. Problems addressed include both steady-state and dynamic modeling, and fault detection and fault classification of the systems.
Who can Attend?
Faculty & Students from any branch of Engineering or Science, Researchers, and Industrial Practitioners can attend and benefit from this course. Familiarity with college-level mathematics is desirable.
To register online, click here.
The last date to apply is September 27, 2019.
Phone Number: 022 2572 2545