Applications are now being accepted for the online course on the Fundamentals of Contemporary Machine Learning for undergraduate engineering students, which is offered by iHub-Data at the IIIT Hyderabad. In August 2023, the 50-week course will get underway. The course is specifically intended for second- or third-year undergraduate engineering students enrolled in India’s four-year B.Tech programme.
Introduction to ML, Revisiting Nearest Neighbor Classification, Decision Trees, Linear Classifier, SVM, Perceptrons and gradient descent, Loss functions and gradient descent, Regression, Clustering, Probabilistic ML models, and Deep Learning Architectures are some of the topics covered. The last date to apply is June 30. Participants need to pay a registration fee of Rs. 500/-.
Students pursuing a 4-year UG program in engineering/technology and in their second or third year are eligible. Students should be studying in an AICTE recognised institution or a technical institution of repute in India. All program courses are taught in English. Hence, a minimum proficiency in English language is expected to participate in the program.
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Students who wish to develop their abilities to recognise and address problems in the real world utilizing the most recent machine learning tools and methodologies are the program’s target audience. The live and interactive seminars would be led by a group that includes CK Raju and Monalisa Patra from iHub-Data and teachers from IIIT Hyderabad.
The advantages of an in-person programme and the flexibility of online study are uniquely combined in this programme. Participants, with recorded classes, have the freedom to learn at their own speed. They can clarify their doubts and questions through live discussions with the instructors and mentors.
To get the most out of the programme, participants must dedicate at least two hours every week. This will also apply to the time spent learning and completing homework as well as the online sessions. Participants would be continually assessed as part of a comprehensive approach. Exams, assignments, group projects, and attendance would all be utilized to gauge performance.
