Weekend Student Training Program on AI/ML at IIIT Hyderabad

Weekend Student Training Program on AI/ML at IIIT Hyderabad

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Weekend Student Training Program on AI/ML at IIIT Hyderabad

(source : ANI) ( Photo Credit : ani)

VMPL

New Delhi [India], August 28: IHub-Data is bringing out a six-month weekend training program on AI/ML for undergraduate students pursuing a career in science, commerce or business streams. The program would be ideal for highly motivated students, desirous to learn tools and techniques of data-driven decision-making processes. Classes would be conducted on all weekends at IIIT Hyderabad by resource persons from these domains.

Integration of Artificial Intelligence (AI) and Machine Learning (ML) into diverse academic disciplines underscores the importance of a short-term course for undergraduate students pursuing non-engineering educational programs. This course fosters critical thinking, encouraging students from all backgrounds to interrogate big data ethics, algorithmic biases, and real-world applications. By bridging theoretical knowledge with practical tools involving natural language processing or other applications using neural networks, this program will ensure that graduates enter their professional careers prepared for roles in analytics, product management, or policy-making, says Dr CK Raju, Head of Educational Programs at IHub-Data.

Key Highlights

Start Date: 28 September 2025

Classes: On all Sundays

Duration: 6 months

Coordinator: Ms. Faheema VV.

Email: faheema.vv@ihub-data.iiit.ac.in

Course Webpage:

ihub-data.ai

About IIIT Hyderabad

The International Institute of Information Technology, Hyderabad (IIITH) is a premier autonomous research university established in 1998. Known for its interdisciplinary research with real-world impact, the institute core strengths include Artificial Intelligence, Visual and Natural Language Technologies, Data Engineering, VLSI and Embedded Systems, Robotics, and more. IHub-Data is its national-level Data and AI Foundation, established in 2021 to drive translational research and innovation in AI and allied areas.

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