ACM India – RBCDSAI Summer School on DS/AI/ML (For Women Only) Hosted by PSG College of Technology, Coimbatore


11th – 22nd July 2022

Name of the school: ACM India – RBCDSAI Summer School on DS/AI/ML (for women only)

Host Institution’s Name and Address: PSG College of Technology, Coimbatore

Industry sponsor: TBD

Dates: 11th July 2022 - 22nd July 2022

Academic Coordinator(s)

Local Coordinator(s)

Description of school:
The shift towards digitalization during the pandemic has changed the operational model of businesses globally. Artificial intelligence (AI), Machine Learning (ML), and Data Science (DS) are emerging fields that will help businesses to make this shift post pandemic. Further, the demand for trained human power in these fields will increase in the coming years. The knowledge in these fields is a key stepping stop towards making a successful career. The aim of this school is to expose and motivate young female students and researchers to the recent advances in the field of Artificial intelligence, machine learning, and data science over a period of two weeks. The school aims to provide a platform to the in-depth understanding of the various aspects/tools in the AI/ML/DS.

List of subtopics:

  • Introduction to AI/ML/DS; Mathematical foundation of AI/ML/DS
  • Supervised Learning Techniques: Regression and classification techniques
  • Support Vector Machine and Tree-based methods
  • Unsupervised learning methods such as clustering and dimensionality reduction
  • Introduction to Deep Learning techniques
  • Industrial Case studies

List of speakers (with affiliation): The current set of confirmed speakers is the following.

  • Nandan Sudarsanam (RBCDSAI)
  • Usha Mohan (RBCDSAI)
  • Ramkrishna Pasumarthy (RBCDSAI)
  • Resmi Suresh (IIT Guwahati)
  • Nirav Bhatt (RBCDSAI)
  • Divya Padmanabhan (IIT Goa)
  • Shweta Jain (IIT Ropar)
  • Arun Rajkumar (RBCDSAI)
  • Gokul Krishnan (RBCDSAI)
  • Preksha Nema (Google)
  • Ananya Sai (IIT Madras)
  • Niyati Chhaya (Adobe Research)
  • Lipika Dey (TCS Research)

Background / prior courses recommended:
The following background is expected from the participants. The links curated contain material that can be used to revise/pick up the necessary material.

  • Exposure to applied probability, statistics and linear algebra, and basic optimization

Any specific software (Matlab, Python etc) to be used:

  • Knowledge of programming is required, preferably, in Python

Detailed schedule: