• Venue : Goa University, Goa
• Date : June 4 to June 15, 2018

Course Contents:

• Mathematical foundation, basic statistical analysis and data visualization: Matrix Algebra, Probability and random processes, inferential statistics, optimization for data science and data visualization;

• Elements of machine learning: Supervised learning (methods: linear and logistic regression, K-NN, LDA, Tree based methods, SVMs, ANNs. Concepts: Bias-Variance tradeoff, regularization, dimensionality reduction), unsupervised learning (clustering and ARM); (iii) Advanced topics: Reinforcement Learning, Deep Learning, Topics in Big Data and Learning Theory.

Faculty :

• Balaraman Ravindran, IIT Madras

• Mitesh Khapra, IIT Madras

• Raghunathan Rengaswamy, IIT Madras

• Harish Guruprasad, IIT Madras

• Nandan Sudarsanam, IIT Madras

• Sahely Bhadra - IIT Palakkad

• Sourangshu Bhattachrya, IIT Kharagpur

• Anirban Dasgupta, IIT Gandhinagar

• Piyush Rai, IIT Kanpur

Prerequisites:

The course requires an understanding of algebra, calculus, and proficiency in programming.

Course coordinators:

• Nandan Sudarsanam, IIT Madrass

• Harish Guruprasad, IIT Madras

• Balaraman Ravindran, IIT Madras