Mathematics for Machine Learning
Linear algebra, multivariable calculus, PCA, eigenvectors.
Linear algebra, multivariable calculus, PCA, eigenvectors.
Data wrangling, visualization, inference, regression, ML with R.
Python foundations, data structures, APIs, SQLite.
Linear algebra, probability, optimization for AI.
Greedy, divide and conquer, dynamic programming.
Core SQL queries, joins, subqueries, analytics.
Search, knowledge, neural networks, reinforcement learning.
Break the Whistle — non-fiction on AI for fair sports refereeing (in progress).
Led the sports council and organized tournaments and trials.
Ran AI and ML workshops and student showcases.
Led waste segregation and plantation drives on campus.
Mentored peers in public speaking and idea development.
