I had an amazing opportunity to participate in the intensive 3-week summer course of Data Science and Machine Learning at the University of Warwick.The course was mix of theoretical knowledge and hands-on practice.

During the course we covered: Introduction to Data Science and Machine Learning; We explored successful analytic examples from companies like Walmart, Google, and Twitter and learned about various learning paradigms - Supervised, Unsupervised, and Reinforcement Learning. Probability and Statistics. Stochastic Bandits and Reinforcement Learning.Regression Techniques: linear regression, logistic regression, and techniques for predicting new data values, using least squares optimization and logistic models for both low and high-dimensional data.

Linear Algebra and Matrix Techniques: matrices to represent data relations, applying linear algebraic operations and matrix decompositions like Singular Value Decomposition (SVD) and Principal Components Analysis (PCA) to complex datasets, such as the Netflix Prize.

Classification Methods: decision trees, Naive Bayes, Support Vector Machines (SVM), and the Kernel Trick. We also utilized the Weka toolkit for practical implementation.

Clustering Approaches: hierarchical, k-means, and k-center clustering techniques, understanding their relative merits and applications.

On top of this, I enhanced my Python skills, especially in data manipulation, visualization, and analysis using powerful libraries like NumPy, SciPy, Pandas, and Seaborn. I’m incredibly grateful for the chance to be the part of this school.