The day -1 of the workshop had sessions on basics of Python programming including data structures (lists, tuples, dictionaries, sets etc), control structures, iterations, creation of modules, introduction to Anaconda & Spyder, introduction to various packages for Data Science such as numpy, scipy, matplotlib, pandas, sklearn etc. 
The day-2 of the workshop covered basics of machine learning including supervised, unsupervised and reinforcement learning. Overview of various data sets available for experimentation, analyzing and & visualizing data, application of KNN, LDA/PCA, SVM, Bayes Classification etc., evaluating different techniques, quality bench marks for machine learning such as confusion matrix, f1-score, recall value etc, introduction to deep learning etc. The workshop was concluded with a Q/A session on Data Science and future directions. 
Workshop was very useful for the participants and it was highly appreciated by participants and the University administration.