1. Analysis of text using frequencies
2. Basic text analysis demo, co-occurrence analysis
3. Co-occurrence analysis (cont'd), visualizing high-dimensional data with PCA
4. PCA (cont'd), manifold learning
5. Manifold learning, clustering
6. Clustering (cont'd), k-means, GMMs
7. Clustering (cont'd) - interpreting GMMs, automatically selecting the number of clusters
8. Clustering on images
9. Intro to neural nets and deep learning
10. Image analysis with convolutional neural nets
11. Time series analysis with recurrent neural nets