Including examples:
- Design and evaluate (quasi) experiments for social scientists: RCT, RDD, IV, Regression, OVB, Network Effects
- High dimensional Data visualization, linear and non-linear clustering and classification, Gaussian Mixture EM
- Neural network and deep learning: feedforward, recurrent, convolutional networks. Natural Language Processing with reinforcement learning.
- Social network analysis with graph centrality, spectral clustering and evolution.
- Climate data time series analysis, (trend, seasonality, stationary) and stats modeling with ARMA models, Gaussian process and spatial prediction.