Fundamentals of the q programming language -- Dictionaries and tables : the q fundamentals -- Functions -- Editors and other tools -- Debugging q code -- Splayed and partitioned tables -- Joins -- Parallelisation -- Data cleaning and filtering -- Parse trees -- A few use cases -- Basic overview of statistics -- Linear regression -- Time series econometrics -- Fourier transform -- Eigensystem and PCA -- Outlier detection -- Simulating asset prices -- Basic principles of machine learning -- Linear regression with regularisation -- Nearest neighbours -- Neural networks -- AdaBoost with stumps -- Trees -- Forests -- Unsupervised machine learning : the Apriori algorithm -- Processing information -- Towards AI : Monte Carlo tree search -- Econophysics : the agent-based computational models -- Epilogue