Introduction to pandas, numpy, scipy and jupyter, extended tricks, jupyter magic commands and technics

Data manipulations

Data visualization

Sklearn. Classifiers, regressors, pre and post processors, cross validation, pipelines. Custom classifier/preprocessor, postprocessor

Python, jupyter environment configuration. External libraries: xgboost, tensorflow, pytorch

Textual features. Nltk. Sound data analysis

Image data. Opencv. Geodata

Time series data

Time series and linkage to supplementary data sources. Graph data

Python and jupyter integrations. Google docs, chatbots, interface prototyping, data annotation, scrapping

Heavy dataset processing with python instruments

Data pipeline versioning

Automl, hyperparameter optimization, etc

Finals

Pet project demonstration