Initial Course of Python Data Analysis in MAI during first semester master's degree program
- Simple Pandas Task - Notebook with some EDA for Iris dataset and JavaCourse StreamAPI task;
- First lesson - Basics;
- Type lesson - Basic structures (strings, lists, tuples e.t.c) and type-defined functions (.split(), .append() e.t.c);
- Classes lesson - Classes overview with binary tree implementation task;
- Numpy lesson - Numpy overview with some many numpy array manipulation tasks and function aproximation task;
- I/O lesson - Loading data from files and URL-s;
- Numpy colloquium - Huge numpy exercise on rotating color layers of the picture;
- Pandas lesson - Pandas basics;
- Matplotlib lesson - Matplotlib & Seaborn overview with two main tasks on huge 2D-plots visualization and EDA with pandas and seaborn;
- EDA lesson - EDA (Exploratory data analysis) examples;
- EDA colloquium - EDA exercise on Titanic disaster and deaths analysis;
- ML basics - Machine Learning problems statements, PCA, Random Forest with Decision Tree forest Classification/Clusterization task in the end (comparison of own implementation with sklearn).