Week 1. Core programming in Python. Libraries overview. Numpy.
Week 2. Data Collection and Management. Data sources. Web scraping. Databases. SQL
Week 3. Data preprocessing. Outliers. Data cleaning. Data imputation. Encoding
Week 4. Statistics. Descriptive analytics. Pandas. Pandas-profiling. Regression. Data visualisation with Matplotlib and Seaborn.
Week 5. Streamlit. Business intelligence tools. Tableau. Probability theory.
Week 6. Predictive analytics.
Week 7. Machine learning. Supervised learning. Features selection. Hyperparameter tuning.
Week 8. Unsupervised learning AutoML. Deep learning. NLP