What you will learn from this course?

Topic 1. Exploratory data analysis with Pandas

Topic 2. Visual data analysis in Python
– Overview of Seaborn, Matplotlib and Plotly libraries

Topic 3. Classification, Decision Trees and k Nearest Neighbors

Topic 4. Linear Classification and Regression.
– Ordinary Least Squares
– Logistic Regression
– Regularization
– Pros and Cons
– Validation and learning curves

Topic 5. Ensembles of algorithms and random forest.
– Bagging
– Random Forest
– Feature importance

Topic 6. Feature engineering and feature selection

Topic 7. Unsupervised learning

Topic 8. Vowpal Wabbit: Learning with Gigabytes of Data

Topic 9. Time series analysis in Python.
– Basics
– Predicting future with Facebook Prophet

Topic 10. Gradient boosting

Certification : No
Time to complete : 2 weeks
Cost : Free
Course Level : Intermediate
Language : English