The first is to go at it alone, and begin applying these skills to projects that interest you.
The step-by-step blueprint you've learned will give you a huge head-start. But strike while the iron is hot! Pick a topic, find a dataset, and start practicing.
For tools, we strongly recommend the Python stack, including the following libraries:
- NumPy for efficient numerical computations.
- Pandas for data management.
- Scikit-Learn for algorithms and model training.
- Seaborn for easy/common visualizations.
- Matplotlib to customize visualizations.
After you've mastered the core workflow, you can use the rest of this lesson as guideposts for continued study.
Our #1 tip for self-study is to skip the textbooks and jump into projects ASAP because it's much faster to learn in context, i.e. "learning by doing."
Plus, it will be easier to stay motivated and continue progressing.