Learn about the most common mistakes that emerging data scientists make while using Python, as well as how to avoid these missteps in your own work.
- [Lavanya] If you're a master in Python or you're still learning, chances are you're making simple mistakes that cost you time and productivity. My name is Lavanya Vijayan. I'm a coding instructor and an advocate for STEM education. In this course, I'll show you the most common mistakes data scientists make while using Python and I'll help you learn how to avoid these mistakes. I'll address mistakes in coding practices, in structuring code, and handling data, as well as in machine learning. By the end of this course, you'll be well-prepared with a set of tools, strategies, and best practices to improve your skills and effectiveness in working with data in Python. So let's get started.
Skill Level Intermediate
1. Avoid Mistakes in Coding Practices
2. Avoid Mistakes in Structuring Code
3. Avoid Mistakes in Handling Data
4. Avoid Mistakes in Machine Learning
Using redundant features1m 45s
Get started with Python1m 7s
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