Learn Python programming from scratch with this modern course that integrates AI tools to accelerate your learning. Whether you’re a scientist, engineer, or just curious about coding, this course provides a solid foundation. We cover everything from basic syntax to scientific computing with NumPy and Matplotlib.
Course Materials
Download Links:
– Jupyter Notebook: python_basics.ipynb
– PDF Version: python_basics.pdf
– Virtual Environment File: lab_python_course_env.yml
– Conda Cheat Sheet: conda-cheatsheet.pdf
Course Overview
Core Topics:
1. Basics & Installation
– Setting up Python environment
– Installing JupyterLab & Anaconda
– Understanding AI tools integration
2. Programming Fundamentals
– Variables and data types
– Conditional statements
– Functions and scope
– Loops and iteration
3. Development Environment
– Keyboard shortcuts
– Virtual environments
– Best practices
4. Scientific Computing
– NumPy basics
– Matplotlib visualization
– Practical applications
Modern Learning Approach
AI Tool Integration:
– ChatGPT for code explanation
– Claude for problem-solving
– Anaconda Assistant for debugging
– Focus on understanding, not just copying
Practical Tips:
– Start with small, manageable code cells
– Work incrementally
– Use AI tools to accelerate learning
– Focus on understanding core concepts
Common Pitfalls and Solutions
Beginner Challenges:
– Understanding error messages
– Thinking like a programmer
– Managing virtual environments
– Debugging effectively
Best Practices:
– Keep code cells small and focused
– Test code frequently
– Use meaningful variable names
– Document your code properly
Next Steps
To get the most out of this course:
1. Download the course materials
2. Follow along with the video
3. Practice with the exercises
4. Use AI tools for support, not replacement
5. Join the community for additional help
Ready to dive deeper? Check out our advanced courses at Training Scientists for more specialized content in scientific computing and data analysis.