Fundamentals
- Syntax, variables, and data types
- Control flow and functions
Intermediate
- Object-oriented programming
- Error handling and debugging
Advanced
- Design principles
- Performance and best practices
Foundations
- Data science workflow
- Python for data analysis
Exploration
- Data cleaning & preprocessing
- Exploratory Data Analysis (EDA)
Applied
- Real-world datasets
- Practical notebooks
Core Concepts
- Supervised and unsupervised learning
- Model evaluation basics
Techniques
- Regression and classification
- Clustering and dimensionality reduction
Practice
- Hands-on notebooks
- Applied ML workflows
Python
- Core Python interview questions
- Advanced problem-solving
Design & Concepts
- Architecture and design questions
- Best practices and pitfalls
Preparation
- Quizzes and exercises
- Revision-focused material
Long-Form Writing
- Python learning and growth
- Engineering mindset articles
Platforms
- Medium publications
- LinkedIn educational posts
Featured
- Curated external resources
- Recommended reading