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Strengths
- Completely free, including courses and GPU resources
- Each course comes with a practical notebook
- After completing the course, you can participate in the Kaggle competition
- Courses are short (4-8 hours) and get started quickly
- Free GPU credit (30 hours per week)
Best for
- Quickly learn specific AI/ML techniques
- Improve skills through competitive practice
- Learn data analysis and visualization
- Build an AI portfolio
- Learn about machine learning best practices
Recommended learning path
Kaggle Learn’s courses are short and practical, suitable for quickly learning specific skills.
Scenario
Getting Started with AI/ML
Prompt example
Recommended learning sequence (all free): Basic skills: 1. Python (5 hours) – Basics of Programming 2. Pandas (4 hours) – Data processing 3. Data Visualization (4 hours) – Data Visualization Machine learning: 4. Intro to Machine Learning (3 hours) - Introduction to ML 5. Intermediate Machine Learning (4 hours) - Advanced ML 6. Feature Engineering (5 hours) - Feature Engineering Deep learning: 7. Intro to Deep Learning (6 hours) - Introduction to deep learning 8. Computer Vision (4 hours) – Computer Vision 9. NLP (3 hours) - Natural Language Processing
Output / what to expect
The trail takes approximately 40 hours to complete,
Each course has a matching practical notebook.
After completing the course, you can participate in Kaggle competitions.
Tips
Completion of each course results in a certificate that can be added to LinkedIn and resumes.
Scenario
Participate in Kaggle competitions
Prompt example
Steps to get started with Kaggle competitions: 1. Start with the "Getting Started" contest - Titanic (classic classification problem) - House Prices (regression problem) - Digit Recognizer (image classification) 2. View Notebooks to learn other people’s solutions - Click on the "Code" tab - Sort by number of votes - Learn the ideas of high score scheme 3. Submit your own predictions - Fork a basic Notebook - Modify and submit - View ranking
Output / what to expect
Through competition practice,
Quickly improve your ML skills,
Build a showcaseable AI portfolio.
Tips
High Scores in Competitions Notebooks are great materials for learning best practices and are more practical than tutorials.