My personal (public) project to share tools and tips about Data Science and Python

1. Critical Thinking (like every scientist)
2. Python, R, Julia (at least intermediate level), some C or C++
3. Statistics
4. Linear Algebra
5. Differential Equations
6. Creativity
7. Good Learning Techniques
8. Machine Learning
9. Deep Learning
10. Big Data Analysis (Spark, Map-Reduce principle, Ray)
11. ETL Pipeline + DataSet generation
12. ...one or two topic to specialize your skills (i.e. Autonomous Driving, Reinforcement Learning, Computer Vision, Finance)

• Simple Reinforcement Learning (or other online learning system)
  • Q-Table
  • Deep Q-Learning (Experience Replay)
• GUI basics (QT, ImGUI, ...)
• Physical Simulations
• BioInformatics
• Effective Data Visualizations (Seaborn, DataViz, ...)
• One simple and effective tool to improve Computer Vision accuracy (No Flatten Information etc...) like this
• Explainable AI
• Edge AI (TinyML, Raspberry, ...)
• Transformers (NLP and Text-to-Image)
  • Visual
  • Stable Diffusion
  • Mistral
• Business Process Automation (PowerBI, Zapier, etc...)
• RAG (Retrieval-Augmented Generation)

• Finance
  • Stock Prediction
  • Risk Analysis
  • Portfolio Management
• Physics
  • New Materials
  • Simulations