🧑🎓 Roadmap
🚀 Data Science & Machine Learning ROADMAP for aspiring Data Scientists and ML Enthusiasts! 🌟
1️⃣ Mathematics & Statistics
✨ From descriptive statistics to calculus, these resources will provide a solid foundation in the core principles that drive data science. 🔢
- 1.1. Descriptive Statistics
- 1.2. Probability
- 1.3. Inferential Statistics
- 1.4. Linear Algebra
- 1.5. Calculus
2️⃣ Python | R for Data Science
🐍 Explore the coding aspect with Python and R cheat sheets for brushing up on your programming skills. 📈
3️⃣ SQL | Databases for Data Science
🔍 In the world of data handling, SQL is the key. These guides will assist you in navigating databases like a pro. 🗃️
4️⃣ Exploratory Data Analysis (EDA) & Data Visualization
📊 Transform data into insights with top-notch visualization tools and techniques. 🎨
5️⃣ Machine Learning
🤖 Discover the fascinating world of Machine Learning with comprehensive guides and resources. 🧑🎓
6️⃣ Deep Learning
🌌 Learn to dive deep into Deep Learning with TensorFlow, Keras, and more! 🧠
7️⃣ Generative AI
🤯 Discover the cutting-edge realm of Generative AI, including a special guide to ChatGPT! 💬
8️⃣ MLOps | LLM Ops
🛠️ Learn the best practices for operationalizing ML models and large language models. 🔄
9️⃣ Papers for ML & Data Science study guides
📜 Dive into seminal papers that every ML enthusiast should read. 🔍
Study guides
Data retrieval with SQL | Data manipulation with R | Data manipulation with Python |
Visualization with R | Visualization with Python | Engineering tips |
Conversion guides between R and Python
Data manipulation | Visualization |
Super study guide
All the above gathered in one place |
🧭 This ROADMAP is not just a learning path; it's my compass that provides links to cheat sheets, tutorials, and references that have been meticulously selected to contribute to my personal learning journey. 🎓