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My Roadmap to Becoming an AI/ML Engineer.
Python & NumPy ✅ — Master the fundamentals and practice numerical computing.
Data Foundations — Learn Pandas, SQL, PostgreSQL, and Git. Build a data analysis project.
Math & Classical ML — Study statistics, linear algebra, scikit-learn, and XGBoost. Build your first ML model.
Deep Learning & Transformers — Learn PyTorch and Hugging Face. Build a neural network and a transformer-based application.
LLM Engineering & AI Agents — Learn RAG, vector databases, LoRA/QLoRA, and AI agents. Build a document-based AI assistant.
Production AI — Learn FastAPI, Docker, CI/CD, MLflow, and AWS. Deploy your AI application.
The goal isn't just to finish tutorials. It's to build projects, solve real problems, and create a portfolio.
One step at a time. One project at a time.
Bootcamp: https://chat.whatsapp.com/LS93hzXRl0ZJqbARzOOXNE
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