AI developer road map
⭐ AI Engineer Complete Concept List (Full Roadmap) (Beginner → Advanced → Expert) 🟩 1. Foundations of AI Engineering ✔️ Mathematics (Practical Level) Linear algebra (vectors, matrices) Probability & statistics Optimization basics (gradient descent) ✔️ Programming Python NumPy, Pandas Matplotlib ✔️ Computer Science Basics Data structures & algorithms APIs (REST, gRPC) JSON, YAML 🟦 2. Machine Learning (ML) Fundamentals Supervised vs unsupervised learning Regression, classification Feature engineering Train-test split Overfitting/underfitting Cross validation Metrics: Accuracy, F1, Precision, Recall ML frameworks: Scikit-learn, XGBoost 🟪 3. Deep Learning ✔️ Core Concepts Neural networks Activation functions Loss functions Optimizers Backpropagation ✔️ Libraries TensorFlow PyTorch ✔️ Architectures CNN (vision) RNN, LSTM (sequence) Transformers (modern AI) 🟧 4. Natural Language Processing (NLP) Tokenization Word embeddi...