From machine learning fundamentals to deep learning and NLP. scikit-learn, TensorFlow, Hugging Face — models trained and deployed on real projects.
Types of learning (supervised / unsupervised), advanced NumPy & Pandas.
scikit-learn: regression, classification, cross-validation, metrics.
Decision trees, Random Forest, SVM, KNN — theory and tuning.
Real project: house price prediction or customer churn detection.
Neural networks, layers, activation functions, loss functions.
CNNs for image recognition: MNIST, then a custom real dataset.
Tokenisation, embeddings, Transformer architecture (encoder/decoder).
Hugging Face: sentiment analysis, translation, text generation, basic RAG.
Guided project of your choice: chatbot, object detector, business predictor.
Streamlit / Gradio, FastAPI API, presentation and certificate.
Ready to master AI and machine learning?