📄️ Introduction to AI - Complete
Complete course on the foundations of artificial intelligence, its history and current applications. Duration: 5 hours, with applied projects, a 40-question exam and a verifiable certificate.
📄️ 1. What AI really is
Module 1 of the premium course Introduction to AI — Complete: an operational definition of AI, the AI / machine learning / deep learning hierarchy, what belongs to the field and what does not, and the essential vocabulary for the rest of the course.
📄️ 2. From rules to data
Module 2 of the premium course Introduction to AI — Complete: expert systems and their dead ends, the two AI winters, the statistical shift of the 1990s and the 2012 deep learning breakthrough.
📄️ 3. Narrow or general
Module 3 of the premium course Introduction to AI — Complete: why all production AI is narrow, what large models change and do not change, and how to discuss AGI without naivety or panic.
📄️ 4. How a machine learns
Module 4 of the premium course Introduction to AI — Complete: the complete mechanics of learning explained with no prerequisites — parameters, loss function, gradient descent, learning rate and convergence.
📄️ 5. The two typical failures
Module 5 of the premium course Introduction to AI — Complete: recognizing overfitting and underfitting, understanding the role of the three datasets, and knowing the standard remedies — regularization, early stopping, more data.
📄️ 6. The three regimes
Module 6 of the premium course Introduction to AI — Complete: the three learning regimes in depth, their data requirements, their real business use cases, and the hybrid regimes — semi-supervised and self-supervised.
📄️ 7. Evaluation metrics
Module 7 of the premium course Introduction to AI — Complete: why accuracy misleads on imbalanced classes, the confusion matrix, precision and recall, the threshold trade-off, and regression metrics.
📄️ 8. The project life cycle
Module 8 of the premium course Introduction to AI — Complete: the seven stages of a real project — framing, data, baseline, iteration, evaluation, deployment, monitoring — and where the effort actually goes.
📄️ 9. Successes and failures
Module 9 of the premium course Introduction to AI — Complete: what successful deployments have in common, the anatomy of the most instructive public failures, and the analysis grid to apply to any project.
📄️ 10. Limits and paths forward
Module 10 of the premium course Introduction to AI — Complete: the structural limits of current systems — data, robustness, explainability, cost, reasoning — and the research directions trying to address them.
📄️ 11. Recap and exam
Synthesis of the ten modules of the premium course Introduction to AI — Complete, then the certification exam: 40 corrected questions, 70% passing threshold, verifiable online certificate.