Artificial Intelligence & Machine Learning Crash Course

Demystifying AI, Deep Learning, and Predictive Models

Artificial Intelligence is reshaping every industry on the planet. This accessible, math-intuitive course bridges the gap between software engineering and machine learning, guiding you step-by-step through real ML pipelines.

What you will master:

• Machine Learning Concepts: Training sets, validation, testing, overfitting, underfitting, bias-variance tradeoff.
• Supervised Learning: Linear Regression, Logistic Regression, Decision Trees, Random Forests.
• Unsupervised Learning: K-Means Clustering, Principal Component Analysis (PCA).
• Model Evaluation: Confusion Matrix, Precision, Recall, F1-Score, ROC-AUC.
• Deep Learning Intro: Perceptrons, activation functions (ReLU, Sigmoid), backpropagation with PyTorch.
• Computer Vision & NLP: Convolutional neural networks (CNN) overview, word embeddings, transformer intuition.