AI & Machine Learning Foundations
Beginner to Intermediate • Estimated: 10 weeks (6-8 hrs/week)
Curriculum Overview
A structured, beginner-friendly roadmap to understanding modern artificial intelligence, machine learning algorithms, deep neural architectures, and practical prompt engineering.
Core Competencies Built:
Who This Is For:
Aspiring AI practitioners, developers shifting to machine learning, and professionals seeking practical fluency in modern AI systems.
Prerequisites:
Basic algebra and high school mathematics. Prior programming experience is helpful but not strictly required.
Week-by-Week Learning Roadmap
Mathematics & Python Essentials
Vectors, matrices, gradient descent concepts, and NumPy vectorization.
Classical Machine Learning
Supervised vs unsupervised learning, decision trees, regressions, and model evaluation.
Deep Learning & Neural Networks
Perceptrons, backpropagation, convolutional networks, and PyTorch tensors.
Natural Language Processing & Transformers
Tokenization, embeddings, self-attention mechanisms, and Hugging Face pipelines.
Applied AI & Capstone Project
Fine-tuning LLMs, retrieval-augmented generation (RAG), and deployment.
Recommended Courses for This Path
Deep Learning Specialization
Coursera / DeepLearning.AI • Intermediate
Become a machine learning expert. Master deep learning, neural networks, CNNs, Sequence Models, and practical ML project structuring.