From an empty workstation to an automatically deployed, monitored, and reproducible application: Git, Jenkins, Docker, Kubernetes, Helm, Ansible, Terraform, and observability.
21 modules151 lessons53 open to everyone
With a final project
Supervised Learning: From Zero to a Professional Project
A complete, progressive path from the basic vocabulary to a model in production. Problem framing, data preparation, classification and regression algorithms, metrics and business costs, leak-proof pipelines, interpretability, deployment and monitoring — with hands-on labs throughout.
23 modules88 lessons11 open to everyone
Zero math formulas
Supervised Learning Explained to Kids: 100 AI Concepts in Simple Words
One hundred questions, one hundred one-page answers, without a single formula: what AI is, how a computer learns from an answer key, the algorithms, the neural networks, the large language models, the data and its biases, AI in real life, and the jobs of tomorrow. For kids — and for curious adults just getting started.
14 modules114 lessons23 open to everyone
With a final project
Deep Learning: From Intuition to Deployment
From neural networks to Transformers: tensors, MLPs, forward propagation, gradient and backpropagation, optimization, initialization, regularization, then CNNs, RNN/LSTM/GRU, attention, embeddings and generative models — through to MLOps deployment and ethics. Five PyTorch labs, a defensible final project, nine modern deep dives.
9 modules52 lessons10 open to everyone
Zero math formulas
Deep Learning Explained to Kids: Neurons, Images, Text and Much More
Not a single formula: how a neural network is built, how it learns by correcting its mistakes, how it looks at images, listens to sounds, reads language and even creates drawings. Every lesson fits on one page, with a simple diagram and a screen-free activity. For curious kids and beginner adults.
7 modules41 lessons11 open to everyone
Zero math formulas
Agentic AI Explained to Kids: Agents That Think, Act and Check Their Work
Not a single formula: discover how an AI agent goes further than a chatbot by looking, thinking, using tools and checking its work until the goal is reached. Memory, planning, agent teams, guardrails and sandboxes, all with everyday analogies, simple diagrams and screen-free activities. For curious kids and beginner adults.
5 modules22 lessons4 open to everyone
Hands on the code
Quick practical guide
The Claude Family: Code, Cowork and Design — The Practical Handbook
A hands-on developer handbook to the Claude family. Drive Claude Code from your terminal, set safe permissions, package Skills, wire hooks and MCP servers, delegate to subagents, collaborate in Cowork and prototype in Design — and move real projects fluidly across the three surfaces.
5 modules21 lessons4 open to everyone
Hands on the code
With a final project
Machine Learning for Data Diagnostics: From Raw Data to Local LLM Agents
Built to make you work, not listen: five-minute lessons, a quiz after each one, guided exercises on one dataset of 40 industrial machines. From pandas, SQL and feature engineering to regression, random forests, clustering and neural networks; then embeddings, RAG, local LLMs with Ollama and LangChain, text-to-SQL tools, LangGraph agents and a Streamlit diagnostic app. Free, offline, no API key.
15 modules209 lessons43 open to everyone
Hands on the code
With a final project
Elasticsearch, OpenSearch, Kibana, and Neo4j: The All-in-One Docker Lab
A Docker lab that starts with one command, end-to-end tested, to learn full-text search with Elasticsearch and OpenSearch, Kibana dashboards, and Neo4j graphs in Cypher — on the same dataset, with every query verified and an entire lesson devoted to troubleshooting.
7 modules42 lessons8 open to everyone
Hands on the code
Terraform in Practice: From First Local Resource to Multi-Cloud
Learning Terraform by doing: nine hands-on guided projects, from your first local file to a project managing GitHub, AWS, Azure and Google Cloud. S3 bucket, static site, Security Group, IAM user, GitHub repository as code, variables, state, modules and team workflow. Short theory backed by HashiCorp documentation, per-module quizzes, clean destroy by project.
7 modules26 lessons6 open to everyone
Hands on the code
With a final project
Monitoring and observability: Prometheus, Grafana, logs, metrics and alerts
Supervise a running application on your machine using Prometheus, Alertmanager, Grafana, Loki and Alloy in Docker Compose, around a fully instrumented API. Metrics, PromQL, dashboards, correlated logs, working alerts, and a final project. Every command followed by real output, a guided practice per module, and a tested GitHub kit.
