Learning Roadmaps & Courses.
Each roadmap is a course: an ordered list of lessons where every example is a small program shown with its real output. Pick a career roadmap to go end to end, or a topic roadmap to go deep on one tool.
Career roadmaps
Ordered courses across several topics
AI Engineer Roadmap
Python, ML, LLMs, embeddings, RAG, agents, MCP and deployment.
Cloud Engineer Roadmap
AWS, Azure, GCP, networking, IaC and cost.
Data Engineer Roadmap
Python, Spark, Airflow, Kafka, dbt and Snowflake.
Data Engineering Tools Roadmap
Spark, Airflow, Kafka, dbt, Snowflake and Databricks.
Database Roadmap
MySQL, PostgreSQL, SQL Server, MongoDB, Redis and replication.
DevOps Engineer Roadmap
Linux, Docker, Kubernetes, Terraform, Ansible, CI/CD and monitoring.
Interview Preparation Roadmap
Behavioral, DSA in Java or Python, SQL, cloud, data and AI/ML.
Kubernetes Administration Roadmap
Controllers, RBAC, observability, networking, autoscaling and Helm.
Kubernetes Engineer Roadmap
Pods, Deployments, Services, config, Helm, autoscaling and security.
Python Developer Roadmap
Python basics, OOP, concurrency, decorators, testing and security.
System Design Roadmap
Caching, consistent hashing, rate limiting, capacity and consensus.
Software Testing Roadmap
Test strategy, pytest, Selenium, Playwright, API and contract tests.
Topic roadmaps
Milestones within a single topic
AI Agents Learning Roadmap
A structured path from building your first tool-using agent to orchestrating multi-agent systems that plan, remember, and self-correct.
LLM Engineering Learning Roadmap
A structured path from how a transformer actually works to building and serving production-grade LLM applications — internals, prompting, RAG, fine-tuning, inference, and safety.
Machine Learning Learning Roadmap
A structured path through ML fundamentals — from understanding algorithms to building production-grade models with interpretability and fairness.
MCP Learning Roadmap
A Model Context Protocol roadmap: first server and client, the wire protocol, client features and testing, OAuth and security, then production and tracing.
MLOps Learning Roadmap
A structured path from experiment tracking basics to fully automated ML platforms — covering CI/CD, monitoring, data versioning, and serving.
NumPy Learning Roadmap
A structured path from NumPy beginner to expert — with milestones, time estimates, and what to build at each stage.
Pandas Learning Roadmap
A structured path from pandas beginner to production data engineer — with milestones, time estimates, and what to build at each stage.
PyTorch Learning Roadmap
A structured path from tensor basics to training and deploying custom neural networks at scale.
Scikit-Learn Learning Roadmap
A structured path from sklearn beginner to ML practitioner — from your first classifier to building production-ready pipelines.
Cybersecurity Learning Roadmap
A defensive cybersecurity roadmap: shared fundamentals, then five paths (beginner, ethical hacker, SOC, AppSec, cloud) built from runnable lessons.
TensorFlow Learning Roadmap
A structured path through TensorFlow and Keras — from your first model to production deployment on mobile, server, and cloud.