Start Your Career in
GenAI Engineering
Core learning content is free and open-source. Roadmap, interview questions, salary data, and project ideas to help you land your first GenAI role.
Choose Your Learning Track
GenAI Engineer path is live. Cloud, DevOps, and Cybersecurity paths coming soon.
GenAI Engineer
Master LLMs, RAG systems, agentic AI, and production ML pipelines. From fundamentals to building real-world AI applications.
- LLMs & Transformers
- RAG Systems
- Agentic AI
- LangChain & Frameworks
Cloud Engineer
Deploy and scale AI systems on AWS, Azure, and GCP. Learn cloud architecture, Kubernetes, and infrastructure as code.
- AWS / Azure / GCP
- Kubernetes & Docker
- Infrastructure as Code
- CI/CD Pipelines
DevOps Engineer
Master CI/CD pipelines, infrastructure automation, monitoring, and site reliability engineering for modern cloud-native applications.
- CI/CD Pipelines
- Kubernetes
- Terraform & IaC
- Monitoring & SRE
Cybersecurity Engineer
Protect AI systems and cloud infrastructure. Learn security architecture, threat modeling, and compliance frameworks.
- Security Architecture
- Threat Modeling
- Cloud Security
- Compliance & GRC
What's Inside?
Career-focused resources to help you land a GenAI Engineering role.
Structured Learning Paths
From beginner to senior-level, follow a clear progression with no guesswork.
Visual-First Content
Complex concepts explained through interactive infographics and animated diagrams.
Industry-Aligned
Content aligned with real job descriptions. Practice with actual interview questions.
Hands-On Projects
Build portfolio-worthy projects that demonstrate real skills to employers.
Visual Learning
Complex GenAI concepts explained through diagrams and visual guides.
GenAI System Stack
Animated layer-by-layer view of how a query travels through a production GenAI system — from UI to inference.
View InfographicGen AICareer Progression Stages
Visual breakdown of the three stages — Beginner, Intermediate, Senior — and the stack you own at each level.
View InfographicGen AIGenAI Application Stack
Multi-layered architecture of a production GenAI app — from client request to LLM inference and back.
View InfographicGen AILangChain vs LangGraph
Side-by-side execution model: pipelines vs state machines — and when each breaks down in production.
View Infographic