Learning Roadmaps
AI, ML & Generative AI Learning Roadmaps
Each roadmap is a standalone, reviewed technical reference — not a course landing page. They cover what to learn, what to build, exit criteria and decision tables. Use them to orient, then choose a structured course when you are ready for guided implementation.
Choose by background
- Starting from zero? → AI Roadmap for Beginners
- Software engineer? → AI Developer Roadmap
- Want end-to-end systems? → AI Engineer Roadmap
- Analysis & modelling? → Data Science Roadmap
- Building LLM apps? → Generative AI Roadmap
- Building agents? → Agentic AI Roadmap
- Model-focused? → ML Engineer Roadmap
- Operating ML? → MLOps Roadmap
- Operating LLMs? → LLMOps Roadmap
- AI for IT operations? → AIOps Roadmap
Foundations
Students
AI Roadmap for Beginners
Build your first small AI projects and choose the next learning path.
Aspiring data scientists
Data Science Roadmap
Turn a question and dataset into a reproducible analysis and a defensible decision.
Engineering
Software engineers
AI Developer Roadmap
Build and deploy an application that uses models, data and tools reliably.
Engineers who want end-to-end AI system-building capability.
AI Engineer Roadmap
Select, adapt, evaluate and integrate models into a working AI system.
Engineers focused on model development and handoff into MLOps.
ML Engineer Roadmap
Build reproducible predictive systems with sound validation and consistent training and inference.
Applied AI
Engineers and practitioners building generative AI systems.
How to Learn Generative AI: A Practical Roadmap
Build and evaluate generative applications, choosing retrieval and adaptation when they fit the task.
Engineers building reliable
Agentic AI Roadmap
Build a tool-using application with controlled actions, recoverable state and measurable task success.
Operations
ML engineers
MLOps Roadmap
Build a repeatable process for training, releasing, monitoring and recovering an ML system.
Engineers operating LLM and generative AI systems in production.
LLMOps Roadmap
Operate LLM applications with measurable quality, failure recovery, latency, cost and capacity limits.
Platform engineers
AIOps Roadmap
AI for IT operations: telemetry, anomaly detection, event correlation, incident investigation and controlled remediation.
Methodology
Roadmaps are reviewed when production practices, tools or platform patterns materially change. Each roadmap states its scope, exclusions, version and last review date. We do not fabricate market statistics, salaries or learner outcomes; technical claims cite primary sources. Commercial conversion happens through one contextual course bridge placed after the educational roadmap and project sections.