Learning roadmaps for 2026

Build products on top of large language models.

Go deeper into models: prompting, fine-tuning and multimodal AI.

Build AI solutions directly with customers.

Train, deploy and monitor machine learning models.

Turn data into answers and dashboards.

Use statistics and machine learning to predict and explain.

Build backends, automation and data tools with Python.

Build fast, accessible websites and web apps.

Build the APIs, databases and services behind apps.

Build complete web apps, front to back.

Design, build and run systems on AWS, Azure or Google Cloud.

Protect systems and data, and manage cyber risk for the business.

Lead technical design across teams and systems.

How AI, ML, deep learning, generative AI and agents fit together.

Build AI that answers from your own documents.

Connect AI apps to tools and data with one open standard.

Build AI that plans, uses tools and gets work done.

Build, deploy and monitor machine learning models reliably.

Run LLM applications in production: prompts, evals, cost and safety.

Operate AI agents safely: tracing, evals, guardrails and cost control.

Build robots that sense, think and move.

Connect devices, collect data and automate the physical world.

Crack coding interviews and write efficient code.

Design scalable, reliable systems and ace design interviews.

The language of AI, data and automation.

Build fast, documented Python APIs.

The database most new apps choose.

The most used library for building user interfaces.

The most widely used cloud platform.

Package apps and run them anywhere.