/// FREE ONLINE COURSE

Free AI Engineer
Course: Zero to Pro

A comprehensive AI engineer course — from LLM fundamentals and prompt engineering, through AI agents, RAG, GraphRAG, SLMs and LLMOps, to deploying AI applications in enterprise environments (Azure, AWS, GCP). You learn by doing: every module ends with a project that goes straight into your portfolio.

119
Lessons
85+ hours
Hours of content
16
Modules
5
Portfolio projects
FREE
Price
Start course →See curriculum

// 100% free course. No credit card. No paywall.

✓Lifetime access✓Source code included✓Portfolio projects✓Discord community✓Completion certificate

/// WHO IS THIS FOR

This course is for you if…

Junior / Mid Developer

You code in Python or JS and want to add AI to your CV. This course shortens the path to "AI Engineer" from years to months.

Tech Lead / Architect

Your team is getting AI tasks and you don't know where to start? This course gives you a map of the whole ecosystem and best practices.

Freelancer / Solopreneur

Want to offer AI services to companies? The course teaches not just technical skills — you also learn how to price and deliver AI projects.

Product Manager / Founder

You don't need to code yourself, but you need to understand what's possible. This course gives you the technical literacy needed to work with AI engineers.

/// WHAT YOU'LL LEARN

After completing the AI Engineer course you'll be able to:

→Integrate LLMs (GPT-4, Claude, Gemini) with your own applications via API
→Design and deploy RAG systems on your own company data
→Build advanced data pipelines (ETL, GraphRAG) for unstructured enterprise documents
→Build autonomous AI agents with tool use and long-term memory
→Fine-tune open-source models using LoRA/QLoRA
→Select and run Small Language Models (3B–8B) with GGUF/AWQ quantization for Edge AI
→Create full-stack AI applications (Next.js + FastAPI + LLM)
→Automate business processes with n8n and AI agents
→Implement RBAC and PII masking in enterprise-grade RAG systems
→Deploy AI applications in Azure OpenAI, AWS Bedrock and GCP Vertex AI ecosystems
→Apply LLMOps: prompt versioning, regression testing and CI/CD pipelines for LLMs
→Monitor and evaluate AI systems in production (LangSmith, evals)
→Price, design and deliver AI solutions for clients

/// CURRICULUM

AI Engineer Course Table of Contents

16 modules · 119 lessons · 85+ hours
1.1▶What is an AI Engineer? Role map and job market in 2026
FREE22 min
1.2▶Machine Learning vs Deep Learning vs LLM — differences and when to use what
FREE18 min
1.3▶How do LLMs work? Intuition without math
FREE25 min
1.4▶Ecosystem map: models, tools, frameworks, clouds
20 min
1.5▶AI Engineer environment — Python, VS Code, Jupyter, Git setup
35 min
1.6◉AI Act and liability — what you need to know as a builder
15 min
1.Q◆Quiz: AI Fundamentals
10 min

/// WHAT'S INCLUDED

Everything in one free course

▶
119 HD video lessons

Recorded in studio, PL/EN closed captions, lifetime access on any device

⬡
5 portfolio projects

RAG chatbot, GraphRAG enterprise, email agent, n8n automation and full AI SaaS app — real projects with GitHub repos

◈
Source code

Every lesson has a Git repository with starter code and finished solution to compare

⬢
Community Discord

Access to private Discord server — ask questions, show projects, network with other AI engineers

◆
Lifetime updates

AI moves fast. Course is updated continuously — pay once, learn forever

◉
Completion certificate

PDF + LinkedIn badge confirming AI Engineer competency (verifiable by employer)

/// INSTRUCTOR

PW
Paweł Wiszniewski
AI Engineer & SEO/GEO Specialist

I've been building AI systems for companies for 3 years. I've integrated LLMs with ERP systems, built RAG and GraphRAG platforms on thousands of documents, deployed AI agents that handle business processes 24/7, and built AI systems in Azure and AWS. Day to day I work with GPT-4, Claude, Gemini and open-source LLMs. This course is condensed knowledge from real client projects — no academic theory, emphasis on what actually works.

10+
Years in tech
20+
AI projects
5+
LLMs in production
30+
Happy clients

/// REQUIREMENTS

What do you need to know before the course?

◎Basics of any programming language (Python, JavaScript, TypeScript)
◎Ability to use terminal / command line
◎Knowledge of REST API at the "I know what it is" level
◎Willingness to learn and experiment — AI engineering is mostly practice

/// FAQ

Questions & Answers

/// JOIN NOW

Start learning AI Engineering — for free

The AI Engineer course is 100% free. Sign up to get access to all lessons, projects and community.

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// Lifetime access · No credit card · No paywall