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Introduction to AI Engineering

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A complete, premium AI Engineering course, updated for 2026. Covers the fundamentals of artificial intelligence, machine learning (supervised, unsupervised, deep learning), Large Language Models (GPT-5.5, Claude Opus 4.8, Gemini 3.1 Pro), working with LLM APIs, prompt engineering, streaming and function calling, AI tools for developers (Cursor, GitHub Copilot, Claude Code), RAG and vector databases, AI agents with tool use and MCP, evaluation and testing, AI security, cost control in production, plus case studies and hands-on projects.

11 modules
28 lessons
~25h duration
v1.0 version
AI professor An AI agent built into every lesson — ask questions and get instant answers based on the course content
Hands-on exercises Real scenarios and practical exercises directly on the platform, with instant feedback
Progress & analytics A personal dashboard with statistics, streaks, scores and structured learning paths
Interactive AI quizzes Questions generated by AI and adapted to your level, with detailed explanations
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Content in English
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What you will learn

Practical skills you gain by completing this course

Fundamentals of Artificial Intelligence
Machine Learning Essentials
Large Language Models and Modern Architectures
Working with LLM APIs and Integrations
AI Tools for Developers
RAG, Embeddings and Vector Databases
AI Agents and Automation
Evaluation, Testing and AI Security
Case Studies and Hands-On Projects
Appendix: Official Resources, 2026 Updates and Learning Paths
Final Quiz — Introduction to AI Engineering

Who it is for

Developers Software engineers Solution architects CTOs / Tech Leads Data Scientists ML Engineers DevOps Engineers

Recommended level

Beginner

No prior knowledge required. The course starts from scratch.

Updates

Regular

Content updated regularly with the latest practices from the industry.

Category

IT & Engineering

A technical course for IT professionals — available with individual course access or the IT Pro / All Access bundle.

Beginner level

Suitable for beginners

No prior knowledge needed. The course starts from scratch and builds step by step.

Always up to date

Up-to-date content

The course is updated regularly with the latest information, tools and practices from the industry.

Practical and applied

28 lessons with real examples

Each lesson includes practical scenarios, actionable checklists and quizzes to check your understanding.

Curriculum

11 modules, 28 lessons — structured to learn step by step.

11 modules
28 lessons
~25h of content
Interactive quizzes
Free preview available What Artificial Intelligence Is in the Real World
Read the preview
1 Free preview lesson What Artificial Intelligence Is in the Real World
Read the preview
2 The History and Evolution of AI: From Turing to GPT-5.5
55 min
3 Key AI Concepts for Software Engineers
55 min
1 Supervised Learning: Classification and Regression
55 min
2 Unsupervised and Reward-Based Learning
55 min
3 Neural Networks and Deep Learning
55 min
1 What Are Large Language Models
55 min
2 Tokenization and Text Processing
55 min
3 Transformer Architectures and State-of-the-Art Models in 2026
55 min
1 Working with LLM APIs: OpenAI, Anthropic and Google
55 min
2 Prompt Engineering Fundamentals for Developers
55 min
3 Streaming, Function Calling, and Tool Use
55 min
1 Cursor, GitHub Copilot, and Claude Code: AI-Native IDEs in 2026
55 min
2 AI Code Generation: From Prototype to Production
55 min
3 Debugging, Refactoring, and Code Review with AI
55 min
1 Introduction to RAG and Embeddings
55 min
2 Vector Databases and Semantic Indexing
55 min
3 Building a Complete RAG System
55 min
1 AI Agents Fundamentals: From Chatbot to Autonomous Agent
55 min
2 Building Agents with Tool Use and MCP
55 min
1 Evaluating and Testing AI Applications
55 min
2 AI Security: Prompt Injection, Jailbreaking, and Protection
55 min
3 Cost Control and Optimization in Production
55 min
1 Case Study: Building an AI Chatbot for a European SaaS Company
55 min
2 Hands-On Project: Build Your First AI Application
60 min
1 Official Resources, 2026 Updates, and Learning Paths
40 min
2 EU AI Act Compliance for Engineers: Transparency, Literacy, and Risk Frameworks
35 min
1 Final Assessment — Introduction to AI Engineering
60 min
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