About The Training
This training program focuses on Generative AI (GenAI) and Large Language Models (LLMs) in particular. In 2023 when ChatGPT became popular, a variety of methods were designed to construct effective instructions to direct LLMs to a desired output. These techniques are known as ‘Prompt Engineering’. Modern models evolve fast and the technology changes move from ‘Prompt Engineering’ to more efficient ‘Context Engineering’ patterns. This program is designed to equip you with comprehensive knowledge and practical skills to maximize the results from modern language models, as well as exploit undocumented features of Generative AI tools learned from real business experience working on dozens of GenAI projects.
By the end of this training, you will be able to:
- Explain how modern LLMs work and what affects the quality, reliability, and limitations of their outputs.
- Design better AI interactions using context engineering instead of relying only on basic prompting techniques.
- Apply key GenAI patterns such as RAG, structured outputs, function calling, and context management to practical business tasks.
- Evaluate where GenAI can create real value in business workflows and where human control or expert validation is still required.
- Use GenAI tools more confidently for research, analysis, decision support, and market or competitor intelligence.
- How Large Language Models work, reason, and generate outputs.
- How AI applications use LLMs to solve practical business and analytical tasks.
- Key implementation patterns, including RAG, function calling, and Model Context Protocol.
- Where LLMs are most effective, where their limitations are, and how to apply them correctly.
- How to use context engineering for market and competitor analysis with structured inputs and reliable outputs.
- Expert-Led Group Sessions: Engage in group sessions led by an experienced professional from a top IT company, including detailed lectures, hands-on workshops, and Q&A sessions for a comprehensive learning experience.
- Up to date syllabus and content: Training includes the latest models and technologies currently being adopted in the corporate segment. Some tools shown during the training were released less than a month ago.
- Technically rich environment: Course is focused on non-engineering staff, but full of technical details and live demos. Such an approach ensures deep understanding of the subject matter and is extremely practical.
- Focus on business. Most of the examples are learned from real enterprise AI adoption projects and come from practical experience from different domains.
Type: Training
Duration: 4 hours
Format: Live online sessions or offline
Language: English
Level: Fundamentals
Group size: 10–15 participants (preferred)
How LLMs work
- Training kick-off
- AI and ML
- Understanding tokenizer
- Learn how LLMs work based on GPT-3 architecture
- Get familiar with foundation models and major providers
- OpenAI organization and features
- Context window concept in LLMs
- Prompting strategies
- Why prompt engineering is dead
Context Engineering
- LLM models: parameters, data type, model card
- Chat with data and code interpreter
- Ways to improve model reasoning
- Functions calling and structured output
- Advanced prompt engineering
- RAG step by step example with Azure AI and MS Copilot
- Context management in Agentic AI
- How to maintain expertise in Generative AI
This Training is Ideal for You If:
- You are interested in advancing your understanding and skills in Generative AI.
- You aim to leverage AI technologies in creative, development, or strategic roles.
- You seek a comprehensive, practical, and practically grounded perspective on AI applications.
- You are preparing for AI enablement in your organization
