Crash Course: Deep Dive into LLM APIs

Integration of language models as a full-fledged API backend

Mentor - Oleksandr Krakovetsky, AI Expert | CEO at DevRain | CTO at DonorUA | Author of books on generative artificial intelligence
Program
Crash Course: Deep Dive into LLM APIs
Crash Course: Deep Dive into LLM APIs

This course is a practical and systematic guide to working with large language models for engineers, architects, and technical leaders who want to not just use LLMs, but understand how they work and how to build solutions for their projects.

You will understand the internal architecture of transformers, key properties and limitations of modern language models, learn how to correctly configure them via API, and work with typical problems - in particular, hallucinations, contextual limitations, and unstable response quality.

Special attention is paid to the transition from Prompt Engineering to Context Engineering: how to build systems where the model works stably within the given rules, knowledge, and tools. You will learn how to use LLM as a backend component, build RAG solutions, connect external tools, work with structured responses, and optimize token usage in real production scenarios.

The course combines theory with practical demos so that you can immediately apply the approaches in your own products, services, or internal platforms.

You will understand in detail:

  • how modern language models work "under the hood"
  • what mechanisms determine their behavior
  • how to apply this knowledge to create reliable, manageable, and scalable solutions

A separate block is dedicated to working with benchmarks:

  • how to correctly evaluate models
  • what characteristics have practical significance
  • how to interpret test results on instruction-following, working with long-term context, and other metrics

After the course, you will be able to test models for relevance to specific tasks and make technical decisions based on metrics, not intuition.

Who will be interested?

  • Software developers
  • Tech leaders
  • Architects
  • Anyone who wants to understand how language models work under the hood

Format:

Date and time: February 24&26, online, start at 18:30 (Kyiv time, GMT+2)

Duration of each session: ~2.5 hours

Theory and practice: 50/50, before the start we will send you a selection of materials to familiarize yourself with key concepts. There will be homework to consolidate the material and understand the concepts.

Platform: Zoom. You will receive a link to the broadcast on the eve of the workshop, and it will also be available on this landing page. In addition, all materials and lecture recordings will be available on the learning platform.

Recommended toolset and subscriptions:

  • OpenAI API Playground (Anthropic API Playground, Google AI Studio Playground are also ok)
  • Ollama
  • Postman or other API-manager

Language of the event and presentations: Ukrainian

Program

Day 1
  • Transformer architecture
  • Key concepts, types, characteristics, and functionality of large language models
  • API parameters for configuring the operation of large language models
  • API evolution
  • Metrics for assessing the quality of models
  • Key characteristics of large language models (multimodality, hallucination, reasoning, non-determinism)
  • From Prompt Engineering to Context Engineering

Day 2
  • Structured responses
  • Token optimization
  • Building RAG solutions, typical problems
  • Fine tuning
  • Evals
  • Instrumentalization: function calls, using external tools
  • Benchmarks for model quality assessment ("instruction following", working with long context, AGI, etc.)

Mentor: Oleksandr Krakovetsky

— Co-founder and CEO of the Ukrainian IT company DevRain

— Co-founder and technical director of DonorUA - an intelligent blood donor recruitment system.

— Candidate of Technical Sciences in Information Technology.

—Microsoft Regional Director, Microsoft Artificial Intelligence Most Valuable Professional.

—Microsoft Certified: Azure Data Science Associate

Author of books on generative artificial intelligence

Linkedin , Facebook

Event price

Attendee's ticket

Access to online course sessions

Access to the course recording for a year

Presentations

Additional materials from the speaker

Access to the chat, where the speaker will answer questions

Participant certificate (subject to completing homework)

Free month in Fwdays Club for those who receive a certificate

10% discount on participation in Fwdays conferences

Mentor's e-book "Large Language Models, Query Engineering + Agents" + subscription to updates

Affordable payment by installments from Monobank and purchase by installments from Privatbank

If after the first lesson you realize that the expectations are not match, we will refund the money in full.
4 500 UAH ≈€90
till 1 February 22 hours left
till 15 February — 5000 UAH≈€100
till 26 February — 6000 UAH≈€120
Buy ticket
Group discounts are available for companies 
Напишіть нам на academy@fwdays.com для прорахування вашої знижки.
Sign in
Or by mail
Sign in
Or by mail
Register with email
Register with email
Forgot password?