PAST COMMUNITY EVENT · UNIVERSITY OF IOANNINA

Building With Generative AI: From Basics To Advanced Patterns

Master Generative AI from fundamentals to advanced patterns — build real-world projects, automate coding and boost productivity through hands-on learning.

March 11, 2026  ·  University of Ioannina
TRAINING COHORT
Crash Course
DURATION
2 Hours
TRAINING TYPE
In-Person · Instructor-Led
WHAT TO EXPECT
Hands-On Frameworks & Use Cases
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2
Sessions
2
Hours
100+
Attendees
In-Person
Format
// Overview

An Intensive Crash Course On Gen AI Applications

This intensive 2-hour lecture equips university students with both foundational knowledge and advanced expertise in Generative AI development using TypeScript. Blending essential theory with hands-on coding demonstrations, the session explores the core principles and state-of-the-art techniques powering today's production AI systems — so students can confidently build and innovate with Generative AI in real-world scenarios.

Generative AI is rapidly transforming healthcare, finance and beyond. By bridging theory with hands-on experience, this lecture prepares students for the demands of AI-engineering roles and a successful career in the field.
// Curriculum

Curriculum & Agenda

09:30 – 10:30Foundation Block

Practical Generative AI — TypeScript Essentials, LLMs & Cost-Efficient Coding

Establishes the technical groundwork for building real-world AI applications.
  • TypeScript essentials for AI — patterns for APIs, structured outputs, async workflows and strongly-typed responses; type safety as a competitive advantage.
  • How LLMs actually work — tokens, context windows, temperature, embeddings, inference and the probabilistic nature of generation.
  • Live code demo — integrating an LLM with real-time streaming: structured prompts, streaming tokens, responsive UI and clean async flows.
  • Token management & cost — how tokenisation works, estimating prompt + completion cost, monitoring usage and designing efficient prompts.
10:30 – 11:30Agents

Architecting AI Agents — From Advanced Prompting to Production-Ready Systems

Moves beyond prompt-response into structured reasoning and autonomous architectures.
  • Advanced prompt engineering — Chain-of-Thought, ReAct (Reason + Act) and Self-Ask as deliberate system design, not trial-and-error.
  • Agent architecture & patterns — planner-executor, tool-augmented agents, short- vs long-term memory, retrieval-augmented workflows and multi-step loops.
  • Live code demo — a ReAct-style agent with tool integration: deciding when to call a tool, handling intermediate reasoning and feeding results back into the loop.
  • Production considerations — ethical constraints, responsible AI usage, observability and logging.
// Tech Stack

Tools & Tech Stack

TypeScript
LLM APIs
Streaming
Embeddings
ReAct Agents
RAG / Retrieval
Chain-of-Thought
Tool-Augmented Agents
// Outcomes

What You'll Walk Away With

Session Format

  • Structured lecture with real-world examples
  • Code walkthroughs on slides showing best practices
  • Visual demonstrations of AI concepts and patterns
  • Q&A opportunities at the end

Technical Requirements

  • Projector / screen for presentation
  • Audio system for clear delivery
  • No special software or student laptops required

Post-Lecture Support

  • Complete slide deck (PDF)
  • GitHub repository with all code examples
  • Live community for ongoing support
// Audience

Who It's For

Designed for university students and early-career developers ready to read, interpret and build with real production AI code.

CS & Engineering StudentsAspiring AI EngineersDevelopers New to GenAIBuilders & Tinkerers
// Disrupt AI Collective

Join Greece's Gen AI Community

This was a Disrupt AI Collective community crash course — free, hands-on and open to all. Be first in the room for the next one.

Learn More Join the Community