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AI-103 - Develop AI apps and agents on Azure

The AI-103 course prepares participants to design and build modern AI-powered applications and agent-based solutions using Microsoft Azure. It focuses on generative AI, large language models (LLMs), AI agents, and their integration into enterprise systems.
Level
Designed for participants with basic knowledge and experience
intermediate
Course length
4 days
Language
 cz
Course code
PU00010006
AI
Category:
Do you want this tailor-made course to your company? Contact us

Courses with lecturer

Term
Language
Place
Form
?
How and where the course takes place.
Price without VAT
7. - 10. 9. 2026
Language
Place
online
Form
virtual classroom
?
Online training with a lecturer at a specific time.
Code of the course: PU00010006-0003
Price without VAT
29 900 Kč
7. - 10. 9. 2026
Language
Place
Praha
Form
classroom
?
The course with an instructor in classroom.
Code of the course: PU00010006-0004
Price without VAT
29 900 Kč
7. - 10. 12. 2026
Language
Place
online
Form
virtual classroom
?
Online training with a lecturer at a specific time.
Code of the course: PU00010006-0005
Price without VAT
29 900 Kč
7. - 10. 12. 2026
Language
Place
Praha
Form
classroom
?
The course with an instructor in classroom.
Code of the course: PU00010006-0006
Price without VAT
29 900 Kč
Open term
?
We will agree on a specific date together. This is a non-binding order.
Language
Place
online
Form
virtual classroom
?
Online training with a lecturer at a specific time.
Code of the course: PU00010006-0001
Price without VAT
29 900 Kč
Open term
?
We will agree on a specific date together. This is a non-binding order.
Language
Place
Praha
Form
classroom
?
The course with an instructor in classroom.
Code of the course: PU00010006-0002
Price without VAT
29 900 Kč

Required knowledge

  • programming experience (Python, JavaScript, or C#)
  • basic understanding of cloud services (Azure preferred)
  • familiarity with REST APIs and data handling
  • basic knowledge of AI/ML concepts

Target audience

  • developers and AI engineers
  • cloud and application specialists
  • teams building AI-driven applications and automation
  • anyone working with generative AI and AI agents

Course content

Introduction to Generative AI and Azure AI Ecosystem
  • overview of generative AI and real-world use cases
  • AI solution architecture on Azure
  • overview of services (Azure AI Services, Azure OpenAI, AI Foundry)
  • use cases: chatbots, assistants, automation
Working with Large Language Models (LLMs)
  • fundamentals of LLMs
  • prompt engineering (zero-shot, few-shot, chain-of-thought)
  • context handling and output control
  • tokenization, limits, and cost optimization
  • basics of fine-tuning and model customization
Azure OpenAI Service
  • model deployment and configuration
  • working with APIs (REST, SDKs)
  • access management and security
  • performance tuning and scaling
  • usage and cost monitoring
AI Agent Design and Development
  • concept of AI agents and agent-based systems
  • agent architecture design
  • multi-agent orchestration
  • planning, reasoning, and tool usage
  • integration with external tools and APIs
5. Retrieval-Augmented Generation (RAG)
  • RAG architecture principles
  • working with custom data (documents, databases)
  • embeddings and vector search
  • Azure AI Search and data indexing
  • knowledge system design
AI Integration into Applications
  • designing AI-enabled backend services
  • integration via REST APIs and SDKs
  • frontend integration (chat UI, assistants)
  • connecting to enterprise systems (CRM, ERP)
  • workflow automation using AI
Security, Governance, and Responsible AI
  • responsible AI principles
  • access control and data protection
  • content filtering and safety mechanisms
  • compliance and regulations (AI Act overview)
  • auditability and transparency
Monitoring, Evaluation, and Optimization
  • AI output quality metrics
  • evaluation of LLM applications
  • logging and monitoring
  • prompt and architecture optimization
  • cost and performance management

Materials

Materials are in electronic form.

Objectives

  • design and build applications powered by generative AI
  • work with Azure OpenAI and LLM models
  • develop and orchestrate AI agents
  • implement Retrieval-Augmented Generation (RAG) solutions
  • integrate AI into enterprise systems and workflows
  • address security, governance, and responsible AI

Do you want this tailor-made course for your company?

Contact us

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Do you want this tailor-made course for your company?

Contact us

News with the course

Náhledový obrázek novinky
Microsoft 10. 6. 2024
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Why with us