Designing and Implementing a Microsoft Azure AI Solution (AI-102T00

About Education

Designing and Implementing a Microsoft Azure AI Solution (AI-102T00) training course aims to equip software developers with the skills to plan, design, develop, deploy, and manage Azure AI services by taking on the role of Artificial Intelligence Engineer.
This training course will demonstrate the use of services such as Azure Cognitive Services, Azure Cognitive Search, and Azure OpenAI. Real-world scenarios will be addressed using REST APIs and SDKs in C# or Python.

Prerequisites

• Software development knowledge (experience working with at least one of the C# or Python languages)
• Knowledge of Azure fundamentals (Azure portal usage, resource creation, basic service logic)
• Experience working with REST APIs (JSON, HTTP requests, authentication processes)
• Familiarity with basic data processing and artificial intelligence concepts (entry-level knowledge in areas such as machine learning, NLP, and visual processing)
• People with general cloud and software development experience can participate in this training, even if they have not worked with Azure AI services before.

Duration of Training

Toplam Süre: 4 Gün (Günde 6 saat)
Toplam Eğitim Saati: 24 saat
Eğitim Formatı: Uygulamalı ve interaktif yüz yüze /online ortam

Who Should Participate?

• Software developers who want to develop real applications using Azure AI services
• AI engineer candidates who want to plan, manage, and deploy projects involving artificial intelligence.
• Azure portal, people who know C# or Python, and have worked with REST/JSON.
• Professionals who want to develop products in areas such as bots, smart search, and visual/audio/speech analysis.

Educational Content

1. Planning and Preparation

• Azure AI services overview, architectural design, and responsible AI principles

2. Creating & Consuming Cognitive Services

• Source creation, endpoint/key management, REST API and SDK usage.

3. Security & Surveillance

• Identity verification, network security, cost/performance/telemetry monitoring, deployment to container environment

4. Computer Vision

• Visual analysis, classification, object recognition, face recognition, OCR, video analysis.

5. Natural Language Processing

• Language recognition, sentiment analysis, entity recognition, translation, question-answering, speech-to-text and vice versa.

6. Cognitive Search

• Smart search, enrichment, knowledge store, semantic and vector search with Azure AI Search

7. Document Intelligence

• Automatic data extraction from forms and documents, pre-trained & custom models.

8. Generative AI & OpenAI

• Natural language, code, image generation, and RAG-based solutions with Azure OpenAI integration.

What You Will Gain at the End of Training

• Analysing Azure AI solutions to select the right services, plan and configure them securely.
• Transforming various AI scenarios into applications with Cognitive Services
• Developing end-to-end solutions in the fields of visual, language, speech, document, search, and generative AI.
• Deploying solutions in containers, monitoring, ensuring security, and optimising costs.
• Prepare for the AI-102 exam and reach the level required to apply for the Azure AI Engineer Associate certification.

Application Development Training with Claude

About Education

This training is designed for developers, product managers, and tech enthusiasts who want to add a new dimension to application development processes using Anthropic's powerful artificial intelligence model, Claude. Throughout the training, Claude's API capabilities, natural language processing (NLP), data analysis, content creation, automation, and artificial intelligence-powered application scenarios will be covered in detail. Participants will gain hands-on knowledge on topics such as how to develop interactive applications with Claude, how to process user inputs, and how to interpret Claude's outputs.

Prerequisites

• Basic knowledge of software development (Python, JavaScript or similar language preferred)
• Basic information about API usage
• General familiarity with artificial intelligence and machine learning concepts (preferred but not required)

Duration of Training

Toplam Süre: 3 Gün (Günde 6 saat)
Toplam Eğitim Saati: 18 saat
Eğitim Formatı: Uygulamalı ve interaktif yüz yüze /online ortam

Who Should Participate?

• Application developers and software engineers
• Product managers and digital transformation professionals
• Entrepreneurs who want to integrate AI solutions into their products

Educational Content

Day 1 – Fundamentals and Getting Started

Morning – Claude Introduction

• Overview of Claude models (Opus 4, Sonnet 4)
• Choosing the right model: balancing performance and cost

Before Lunch – API Basics

• Obtaining an API key and authorisation
• Messages API structure and message flow
• Practical: Sample application with Python/Node

Afternoon – Prompt Engineering

• Prompt techniques for Claude 4
• Examples of information extraction and structuring
• Application: prompt design that produces structured output

Day 2 – APIs, Tools and Multimodality

Morning – Advanced API Usage

• Message Batching (Message Batches API)
• Prompt caching and performance
• Code example: adding a caching layer

Before Lunch – File & PDF Analysis

• File upload and analysis
• PDF content processing

Afternoon – Vehicle Usage & Agents

• Claude's driving characteristics
• Developing a JSON-based task agent
• Mini agent application: resume parser

Day 3 – Advanced Architecture and Implementation

Morning – Model Context Protocol (MCP)

• What is MCP and what does it do?
• Use with backend integration

Before Lunch – Visual Skills

• Visual data processing, graph/chart interpretation
• Application: extracting structured data from images

Afternoon – Agent Systems & Evaluation

• Smart agents with multi-step planning
• Evaluation criteria and automation
• Project: End-to-end Claude-supported workflow

Additional Module – RAG (Retrieval-Augmented Generation)

• Using Claude with external information sources
• LlamaIndex or database integration
• Setting up a question-and-answer system

What You Will Gain at the End of Training

• Effective use of the Claude API
• Advanced prompt design
• Multimodal and tool-agent systems
• Artificial intelligence evaluation and production readiness