Build an AI App with Azure Using RAG
Build practical skills in building retrieval-augmented generation applications with Azure OpenAI, Azure AI Search, enterprise data, security, evaluation, and deployment through four structured lessons with demonstrations, hands-on activities, troubleshooting, validation checklists, and an applied improvement plan.
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-by SkillDynamo
- 0 Students
- Last updated
Course Description
This SkillDynamo course develops practical, role-relevant capability in building retrieval-augmented generation applications with Azure OpenAI, Azure AI Search, enterprise data, security, evaluation, and deployment. The learning path progresses from essential concepts and planning to implementation, validation, troubleshooting, and operational use.
Learners work through realistic scenarios, guided demonstrations, applied exercises, and evidence-based reviews. Every topic is connected to workplace responsibilities, common risks, quality controls, and measurable outcomes.
The course helps professionals make informed decisions, identify failure points, communicate results, and create an actionable improvement plan for future projects.
What You Will Learn
- Explain retrieval-augmented generation, embeddings, vector stores, prompts, orchestration, and grounded response flow
- Design Azure OpenAI, Azure AI Search, storage, identity, networking, application, and monitoring components
- Prepare approved documents with cleaning, chunking, metadata, embeddings, indexing, and refresh workflows
- Configure vector, keyword, semantic, hybrid, filtering, ranking, and access-aware retrieval
- Implement query processing, retrieval, context construction, prompt templates, citations, and conversation state
- Apply managed identities, secret protection, least privilege, network controls, content safety, and input validation
- Measure relevance, groundedness, answer quality, safety, latency, cost, and user acceptance
- Deploy, monitor, troubleshoot, version, support, govern, and improve the RAG application
SkillDynamo Training Approach
SkillDynamo delivers this course through demonstrations, hands-on exercises, scenario analysis, validation checklists, structured troubleshooting, solution reviews, and a final improvement plan. Learners repeatedly practice planning, implementation, evidence collection, testing, correction, and communication so the skills transfer confidently into real workplace situations.
Curriculum
- 1 Section
- 4 Lessons
- 8 Hours
- Course Curriculum4 Items
- 1.1Build an AI App with Azure Using RAG — Lesson 1: RAG Architecture, Requirements and Azure Services2 hours
- 1.2Build an AI App with Azure Using RAG — Lesson 2: Data Ingestion, Chunking and Search Index Design2 hours
- 1.3Build an AI App with Azure Using RAG — Lesson 3: Application Orchestration, Prompting and Security2 hours
- 1.4Build an AI App with Azure Using RAG — Lesson 4: Evaluation, Deployment, Monitoring and Improvement2 hours
SkillDynamo Expert Team
SkillDynamo instructors combine platform knowledge, practical implementation experience, guided demonstrations, scenario-based exercises, troubleshooting methods, and validation checklists to help learners apply the course skills confidently in real work.
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