Build a Copilot App Using Azure AI Studio and Semantic Kernel
Build practical capability in building copilots with Azure AI Studio and Semantic Kernel using models, prompts, plugins, orchestration, memory, grounding, identity, security, integration, evaluation, deployment, monitoring, and responsible AI through four structured lessons with demonstrations…
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-by SkillDynamo
- 0 Students
- Last updated
Course Description
SkillDynamo’s Build a Copilot App Using Azure AI Studio and Semantic Kernel course develops practical, role-relevant capability in building copilots with Azure AI Studio and Semantic Kernel using models, prompts, plugins, orchestration, memory, grounding, identity, security, integration, evaluation, deployment, monitoring, and responsible AI. 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. Each topic is connected to workplace responsibilities, common risks, quality controls, secure working practices, and measurable outcomes.
The content is independently written for SkillDynamo using the supplied source page as the title, update-date, duration, and topic-alignment reference. Learners finish with an applied scenario, documented validation evidence, and a prioritized improvement plan.
What You Will Learn
- Explain and apply azure ai studio, projects, models, prompts, and copilot architecture within Build a Copilot App Using Azure AI Studio and Semantic Kernel
- Configure, validate, and troubleshoot azure ai studio, projects, models, prompts, and copilot architecture using security, quality, governance, and operational controls
- Explain and apply semantic kernel, plugins, functions, orchestration, and memory within Build a Copilot App Using Azure AI Studio and Semantic Kernel
- Configure, validate, and troubleshoot semantic kernel, plugins, functions, orchestration, and memory using security, quality, governance, and operational controls
- Explain and apply grounding, retrieval, identity, security, apis, and integration within Build a Copilot App Using Azure AI Studio and Semantic Kernel
- Configure, validate, and troubleshoot grounding, retrieval, identity, security, apis, and integration using security, quality, governance, and operational controls
- Explain and apply evaluation, responsible ai, deployment, monitoring, and improvement within Build a Copilot App Using Azure AI Studio and Semantic Kernel
- Configure, validate, and troubleshoot evaluation, responsible ai, deployment, monitoring, and improvement using security, quality, governance, and operational controls
SkillDynamo Training Approach
SkillDynamo delivers this Build a Copilot App Using Azure AI Studio and Semantic Kernel course through instructor-led 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, documentation, and communication so the skills transfer confidently into real workplace situations.
Curriculum
- 1 Section
- 4 Lessons
- 16 Hours
- Course Curriculum4 Items
- 1.1Build a Copilot App Using Azure AI Studio and Semantic Kernel — Lesson 1: Azure AI Studio, Projects, Models, Prompts, and Copilot Architecture240 Minutes
- 1.2Build a Copilot App Using Azure AI Studio and Semantic Kernel — Lesson 2: Semantic Kernel, Plugins, Functions, Orchestration, and Memory240 Minutes
- 1.3Build a Copilot App Using Azure AI Studio and Semantic Kernel — Lesson 3: Grounding, Retrieval, Identity, Security, APIs, and Integration240 Minutes
- 1.4Build a Copilot App Using Azure AI Studio and Semantic Kernel — Lesson 4: Evaluation, Responsible AI, Deployment, Monitoring, and Improvement240 Minutes
SkillDynamo Expert Team
Instructor-led delivery focused on Build a Copilot App Using Azure AI Studio and Semantic Kernel with practical demonstrations, guided implementation, scenario analysis, validation, troubleshooting, and role-relevant improvement planning.
- Structured explanations and course-specific demonstrations
- Hands-on exercises, solution reviews, and evidence-based validation
- Security, governance, troubleshooting, and workplace transfer guidance
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