#AI Engineer

Master Python, Artificial Intelligence, Generative AI, LLMs, Prompt Engineering, RAG, and AI Agents with hands-on AI Engineer Training at SQL School. Learn to build intelligent AI applications, automate workflows, develop AI-powered chatbots, and deploy real-world AI solutions. Gain practical experience through real-time projects, expert-led training, and interview preparation to build a successful AI Engineering career.

Training Highlights

✅ Python Programming for AI & Machine Learning
✅ Artificial Intelligence & Generative AI Fundamentals
✅ Prompt Engineering & Large Language Models (LLMs)
✅ LangChain, Vector Databases & RAG Applications
✅ Build AI-Powered Chatbots & Intelligent Assistants
✅ AI Agents, Workflow Automation & Multi-Agent Systems
✅ AI Application Deployment, Security & Responsible AI
✅ 2 Real-Time Projects + 1 Capstone Project

Modules We Learn

✅ Module 1: Microsoft Copilot & Generative AI Fundamentals
✅ Module 2: Prompt Engineering for Copilot
✅ Module 3: Microsoft 365 Copilot for Productivity
✅ Module 4: Copilot Chat & Agent Builder
✅ Module 5: Microsoft Copilot Studio: Agent Development
✅ Module 6: Enterprise Readiness & Responsible AI
✅ Module 7: Guided Real-Time Projects
✅ Module 8: Capstone, Assessment & Career Applications

Course Duration: 1.5 Months

Course Content
FAQs

Azure AI
Course Contents:

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Module 1: Microsoft Copilot & Generative AI Fundamentals

Chapter 1. AI Foundations

AI, machine learning, generative AI and large language models
How prompts, context and output generation work
Hallucinations, accuracy, grounding and human review
Typical workplace use cases and limitations

Chapter 2. Microsoft Copilot Ecosystem

Microsoft Copilot consumer experiences versus Microsoft 365 Copilot Chat
Microsoft 365 Copilot in work apps and the role of Microsoft Graph
Microsoft Copilot Studio and agent use cases
Overview of GitHub Copilot and Microsoft Security Copilot (orientation only)

Chapter 3. Setup, Access & Licensing

Work/school account and Microsoft 365 tenant concepts
Licensing and feature availability overview
Copilot entry points, user interface and settings
Lab readiness checklist and data safety rules

Module 2: Prompt Engineering for Copilot

Chapter 4. Writing Better Prompts

Goals, context, source information and desired format
Role, tone, audience and output constraints
Zero-shot, few-shot and stepwise prompting
Prompt templates for recurring work

Chapter 5. Advanced Prompt Workflows

Prompt iteration and follow-up questions
Summarization, extraction, classification and rewriting
Comparing options and requesting evidence/citations
Evaluating outputs with a practical quality checklist

Chapter 6. Prompting Lab

Draft professional emails and meeting agendas
Create a project plan and status update
Summarize lengthy documents with source checking
Build a personal prompt library

Module 3: Microsoft 365 Copilot for Productivity

Chapter 7. Copilot in Word

Create first drafts, summaries and rewrites
Adjust voice, clarity, structure and length
Work with source documents where supported
Review generated content and factual accuracy

Chapter 8. Copilot in Excel

Describe data trends and request analysis
Explore formulas, tables and visual summaries
Interpret results and cross-check calculations
Practice with sample sales and operations data

Chapter 9. Copilot in PowerPoint

Build presentation outlines and draft slides
Summarize decks and refine slide messaging
Create speaker notes and adapt audience tone
Review design and data integrity

Chapter 10. Copilot in Outlook & Teams

Draft, summarize and prioritize email conversations
Prepare meetings and summarize discussions
Identify action items and follow-up tasks
Understand meeting transcription/recording prerequisites

Chapter 11. Microsoft 365 Search & Collaboration

Finding organizational information within access permissions
Working with SharePoint and OneDrive content
Grounding, references and permission boundaries
Cross-application productivity scenarios

Module 4: Copilot Chat & Agent Builder

Chapter 12. Working with Copilot Chat

Web-grounded and work-grounded experiences
Files, context and supported chat capabilities
Creating structured reusable conversations
Checking references and data boundaries

Chapter 13. Introduction to AI Agents

Chat assistants versus task-oriented agents
Agent instructions, knowledge, tools and actions
Agent scope, personas and guardrails
When an agent is the right solution

Chapter 14. Build a Simple Agent

Define agent objective and user questions
Create a declarative agent using available builder tools
Attach approved knowledge sources where supported
Test responses and refine instructions

Module 5: Microsoft Copilot Studio: Agent Development

Chapter 15. Copilot Studio Fundamentals

Environments, agent creation and authoring interface
Agent instructions, orchestration and configuration
Standard authoring concepts and feature differences
Create a customer-support or course-enquiry agent

Chapter 16. Knowledge & Conversations

Add approved websites, files and connected knowledge
Ground answers and address unsupported questions
Topics, variables and conversation branches
Fallbacks, escalations and safe response design

Chapter 17. Tools, Actions & Automation

Overview of tools, connectors and agent flows
Basic Power Automate integration concepts
Capture user inputs and invoke a permitted action
Error handling, confirmation and human handoff

Chapter 18. Test, Publish & Monitor

Test cases and response validation
Publish to supported channels based on licensing
Analytics, user feedback and response improvement
Versioning, maintenance and release checklist

Module 6: Enterprise Readiness & Responsible AI

Chapter 19. Microsoft 365 Security Foundations

Microsoft Entra identity and least-privilege access
Microsoft Graph and existing data permissions
SharePoint/OneDrive content hygiene and oversharing
Sensitive data handling and organizational policy

Chapter 20. Responsible AI & Governance

Privacy, fairness, transparency and accountability
Prompt injection, inaccurate answers and misuse risks
Human-in-the-loop approvals and quality reviews
Audit, data retention and governance overview

Chapter 21. Adoption & ROI

Identify high-value productivity workflows
Measure time saved and output quality
Create prompt/agent adoption playbooks
Plan support and ongoing improvement

Module 7: Guided Real-Time Projects

Chapter 22. Project 1: Productivity Accelerator

Create a reusable business prompt library
Summarize a project brief and prepare an executive update
Build a presentation and professional email follow-up
Deliver outputs with an accuracy and privacy checklist

Chapter 23. Project 2: Knowledge Assistant

Define FAQs for HR, IT support or training enquiries
Create an agent with approved knowledge documents
Test known, unknown and sensitive questions
Deliver a demo plus test evidence

Module 8: Capstone, Assessment & Career Applications

Chapter 24. Capstone: Business Process Agent

Select a use case and write the requirement document
Configure agent instructions, knowledge and conversation flow
Connect one simple approved action or escalation path
Test, demonstrate and document limitations

Chapter 25. Assessment & Portfolio

Prompt engineering practical assessment
Copilot productivity task demonstration
Agent build, test and presentation rubric
Prepare project README, screenshots and portfolio summary

Chapter 26. Roles, Next Steps & Certification Guidance

Copilot champion and business productivity roles
Copilot Studio maker and automation pathways
Microsoft Learn practice resources and role-based learning
Certification mapping subject to current Microsoft exam catalog

What is the Azure AI & Gen AI course, and who should join this program?

This course is designed for Freshers, Python Developers, SQL Developers, Data Engineers, Software Engineers, IT Professionals, and Career Switchers. It covers Microsoft Azure AI, Azure OpenAI, Generative AI, LLMs, Prompt Engineering, RAG, Azure AI Search, AI Agents, and Cloud AI Application Development.

What are the prerequisites to learn Azure AI & Generative AI?

No prior Azure AI or Generative AI experience is required. Basic computer knowledge is sufficient to begin. Python, SQL, or Azure knowledge is helpful but not mandatory. The training starts with Azure AI fundamentals and progresses step by step to advanced AI application development.

What modules are included in the Azure AI & Gen AI training?

The course covers Azure AI Services, Azure AI Foundry, Azure OpenAI, Prompt Engineering, Large Language Models (LLMs), Azure AI Search, Vector Databases, Retrieval-Augmented Generation (RAG), AI-Powered Chatbots, Azure AI Agents, Workflow Automation, Security, Responsible AI, and AI Application Deployment.

Is the Azure AI & Gen AI course fully practical and project-oriented?

Yes. SQL School provides LIVE instructor-led training, hands-on Azure labs, practical assignments, and industry-oriented AI projects. Students learn to integrate AI models, develop intelligent applications, build RAG solutions, create AI Agents, and deploy AI-powered applications using Microsoft Azure.

What real-time projects will I work on in this course?

The training includes 2 Real-Time Projects and 1 Capstone Project. Project examples include an Azure OpenAI-Powered Chatbot, Enterprise Document Search using Azure AI Search and RAG, and an Intelligent AI Agent for business workflow automation using Azure AI services.

Will I learn how to build, deploy, and secure AI applications on Azure?

Yes. The training covers AI application development, model integration, API connectivity, Azure deployment concepts, authentication, access control, data security, monitoring, and Responsible AI practices. Students learn how to build and deploy scalable AI-powered solutions on Microsoft Azure.

What career opportunities are available after completing Azure AI & Gen AI training?

Depending on their existing skills and practical experience, learners can pursue roles such as Azure AI Engineer, Generative AI Developer, AI Application Developer, LLM Application Developer, RAG Developer, and AI Agent Developer. SQL School also provides certification guidance, interview preparation, and career support.