Course Brief

This module provides a rigorous immersion in generative AI, covering foundational model families and responsible use, alongside modern tools such as ChatGPT, Claude, Gemini, and DeepSeek. Learners advance from principled prompt design to building agentic systems with Microsoft Copilot Studio, translating theory into dependable, auditable solutions suited to real organisational workflows and governance requirements.


By the end, learners will characterize strengths and limitations of major generative architectures; compare tools and deployment options; and conduct systematic prompt engineering, including Few Shot Prompting, Chain of Thought, and Self Consistency Prompting. They will design task-oriented agents in Copilot Studio; configure connectors, authentication, entities, variables, and state; orchestrate agent flow; integrate Prompt tools and the Model Context Protocol (MCP) and instrument testing, monitoring, and iteration aligned with compliance and business objectives. Learners will evaluate outputs for quality and safety, iterate prompts and flows based on test cases, and align solutions with organizational policies and stakeholder needs. The module culminates in assembling an end-to-end agent demonstrating robust intent handling and effective task completion.


Graduates gain the capacity to deliver differentiated, trustworthy agents faster and at lower risk. The resulting capability compounds across products and operations, enabling measurable efficiency, better customer experiences, and confident compliance, creating a durable career advantage in AI-enabled organizations.

Course Knowledge, Skills & Ability Summary

At the end of the course, you will be able to acquire the following:

Knowledge

  • Define key concepts of Generative AI and its applications in various industries.
  • Explain the principles and techniques of prompt engineering for optimizing AI-generated responses.
  • Differentiate between basic and advanced prompt engineering methods to enhance AI outputs.
  • Describe the functionalities of Microsoft Copilot Studio for agent creation and enhancement.
  • Describe how Copilot Studio’s Prompt tools and MCP tools coordinate templating, binding, and capability negotiation.

Skills

  • Design effective prompts to generate accurate and relevant AI responses.
  • Apply advanced prompt engineering techniques to refine AI-generated content.
  • Develop AI agents using Microsoft Copilot Studio.
  • Enhance agent interactions by integrating advanced Copilot Studio features.
  • Configure Prompt templates and register MCP tools to bind entities, negotiate capabilities, and execute secure actions

Ability

Effectively demonstrates proficiency in prompt engineering to create and optimize AI-generated 
content for improved productivity in professional environments, and in designing and building 
intelligent agents using Microsoft Copilot Studio.

Blended Learning Journey

(60.5 Hours)

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E-Learning

12 Hours

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Flipped Class

16 Hours

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Mentoring Support (Sync) (Assignment)

11 Hours

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Mentoring Support (Sync) (Project)

9 Hours

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Mentoring Support (Async)

12 Hours

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Summative Assessment

0.5 Hours

Module Summary

WSQ Generative AI (SF)

Module Brief

This module provides a rigorous immersion in generative AI, covering foundational model families and responsible use, alongside modern tools such as ChatGPT, Claude, Gemini, and DeepSeek. Learners advance from principled prompt design to building agentic systems with Microsoft Copilot Studio, translating theory into dependable, auditable solutions suited to real organisational workflows and governance requirements.


By the end, learners will characterize strengths and limitations of major generative architectures; compare tools and deployment options; and conduct systematic prompt engineering, including Few Shot Prompting, Chain of Thought, and Self Consistency Prompting. They will design task-oriented agents in Copilot Studio; configure connectors, authentication, entities, variables, and state; orchestrate agent flow; integrate Prompt tools and the Model Context Protocol (MCP) and instrument testing, monitoring, and iteration aligned with compliance and business objectives. Learners will evaluate outputs for quality and safety, iterate prompts and flows based on test cases, and align solutions with organizational policies and stakeholder needs. The module culminates in assembling an end-to-end agent demonstrating robust intent handling and effective task completion.


Graduates gain the capacity to deliver differentiated, trustworthy agents faster and at lower risk. The resulting capability compounds across products and operations, enabling measurable efficiency, better customer experiences, and confident compliance, creating a durable career advantage in AI-enabled organizations.

Other Information
  • SWDA Module Reference No: TGS-2026066403
  • Module Validity Date: 2028-01-31

Target Audience & Prerequisite

Target Audience

Prerequisite

  • Minimum Age: Minimum 21 years.
  • English Proficiency: Minimum IELTS 5.5 or its equivalent.
  • Academic Qualification: Minimum one credit in O Level or its equivalent
  • Experience: Minimum 1 year of experience in any business process

Graduation Requirements

Certificates

Academic Qualification

  • No Academic Qualification for this course

Statement of Attainment

  • WSQ Generative AI (SF)

    ICT-DIT-4029-1.1: Text Analytics and Processing

Industry Skills Certificate

  • WSQ Generative AI (SF)

    Microsoft : Microsoft Applied Skills credential PL-7008: Create agents in Microsoft Copilot Studio

*Taking this certification is not mandatory. However, if the learner wishes to pursue it, they need to register for the examination directly with the vendor after paying the necessary fees.

Other Information

Course Reference

  • SWDA Course Reference No: TGS-2026066403

  • Course Validity Date: 2028-01-31

  • Course Developer : Lithan Academy

Pricing & Funding