WSQ Generative AI (SF) (Synchronous and Asynchronous E-Learning)
About This Course
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 characterise 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.
What You'll Learn
Duration of this course is 80.5
The Instructional Units are
1. Introduction to Generative AI Models & Tools
2. Prompt Engineering
3. Microsoft Copilot Studio for Agent Creation
4. Enhancing Agents with Custom Entities and Agent Flow
5. Prompt and MCP Tools in Copilot Studio
Learning Outcomes are
Knowledge Outcomes:
1. Define key concepts of Generative AI and its applications in various industries.
2. Explain the principles and techniques of prompt engineering for optimizing AI-generated responses.
3. Differentiate between basic and advanced prompt engineering methods to enhance AI outputs.
4. Describe the functionalities of Microsoft Copilot Studio for agent creation and enhancement.
5. Describe how Copilot Studio’s Prompt tools and MCP tools coordinate templating, binding, capability negotiation, and permissioning.
Skills Outcomes:
1. Design effective prompts to generate accurate and relevant AI responses.
2. Apply advanced prompt engineering techniques to refine AI-generated content.
3. Develop AI agents using Microsoft Copilot Studio.
4. Enhance agent interactions by integrating advanced Copilot Studio features.
5. Configure Prompt templates and register MCP tools to bind entities, negotiate capabilities, and execute secure actions.
Entry Requirements
Academic Qualification: Minimum 1 credit in O Level or its equivalent
Experience: Minimum 1-year experience in any business process