Getting Started with Generative AI

Course code: PT1002

Apply generative AI to daily workplace tasks without becoming an AI specialist. Generative AI foundations cover what GenAI is and how it differs from traditional AI, tokenization, embeddings, decoding, foundation model architectures, and the model settings such as temperature, top-p, and max tokens that shape output quality. Prompt engineering covers the CLEAR framework and RCTO/RTF structures, the adaptive iteration loop, and workflow decomposition with human checkpoints between stages. Use cases and ethics cover real-world applications, the ethical considerations around responsible use, and the regulatory and governance issues organizations now face. Hands-on no-code labs produce a personal prompt library, a workplace-task workflow, and case-study analyses across cross-industry examples. The course is designed as onboarding for working professionals across business, technical, and operations roles adopting AI tools.

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About This Course

Duration:

1 Day

Skills Gained

By the end of this course, participants will be able to:

Apply key generative AI concepts to identify productivity opportunities
Recognize ethical implications of generative AI in business contexts
Apply prompt engineering frameworks to automate routine tasks
Analyze the benefits and challenges of generative AI for informed decisions
Improve content creation and data analysis through effective prompting

Who Can Benefit

This course is designed for:

Business Professionals & Managers
Technical Staff & Developers
Operations & Support Teams
Anyone New to Generative AI Tools

Prerequisites

Participants should enter this course with:

None required

Organizational Objectives

This course assists organizations to:

Build baseline GenAI literacy across knowledge-work teams in one day
Reduce time spent on first-draft writing and routine summarization through prompt patterns
Lower governance risk by training staff to recognize ethical and responsible-use issues
Establish a shared vocabulary for AI-assisted work across functions

Software

All attendees must have a modern web browser and an Internet connection.

You'll Learn

Module 1 - Understanding Generative AI

By the end of this module, you will be able to differentiate generative AI from traditional AI, describe how foundation models produce text and other modalities, and recognize the model settings and parameters that influence output quality.

Defining intelligence, artificial intelligence, and generative AI
Differentiating generative AI from traditional AI
How generative AI works (tokenization, embeddings, decoding)
Benefits and challenges of generative AI
Popular GenAI models and frameworks
LLM settings and parameters; intro to prompt engineering, RAG, and agentic AI
Hands-on Lab: Explore tokenization, embeddings, and core LLM settings hands-on without writing any code.

Module 2 - Basics of Prompt Engineering

By the end of this module, you will be able to write structured prompts using the CLEAR and RCTO/RTF frameworks, iterate prompts through a deliberate loop, and decompose tasks into sequenced prompts with human checkpoints between stages.

CLEAR framework
RCTO / RTF structure
Adaptive iteration loop
Workflow decomposition (analyze/transform/write)
Human checkpoints between stages
Prompt-vs-workflow-vs-tool decision
Hands-on Lab: Author and iterate one effective ChatGPT prompt that uses CLEAR and at least one n-shot variant for a workplace task.

Module 3 - Generative AI Use Cases and Ethics

By the end of this module, you will be able to identify high-value generative AI use cases inside your work context, recognize the ethical considerations that govern responsible use, and reason about AI-related risk through real case studies.

Real-world applications of generative AI
Ethical considerations in generative AI
Responsible use of generative AI
Case studies and examples
Hands-on Lab: Identify candidate GenAI use cases in your team’s workflow and spot the ethical issues each one raises.