Course Code: tsbs
Duration: 2 hours
Overview:
  • Equip employees with a comprehensive understanding of Generative AI (GenAI).
  • Provide a historical overview and foundational knowledge of GenAI and its workings.
  • Introduce Key AI Architectures and types of AI
  • Demonstrate the Importance of 
  • Introduce various GenAI tools and their strengths and weaknesses.
  • Offer hands-on experience in creating and refining prompts for GenAI.
  • Demonstrate practical applications of GenAI in writing, reading, and conversational contexts.
  • Explore industry-specific use cases, particularly in logistics and finance.
  • Highlight the potential of GenAI to enhance business processes and drive innovation.
  • Emphasise the importance of responsible and ethical use of AI technologies.
  • Enable participants to integrate GenAI into their daily workflows effectively.
  • Address potential concerns and provide strategies for overcoming challenges in AI implementation.
Course Outline:

 

Introduction 

  • Brief welcome and session objectives. - Theoretical
  • Overview of the AI landscape. - Theoretical
  • How GenAI Works - Theoretical
  • LLMs as partners for thought - Theoretical
  • AI is a general purpose tool - Theoretical

 

Key AI Architectures 

  • Understanding Machine Learning, Deep Learning, and Neural Networks - Theoretical
  • Introduction to Natural Language Processing (NLP) and Computer Vision - Theoretical
  • AI Model Development Lifecycle - Theoretical
  • Importance of Data in AI (15 minutes)
  • Structured vs. Unstructured Data - Theoretical
  • Importance of Labelled Training Data - Theoretical
  • Data Quality and Its Impact on AI Performance - Theoretical
 

GenAI as a partner for thought 

  • LLMs as partners for thought - Theoretical
  • Writing - Theoretical/Practical
  • Reading - Theoretical/Practical
  • Chatting - Theoretical/Practical
  • What LLMs can and cannot do - Theoretical

 

Current AI Tools Overview 

  • Applications of Generative AI
  • Tools for Text Generation. - Theoretical
  • Tools for Image Generation - Theoretical
  • Tools for Audio and Video Generation - Theoretical
  • Tools for Code Generation - Theoretical
  • Strengths and weaknesses of each tool. - Theoretical
  • Interactive Q&A session. - Theoretical

 

Prompt Engineering for Generative AI 

  • What Is a Prompt? - Theoretical
  • What Is Prompt Engineering? - Theoretical
  • Best Practices for Prompt Creation - Theoretical/Practical
  • Common Prompt Engineering Tools - Theoretical
  • Text-to-Text Prompt Techniques - Theoretical/Practical
  • Interview Pattern Approach - Theoretical/Practical
  • Chain-of-Thought Approach - Theoretical/Practical
  • Tree-of-Thought Approach - Theoretical/Practical 

 

Generative AI Security

  • Concerns about AI - Theoretical
  • Responsible AI - Theoretical

 

Q&A and Wrap-Up 

  • Open floor for questions.
  • Recap of key points.