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Prompt Engineering and Generative AI

Navigating the Landscape of Prompt Engineering: Practical Insights and Techniques”


This course is designed to provide participants with comprehensive knowledge and practical skills in utilizing prompt engineering techniques and generative artificial intelligence (AI) models. This course is ideal for individuals interested in understanding how to harness the power of AI to generate creative and meaningful content across various domains.

Course Outline

MODULE 1: Introduction to Prompt Engineering and Generative AI (Weeks 1-2) 

Session 1-2: Overview of Natural Language Processing 

  • Introduction to NLP
  • Key Terminology
  • Applications of NLP in AI 

Session 3-4: Introduction to Prompt Engineering and Basics of Generative AI Models 

  • What is Prompt Engineering? 
    Fundamentals of Generative AI
  • Overview of Common Generative Models 


  • Quiz on NLP concepts and basics of prompt engineering. 

MODULE 2: Fundamentals of Prompt Design (Weeks 3-4) 

Session 5-6: Principles of Effective Prompt Engineering 

  • Role of Prompts in Language Models 
  • Understanding Task-specific Requirements 

Session 7-8: Types of Prompts for Different Tasks 

  • Classification Prompts 
  • Generation Prompts 
  • Practical Exercise: Creating and Testing Prompts 


  • Submission and evaluation of prompt design exercise. 

MODULE 3: Advanced Generative AI Models (Weeks 5-6) 

Session 9-10: Transformer Architectures 

  • Understanding Transformer Models 
    Attention Mechanism 
  • Case Studies: Applications of Advanced Generative Models


  • Short project: Implementing a generative model using advanced architectures. 

MODULE 4: Fine-tuning Models for Specific Tasks (Weeks 7-8) 

Session 11-12: Transfer Learning in Generative AI 

  • Basics of Transfer Learning
  • Adapting Pre-trained Models for Specific Tasks 

Session 13-14: Techniques for Fine-tuning Pre-trained Models 

  • Fine-tuning Strategies 
  • Practical Exercise: Fine-tuning a Model for a Custom Task 


  • Evaluation of the fine-tuning exercise. 

MODULE 5: Ethical Considerations and Bias in Prompt Engineering (Weeks 9-10) 

Session 15-16: Understanding Ethical Issues in AI 

  • Overview of AI Ethics
  • Responsible AI Practices 


  • Reflection assignment on ethical considerations in prompt engineering. 

MODULE 6: Real-world Applications and Case Studies (Weeks 11-12) 

Session 17-18: Industry Applications of Prompt Engineering 

  • Use Cases in Different Industries 
    Success Stories and Challenges 

Session 19-20: Group Project: Solving a Real-world Problem using Prompt Engineering 

  • Forming groups and selecting projects 
    Implementation and Presentation of Group Projects 


  • Evaluation of the group project and individual contributions. 

Case Studies

Sentiment Analysis in Customer Reviews  

  • Applying prompt engineering to analyze sentiment in diverse datasets. 

Customizing Chatbot Responses  

  • Fine-tuning language models for personalized chatbot interactions.

Bias Detection and Mitigation  

  • Investigating and addressing biases in generative AI models. 

Domain-specific Language Generation  

  • Adapting models for industry-specific language generation tasks. 

Course Highlights

1. Comprehensive Understanding: Start with an NLP overview, then advance to prompt design and generative model architectures for a thorough grasp of prompt engineering and generative AI.

2. Hands-on Learning: Develop practical skills by crafting effective prompts, exploring various types, and fine-tuning models using transfer learning for specific tasks.

3. Cutting-edge AI: Explore transformer architectures’ role in generative AI, gaining insights into the latest advancements shaping the field.

4. Ethical Insight: Delve into ethical considerations and biases in prompt engineering, fostering responsible AI practices and ethical decision-making.

5. Real-world Application: Apply knowledge to real-world scenarios through industry case studies and a group project, solving problems using prompt engineering techniques.

Contact Us

PPIC Technologies Pte Ltd

Contact Number +6591792003

Contact Email:  admin@ppictech.com


9 North Bouna Vista Drive #02-01 Metropolis Tower 1, Singapore 138588


Prompt Engineering and Generative AI

Duration: 40 hours (10 sessions, 4 hours per session) 

231 Mountbatten Road
Mountbatten Centre, Block B #02-01
Singapore 397999

Course Fee
$1,380.00 / $1,504.20 (with GST)

Nett Fee after 50% funding: $814.20

Nett Fee after 70% funding: $538.20

Who Should Attend?

This course is ideal for business managers, IT professionals, executives, and anyone interested in gaining practical skills and insights into prompt engineering and generative AI. No programming experience or expertise required.

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Funding Information

  • WSQ Funding Up to 50% for < 40 yrs old SC/PR/LTVP+
  • Enhanced Funding – MCES/SME (Up to 70% >40 yrs old SC)
  • SkillsFuture Mid-Career Enhanced Subsidy (MCES)
  • More details on funding at tpgateway.gov.sg
  • Eligible Singapore Citizens can use their Skillsfuture Credit or PSEA to offset course fees payable after funding
  • Funding Validity period: 7 Dec 2023 – 5 Dec 2025
  • TGS-2023040639