Master the Art of Prompt Engineering

Course Info

Length: 1 Week

Type: In Classroom

Available Dates

Venue

  • Dec-30-2024

    Barcelona

  • Jan-27-2025

    London

  • Jan-27-2025

    Dubai

  • Mar-03-2025

    Singapore

  • Mar-03-2025

    Istanbul

  • Mar-03-2025

    Paris

  • Mar-03-2025

    Kuala Lumpur

  • Mar-03-2025

    Barcelona

  • Mar-03-2025

    Amsterdam

  • Apr-21-2025

    London

  • Apr-21-2025

    Dubai

  • June-02-2025

    Barcelona

  • June-02-2025

    Paris

  • June-02-2025

    Istanbul

  • June-02-2025

    Amsterdam

  • June-02-2025

    Kuala Lumpur

  • June-02-2025

    Singapore

  • June-16-2025

    Dubai

  • June-16-2025

    London

  • July-28-2025

    Dubai

  • July-28-2025

    London

  • Sep-01-2025

    Paris

  • Sep-01-2025

    Kuala Lumpur

  • Sep-01-2025

    Singapore

  • Sep-01-2025

    Istanbul

  • Sep-01-2025

    Amsterdam

  • Sep-01-2025

    Barcelona

  • Sep-29-2025

    Dubai

  • Sep-29-2025

    London

  • Nov-24-2025

    Dubai

  • Nov-24-2025

    London

  • Dec-01-2025

    Barcelona

  • Dec-01-2025

    Paris

  • Dec-01-2025

    Singapore

  • Dec-01-2025

    Istanbul

  • Dec-01-2025

    Kuala Lumpur

  • Dec-01-2025

    Amsterdam

Course Details

Course Outline

5 days course

Foundation of Large Language Models (LLMs)

 

  • Understanding LLMs concepts and its applications
  • Identifying LLMS types:


  •      Autoregressive language models
  •      Transformer-based models
  •      Encoder-decoder models
  •      Pre-trained and fine-tuned models
  •      Multi-language models
  •      Hybrid models


  • Understanding LLMS training process:


  •       Pre-training
  •       Fine-tuning


  • Exploring LLM frameworks:


  •         Open AI’s GPT
  •          BERT


  • Navigating LLMs Issues:


  •     Confabulation
  •     Hallucination

Introduction to Prompt Engineering

 

  • Defining prompt engineering and prompts
  • Role of prompts in AI
  • Identifying prompts key elements:

  •      Instructions
  •      Context
  •      Input data
  •      Output indicators


  • Exploring prompt patterns:


  •      Persona Pattern
  •      Audience Persona Pattern
  •      Flipped Interaction Pattern
  •      Question Refinement Pattern
  •      Cognitive Verifier Pattern


  • Types of Prompts
  •      Zero-shot prompting
  •      Few-shot prompting
  •      Multi-shot prompting

Master Prompts Design

 

  • Characteristics of effective prompts
  • Utilizing prompting principles for effective prompts
  • Setting metrics for prompt performance evaluation
  • Prompts parameters adjustment for effective prompts
  • Strategies to control model outputs and reduce repetition

Advanced Prompt Techniques

 

  • Utilizing prompts recipes for reusable AI prompts
  • Implementing Semantic Embeddings & Fine-Tuning techniques
  • Understanding Chain of Thought Prompting
  • Utilizing Generated Knowledge Prompting
  • Applying Self-Consistency Prompting
  • Utilizing Reflexion and Tree of Thought approaches to problem-solving

Prompts Engineering Applications & Future Trends

 

Diving into prompts applications:

 

  • Content generation
  • Code generation
  • Summarization
  • Contextual question and answer
  • Discussing ethical consideration in prompt engineering
  • Learn debugging and troubleshooting in prompts engineers
  • Project: Applying newfound skills to design a prompt
  • Recap and Q&A