Introduction to Prompt Engineering

Exploring the power and capabilities of ChatGPT using Prompt Engineering

Duration

2 Days (8 hours per day)

Level

Basic Level

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As per your team needs

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In this course, participants will delve into the intricacies of Prompt Engineering, with a focus on practical applications such as using API calls. From setting up authentication and API keys to making basic text-generation requests, students will gain hands-on experience in manipulating prompts effectively. Additionally, they will explore advanced parameters like temperature and max tokens to refine their text generation skills. By the end of the course, participants will have a comprehensive understanding of Prompt Engineering, bolstered by real-world project experience to further solidify their learning.

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Developers curious about the art of shaping AI-generated content.
Students eager to bridge theory and practice in the realm of prompt engineering.
Professionals looking to leverage ChatGPT to boost their productivity.
Anyone intrigued by the limitless possibilities of language models and their creative potential.

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Introduction to Generative AI for Prompt Engineering

Generative AI Overview
Working on Generative AI
Introduction to Large Language Models (LLMs)
LLM Architecture
LLMs and Gen AI Real-Life use cases
Ways to Customize Large Language Models

Introduction to Prompt Engineering

Overview of Prompt Engineering
Real-world applications and examples
Setting up an Account for using ChatGPT
Key Elements of Prompt Engineering
Good Prompts vs Bad Prompts
Tips for designing single-stage Prompts
Designing effective multistage prompts
Implementing iterative refinement processes
Integrating feedback loops into multistage prompts

OpenAI API Calls

Setting up authentication and API keys
Making basic text-generation requests
Handling advanced parameters such as temperature and max tokens

Summarizing, Inferring, and Transforming Text

Techniques for summarization (extractive vs. abstractive)
Evaluating the quality of summaries
Data preprocessing techniques for text
Paraphrasing and text expansion methods
Implementing text transformation techniques

Prompt-Based Learning Strategies

Zero-shot Prompt Engineering
Few-shot Prompt Engineering
Consistency over Time (COT)
Self-consistency
Generate Knowledge Prompting (GKP)
Test of Time (TOT) Prompt Engineering
Adaptive Prompting
Template-Based Approach Prompting

Structured Prompting Strategies

Interview Pattern Approach
Chain-of-Thought Approach
Tree-of-Thought Approach

Prompt Engineering for Images

Importance of Prompt Engineering for Images
Basic Elements of Prompts
Subject, Background, and Text
Adding Style & Compositions
Lighting & Shadows
Emotions & Atmosphere
Colors & Textures

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It is important to know some fundamentals of programming, like API calls, etc
A basic understanding of ChatGPT will be helpful.

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Introduction to Prompt Engineering

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