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Hands-on Prompt Engineering

Published by O'Reilly Media, Inc.

Beginner to intermediate content levelBeginner to intermediate

Improve content creation, automate development tasks, and generate insightful data analysis

Course outcomes

  • Learn prompt engineering for diverse tasks such as summarization, text extraction, code generation, and debugging
  • Explore advanced prompting techniques such as zero-shot, few-shot, and chain-of-thought prompting
  • Use the OpenAI Playground to work with Chat Completions and Assistants APIs

Course description

Join expert Janani Ravi to explore the world of AI interaction and acquire the skills to effectively leverage advanced AI models. You’ll understand the fundamentals of large language models, study the anatomy of a prompt, and learn the nuances of crafting prompts for summarization, classification, text extraction, question answering, and data and code generation. You’ll also explore advanced prompting techniques, including zero-shot, few-shot, and chain-of-thought prompting, as well as generated knowledge prompting and image interpretation through prompts. You’ll get a taste of how prompt responses can be tweaked using the OpenAI Playground where you’ll use the Chat Completions and Chat Assistants APIs without writing a single line of code.

What you’ll learn and how you can apply it

  • Learn the fundamentals of generative AI and large language models
  • Master prompting techniques for a variety of tasks such as summarization, content writing, text extraction, question-answering
  • Improve the responses from generative AI models by tailoring prompts
  • Use advanced prompting techniques such as zero-shot, few-shot, chain-of-thought, and augmented knowledge prompting
  • Leverage OpenAI APIs without writing code

This live event is for you because...

  • You work with technologies like SQL, Python, and Java and would like to learn how prompting can help you work more effectively.
  • You’re a busy professional in any field who’d like to learn how to use generative AI for day-to-day tasks such as writing emails, creating content, or parsing resumes.
  • You’re curious about the capabilities of generative AI models and would like to improve your efficiency at work.

Prerequisites

  • A level of comfort working with technical tools

Recommended preparation:

Recommended follow-up:

Schedule

The time frames are only estimates and may vary according to how the class is progressing.

(break every 60 mins)

Introducing generative AI and LLMs (30 minutes)

  • Presentation: Generative models and discriminative models, Introducing generative AI and LLMs; overview of attention and transformers that power generative models; benefits, limitations, and biases; ChatGPT, Google Gemini, Meta.ai and Bing Copilot
  • Group discussion: Use cases of generative AI

Hands-on prompting (60 minutes)

  • Presentation: Anatomy of a prompt; Steps involved in writing a good prompt; Prompting best practices
  • Hands-on demos: Structuring prompts, open-ended prompts, providing context; improving model responses;summarization, text extraction, question answering, and classification; email writing, parsing resumes, and technical documentation; writing, grammar, and tone; ideation, role play, and reasoning
  • Group discussion: Prompting in the workplace (safety and security); other prompts that learners have used

Advanced prompting techniques (90 minutes)

  • Hands-on demos: Data generation and code generation prompts; debugging and code explanations; using prompts with SQL, Python, Java; zero-shot and few-shot prompting; chain-of-thought prompting; augmented knowledge prompting; image generation; image interpretation using prompts; graph and chart interpretation; mitigating biases in responses; other use cases of prompting
  • Group discussion: Examples of biases in prompt responses, seeking prompts from learners

OpenAI Playground (60 minutes)

  • Presentation and hands-on demos: Chat completions and legacy completions; control responses using parameters (configuring models, temperature, max-tokens, stop sequence, stop-probability scores, frequency and presence penalty); data analysis and retrieval with assistants
  • Group discussion: Use cases of prompting

Your Instructor

  • Janani Ravi

    Janani Ravi is cofounder of Loonycorn, a team dedicated to upskilling IT professionals. She’s been involved in more than 100 online courses in data analytics, feature engineering, and machine learning. Previously, Janani worked at Google, Flipkart, and Microsoft. She completed her studies at Stanford.

Skill covered

Prompt Engineering