Prompt Engineering for Developers
Learn the most important prompting techniques and best practices for building effective LLM applications.
Setting up Environment
Getting Started
Quiz
Write Clear Instructions
Role Prompting & Delimeters
Step-by-Step Prompting
Providing Examples & Specifying Output Length
Providing Reference Text
Splitting Complex Tasks
Time to Think
Chaining Queries
Zero-shot Prompting
Few-shot Prompting
Few-shot Prompt Template
Evaluating Few-Shot Prompts
LLM-as-a-Judge
Exercise
Chain-of-thought Prompting
Inner Monologue & Testing CoT
Discussion: Automatic CoT vs. Manual CoT
Exercise
Prompt Chaining Overview
Applied Prompt Chaining
Exercise
PAL Overview
Exercise
Function Calling Overview
Advanced Function Calling Tips
Exercise
Applying Function Calling to a Chat App
Exercise
OVERVIEW
Prompt Engineering for Developers is a course focused on learning how to design and optimize prompts for LLMs with the latest prompting techniques and methods.
After completing this course, students will know how to apply the best practices and prompting techniques to help them build more effective, efficient, and robust LLM applications and agents.
PREREQUISITES
This course leverages the Python programming language so it requires basic knowledge of Python. We primarily use the OpenAI SDK so you are required to have a paid developer account with OpenAI (any tier should work).
TOPICS
Throughout the course, students will use Python to apply best practices for prompting LLMs, including:
FREE LECTURE PREVIEW
Here's a subset of companies whose employees have benefitted from our courses:
Accrete, Airbnb, Alston & Bird, Amazon, Apple, Arm, Asana, Bank of America, Belong For Me, Biogen, Brilliant, Carebound, CDM, CentralReach, Centric Software, Chime, Coinbase, Digital Green, DoHQ, Elekta, Fidelity Investments, Fivecast, Fulcrum Labs, Google, Guru, Gretel, Harrison Insights, Intel, Intuit, Jina AI, JPMorgan Chase & Co, Khan Academy, KnowBe4, Lawyer.com, LinkedIn, LionSentry, MagmaLabs, MasterClass, Meta, Metopio, Microsoft, Moneta Health, Oracle, OpenAI, Rechat AI, RingCentral, Salesforce, Scale AI, Scribd, Space-O Technologies, Sun Life, TD Bank, TELUS Corporations, Trilogy, TTEC Digital, UniCredit, VaxCalc Labs, Vendr, Walmart, Wolfram Alpha, Zemoso Technologies, Zeplin
Reach out to [email protected] for any questions and team/student discounts.
Learn how to build agentic workflows powered by LLMs.
Learn how to build effective and modern Retrieval Augmented Generation (RAG) systems.
Learn important prompt engineering techniques to build use cases with LLMs.
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