Prompt Engineering · The Multiverse School

What You'll Learn

Prompt Engineering is a cutting-edge course designed for those who wish to master the art of interacting with and manipulating large language models. Through a series of workshops, participants will learn to create complex prompts, develop benchmarks, jailbreak models, automate conversations, and much more. The course emphasizes practical skills alongside theoretical knowledge, preparing students for advanced applications in AI.

Develop complex prompts and rubrics for AI artifacts
Benchmark testing for prompts and templates
Techniques for 'jailbreaking' large language models
Automating and hosting conversations with AI
Using no-code tools for AI automation and scheduling
Coding alongside large language models
Running open source large language models
Aligning AI outputs to human values
Creating metalanguages for symbolic reasoning and narrative design

Course Schedule

7Weeks

21Classroom Hours

Week 1

Complex Prompts

Tuesday, September 23 at 5:00 PM - 6:30 PM PDT

Build powerful, flexible prompt structures

1.5h

Week 1

Complex Prompts

Thursday, September 25 at 5:00 PM - 6:30 PM PDT

Build powerful, flexible prompt structures

1.5h

Week 2

Benchmarks & Meta-languages

Tuesday, September 30 at 5:00 PM - 6:30 PM PDT

Evaluate prompts with symbolic reasoning

1.5h

Week 2

Benchmarks & Meta-languages

Thursday, October 02 at 5:00 PM - 6:30 PM PDT

Evaluate prompts with symbolic reasoning

1.5h

Week 3

Model Context & Tools

Tuesday, October 07 at 5:00 PM - 6:30 PM PDT

Custom tools and model integration

1.5h

Week 3

Model Context & Tools

Thursday, October 09 at 5:00 PM - 6:30 PM PDT

Custom tools and model integration

1.5h

Week 4

Scheduling & File Access

Tuesday, October 14 at 5:00 PM - 6:30 PM PDT

Automate triggers and file operations

1.5h

Week 4

Scheduling & File Access

Thursday, October 16 at 5:00 PM - 6:30 PM PDT

Automate triggers and file operations

1.5h

Week 5

Simple RAG

Tuesday, October 21 at 5:00 PM - 6:30 PM PDT

Basic retrieval-enhanced agent design

1.5h

Week 5

Simple RAG

Thursday, October 23 at 5:00 PM - 6:30 PM PDT

Basic retrieval-enhanced agent design

1.5h

Week 6

Advanced RAG

Tuesday, October 28 at 5:00 PM - 6:30 PM PDT

Sophisticated retrieval with evaluation layers

1.5h

Week 6

Advanced RAG

Thursday, October 30 at 5:00 PM - 6:30 PM PDT

Sophisticated retrieval with evaluation layers

1.5h

Week 7

Jailbreaking

Tuesday, November 04 at 5:00 PM - 6:30 PM PST

Break alignment with red-teaming

1.5h

Week 7

Jailbreaking

Thursday, November 06 at 5:00 PM - 6:30 PM PST

Break alignment with red-teaming

1.5h

All times shown in Pacific Time

Who Is This Course For

Professionals and enthusiasts with a foundational understanding of large language models looking to expand their skill set in prompt engineering and AI interaction.

Who this is for & what you'll need

Solo coding

You should be able to write in some language on your own.

Strong computer or subscription

Use your own capable machine, or a paid hosted option below.

On your own machine

Install LocalLM and run open-source LLMs locally (for those with the hardware).

Or use the hosted option

Or use Google Colab (Oobabooga) / OpenAI API.

Where This Class Leads

What you leave able to do

govern a swarm by information hierarchy
reconcile a working set with the context window it must fit
synthesise a long work that stays consistent across many generations
synthesise a memory hierarchy for an agent
synthesise a metalanguage for a problem domain
synthesise a self extending agent behind a review gate
synthesise an agent that carries notes across its own runs

How you show it. Paired runs of the same multi-step task with the note store kept and cleared, where the cleared run repeats a step the noted run skips, plus the note text the agent wrote and the later turn that cites it.

It sits on one path

Build production AI systems from prompt to deployment.7 of 12 after Intro to Agents · before RAG & Memory

About 101 hours of practice sit behind this one. See what your hours buy.

Join the Course

Pay what you can - accessible learning for all

The minimum is $300, it keeps out spam. Need a larger discount? Apply for a scholarship. We offer 100% scholarships, no one is turned away for lack of funds.

Suggested $600 pay what you can

Suggested price • Pay what you can

Industry mentors
Participate in active research projects
Networking events
Integrate AI into your workflow from the beginning
Please self-select into this tier- if you need it, use it

Pay What You Can

Secure payment via Stripe

Suggested $1200 pay what you can

Suggested price • Pay what you can

Industry mentors
Participate in active research projects
Networking events
Integrate AI into your workflow from the beginning
Help pay for underrepresented folks in tech!

Pay What You Can

Secure payment via Stripe

Instructor

Liz Howard

Future Infinitive☸️ (Liz Howard) Founder & Professor, The Multiverse School Computer Science · AI · Cybersecurity Formerly faculty, Cal State Monterey Bay Co-founder, Hipcamp Previously built Hackbright Academy, Girl Develop It, Galvanize, Enki

GitHub LinkedIn Website

Frequently Asked Questions

How are classes delivered?

All classes are live and online via video call. Sessions are recorded so you can review them later if you miss one.

What does "pay what you can" mean?

We show a suggested price, but you can pay any amount. If you need a larger discount, apply for a scholarship, we offer 100% scholarships and no one is turned away for lack of funds.

Do I need prior experience?

Solo coding. You should be able to write in some language on your own.

What do I get when I enroll?

Live sessions with the instructor, access to course curriculum materials, community access via our Matrix chat server, and recordings of all sessions.

Want to schedule this course for your team?

Contact us: [email protected]