1-Week Course
Using Large Language Models
03.26.24 - 03.28.24 1 weeks live & online, 4.5 hours in class
Empower your decisions and creativity with AI, no tech background required.
with Liz Howard
What You'll Learn
"Using Large Language Models" is an engaging course designed to introduce a wide audience to the transformative potential of AI technologies, such as ChatGPT, without requiring prior technical expertise. Participants will explore the practical applications of these models in enhancing decision-making, creativity, and productivity in various settings. The course offers hands-on experience in customizing AI tools for real-world challenges, aiming to provide a deep understanding of both the opportunities and the critical considerations of employing large language models in personal and professional domains.
- **Emotional Priming**: Enhance output quality - **Structured Notes**: From vocal to formal - **Brainstorming Aid**: Ideate with AI - **Data Structuring**: Unstructured to organized - **Summarize Documents**: Condense lengthy texts - **First-Pass Editing**: AI-assisted editing - **Token Recognition**: Understand inference roles - **Model Comparison**: Differentiate AI models - **Limitation Awareness**: Acknowledge AI biases - **Hyperparameter Tuning**: Customize output - **System Prompts**: Set preferences easily - **Data Analysis**: Simplify complex analysis - **Plan Critique**: Evaluate and improve - **Language Efficacy**: Sharpen prompt performance - **Sparse Priming**: Knowledge decomposition - **Value Alignment**: Reflect human ethics - **Thought Chains**: Enhance reasoning - **Critical Skills**: Boost output reliability - **Rubric Creation**: Guide AI responses - **Expert Reviewers**: Refine AI output - **Prompt Optimization**: Expert-level prompts
Course Schedule
Effective Use of Large Language Models as Assistants
Tuesday, March 26 at 5:00 PM - 6:30 PM PDTThis workshop covers practical applications of large language models for tasks such as emotional priming, brainstorming, and summarizing documents. Participants will learn the differences between market and open-source models, the role of tokens in inference, and how to use effective language in prompts to improve performance.
Effective Use of Large Language Models in Analysis and Critique
Wednesday, March 27 at 5:00 PM - 6:30 PM PDTThis session focuses on utilizing large language models for editing, data structuring, and understanding model limitations and biases. Participants will learn to configure inference outputs using hyperparameters, apply Chain of Thought for better reasoning, and use models to analyze data and critique plans. System Prompts customization and knowledge decomposition techniques will also be covered.
Effective and Ethical Use of Large Language Models
Thursday, March 28 at 5:00 PM - 6:30 PM PDTThe final workshop session emphasizes ethical considerations and the alignment of model outputs with human values. Participants will explore the use of Critical Theory, Reflection, and Metacognitive skills to enhance model reliability and quality. The session also covers creating a rubric for language models, using the Expert Reviewers strategy for model evaluation, and optimizing prompts to mirror expert-level queries.
All times shown in Pacific Time
Who Is This Course For
This course is tailored for a broad audience, including managers, product professionals, executives, and technically inclined individuals. It focuses on the applications of ChatGPT and other large language models for non-technical users, showcasing how these technologies can enhance decision-making, creativity, and productivity across various domains. No prior technical skills or knowledge of machine learning are required, making it accessible to anyone interested in leveraging the power of AI to achieve their goals.
Who this is for & what you'll need
No code
The AI writes any code. You'll never touch a terminal.
Any computer
Just a web browser, nothing to install.
Where This Class Leads
What you leave able to do
- generalise several sources into a position you can defend
- parameterise an agent persona
- verify synthetic data preserves the property you need
- construct a predictive account of a model's behaviour
- design an interaction protocol for responsible use
- reconcile a working set with the context window it must fit
- synthesise a metalanguage for a problem domain
How you show it. The notation's grammar, a work produced in it that exceeds the context window, and a consistency check a reader runs to catch contradictions.
It sits on one path
The AI Builder1 of 12 before Control AI SpendingAbout 26 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 $20, 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 price • Pay what you can
Secure payment via Stripe
Suggested price • Pay what you can
Secure payment via Stripe
No sponsored scholarship seats are open in this class yet.
What each price funds for someone else:
- $40 (Underrepresented in Tech Scholarship) · funds 1 scholarship seat
- $60 (Full Price) · funds 2.0 scholarship seats
Instructor
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. The minimum is $20, which keeps out spam. If that's out of reach, apply for a scholarship, we offer 100% scholarships and no one is turned away for lack of funds.
Do I need prior experience?
No code. The AI writes any code. You'll never touch a terminal.
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]