Mark Kim-Huang

AI Agents & Multimodal LLMs

Co-Founder & Chief Architect at Gradient

Determine when you should consider using adapted models for table reasoning, pdf parsing or sentiment analysis.

Why and When to Use Task Adapted Models

Use low code APIs to train a base model for a specific task.

Fine-tune LLMs for Task Adaptation

Learn about how task-adapted LLMs can help move your business closer towards deploying autonomous assistants.

How to Shift Towards Agentic Workflows

Welcome to today's most technically rigorous and hands-on Large Language Model (LLM) application course. This course is unique because each class is taught online and held with separate office hours - in total, we will conduct 15 sessions. Most courses are taught asynchronously, i.e., recorded sessions with Q&amp;A. We believe you should get what you pay for. There are 7 - 2 hr sessions for teaching and 7 office hours—1 session for DEMO DAY. We have increased our cohort to 10 weeks to allow you to learn and implement your projects thoroughly. This isn't just another AI course – it's your gateway to mastering the art and science of deploying production-grade LLM solutions that stand out in the real world. As part of Maven's Top-Rated Content, this course is designed for those who have already mastered the basics of RAG, cosine similarity, vector databases, and LLMs. We'll take you to the next level, focusing on practical aspects of packaging and deploying these models in real-world production environments. For cohort members joining this intensive learning experience, here's what you get: - 10 weeks of in-depth content in-person courses - We will teach you each class- Weekly office hours for personalized guidance- Real-world projects and challenging assignments- Guest Lectures by Leading AI Professionals- Continued support post-graduation- Lifetime access to course materials What You'll Master: Course Highlights Agents: Forget CrewAI or Autogen, build your won Agents from scratch. Learn what it takes to make an Agent from the ground. Contribute to Open Source community. Advanced RAG Solutions: Dive into enterprise-level RAG architectures and learn how to build and implement semantic caching from scratch using GCP and Redis. LLM Hosting and Deployment: Gain insights into best practices for hosting Large Language Models (LLMs) in diverse production settings, creating inference endpoints, and deploying LLMs on serverless platforms. Continual Pre-Training and Fine-Tuning: Explore advanced techniques for continual pre-training, fine-tuning LLMs, and mitigating catastrophic forgetting. Learn how to build a data pipeline for pre-training, apply causal language modeling, and leverage scaling laws. Model Merging and Mixture of Experts: Master techniques for merging multiple models to enhance their collective capabilities, including the Mixture of Experts (MoE) approach. Learn to use tools like mergekit for efficient model merging. Quantization Methods: Discover techniques to reduce model size while maintaining performance, crucial for deployment in resource-constrained environments. Inference Speed Optimization: Learn strategies to accelerate inference speeds for real-time language processing, ensuring efficient and responsive AI systems. Responsible AI Implementation: Explore ethical AI development using guardrails like NeMo, Colang, and Llama Guard to ensure AI systems align with responsible AI principles. Agentic RAG and Chunking Strategies: Implement advanced semantic chunking techniques and explore AI agent frameworks like AutoGen to enhance the capabilities of RAG systems. DSPy and Knowledge Graphs: Learn to create and utilize knowledge graphs effectively, mastering DSPy as an alternative prompting approach for structured data handling and enhanced AI interaction. Throughout the course, we will analyze state-of-the-art AI products, reverse-engineering some through Python. As a bonus, you'll have access to experimental products being developed at Traversaal.ai, my startup, allowing you to stay at the forefront of advancements in the field. Prerequisite: You should have coding experience of building RAG Solution. Understanding of Encoders and Decoders and some knowledge of Cloud Solutions and APIs. If you feel the need for a more foundational course, consider checking out my other offering on LLMs: Building LLM Applications (https://maven.com/boring-bot/ml-system-design).

Go Beyond Basic Frameworks: Build and Deploy Production-Grade AI Solutions

Provide a brief description for each module as a way to sell the value of what students will be learning throughout the course.

First Module

Second Module

Third Module

Course syllabus

Sundays

Work in teams to build solutions, this requires engagement with other team members

Weekly projects

Course schedule

Machine Learning Engineer exploring different techniques to scale LLM solutions

Researcher, who would like to delve in to various aspects of open-source LLMs

Software Engineer, looking to learn how to integrate AI into their products

This course is for you if you are a:

What you’ll get out of this course

Understand and implement complex AI architectures, including enterprise-level RAG systems and agentic RAG strategies. You will also dive deep into the Mixture of Experts (MoE) technique and other model merging strategies to enhance the capabilities of your AI systems.

Advanced AI Architectures

From building semantic caches using GCP and Redis to deploying LLMs on serverless platforms like AWS Bedrock, you'll learn the practical skills to deploy and manage AI applications in real-world scenarios.&nbsp;

Practical Skills for Deployment

Acquire advanced techniques for fine-tuning LLMs, enabling you to adapt these models to specific tasks or domains and enhance their performance in targeted applications.

Fine-Tuning Expertise

Explore strategies for exploring and optimizing inference speeds, ensuring that your language models perform efficiently in real-time scenarios, a crucial skill for deploying responsive and scalable applications.

Efficient Inference Processing

Understand the importance of ethical AI development and learn to implement guardrails using tools like NeMo, Colang, and Llama Guard to ensure your AI systems align with responsible AI principles.

Knowledge of Responsible AI

Build and Optimize Production-Grade RAG and LLM Applications: Master Advanced Techniques for Scalable, Secure, and Low-Latency AI Solutions

Hamza Farooq

Cohort 4

Cohort 5

"Despite being a student in Harvard’s Master’s in Data Science program, I've struggled to understand the concepts that make LLMs so impressive. This class gave me the answers." - Tony "Ishan takes a black box, rips it apart to understandable compartments, and clearly communicates what is going on. Highly recommend." - Joe, CFO ______________________________________________________________________ The current cohort completed recording on January 17th, 2025 but you can still enroll to participate asynchronously: •&nbsp;Get lifetime access to all recorded sessions, including interactive Q&amp;A segments•&nbsp;Connect with peers in our dedicated private Discord community•&nbsp;Master the material through comprehensive quizzes and training resources•&nbsp;Receive direct instructor support via email or Discord whenever you need help•&nbsp;The option to attend a future live cohort for free______________________________________________________________________ Why This Course Stands Out: You already know how vital AI is to your career—it's in every conversation, project, and strategy session. But diving into AI feels daunting with limited time for self-study or complex programming. That’s where this course comes in. Skip the endless prep work and gain an intuitive, hands-on understanding of AI and transformers in just a few hours—without needing an advanced degree. No other course offers such an interactive, fast, and in-depth technical understanding of AI using an actual GPT-2 model, all using an easy-to-learn spreadsheet interface. ______________________________________________________________________ Perfect for Busy STEM Professionals:Whether you're a developer, technical manager, or executive, this course demystifies AI and teaches you exactly how Large Language Models (LLMs) like GPT-2 work, with no prerequisites beyond a STEM background. It’s ideal for: • Software/Web Developers seeking an easy introduction to machine learning. • Science &amp; Tech Professionals navigating AI transformations in their fields. • Technical Sales/Marketing crafting messaging for AI products. • Product/Project Managers overseeing LLM-powered solutions. • Executives/Leaders guiding AI strategy in their organizations. ______________________________________________________________________ What You’ll Learn:Using a unique spreadsheet implementation of GPT-2 (the predecessor to ChatGPT), we’ll break down each model component with crystal-clear explanations. In just a few sessions, you’ll be able to: • Understand how LLMs work—as quickly as possible. • Explain every key component—tokenization, embeddings, attention, and more. • Gain AI literacy—so you can confidently lead and manage AI-driven teams. • Build a foundation for further AI projects—and even more advanced learning. ______________________________________________________________________ Why Spreadsheets?You don’t need to be a coder or a calculus expert to understand AI—just the right approach. This course uses an innovative, no-code, spreadsheet-based method to teach LLMs. It's fast, interactive, and designed for busy professionals like you. By breaking down complex AI principles into easy-to-follow spreadsheet exercises, you’ll gain a lasting, foundational understanding of how large language models work. This is knowledge you can carry across into any model, any programming language, and any project. ______________________________________________________________________ Hands-On Learning, No Programming Required: By the end of the course, you’ll have a working, detailed understanding of how transformers power LLMs like ChatGPT, Claude, and Llama. Plus, you'll have a spreadsheet tool you can explore and tweak to deepen your understanding further. ______________________________________________________________________ See it for Yourself: Still unsure? Watch the FREE lightning lesson:"Inside the Brain of an LLM: How it Works in 30 Minutes" to see how accessible AI learning can be: https://maven.com/p/eeea6f/inside-the-brain-of-an-llm-how-it-works-in-30-minutes ______________________________________________________________________ Join the Community of Learners: • “I could’ve read 20 papers on this and not gotten nearly the understanding I got from this hands-on course.”— Class Participant from Adobe • “Highly recommend this course for anyone wanting to build a foundation in LLMs. Ishan’s interactive approach makes complex concepts incredibly clear.”— Matt, Business Intelligence Analyst ______________________________________________________________________ Practical Details: • Course Access: All sessions are recorded and available to stream after the course concludes, so you’ll never miss a thing.• Reimbursement: Your company may cover this course if you're building or transitioning into AI at work. ______________________________________________________________________ New for this cohort! We've dropped the requirement for Excel. We have a browser based alternative. Some exercises may use Google Sheets and/or Python.

Skip the mountains of prep work and learn how AI works in just a few hours

If your events are recurring and at the same time, it might be easiest to use a single line item to communicate your course schedule to students

Tuesdays & Thursdays

Feel free to type out dates as your title as a way to communicate information about specific live sessions or other events.

May 7, 2022

Schedule items can also be used to convey commitments outside of specific time slots (like weekly projects or daily office hours).

Executives, engineering managers, and product managers leading and coordinating technical AI teams leveraging LLMs

Developers without formal training in machine learning that want to quickly understand the LLM technology in their projects

A gentle introduction to LLMs for professionals pivoting their career to AI from traditional software engineering or other STEM fields

Anyone who can read a spreadsheet that is motivated and deeply interested in how the next wave of computing works

Who is this course for

This course breaks down complex AI concepts into easy-to-follow steps using Excel, making it accessible for anyone with a STEM background.

Understand how LLMs work as quickly as possible

Precisely understand in detail the architecture and function of the GPT2 model, including tokenization, embeddings, attention, multi-layer perceptron, and layernorm.

Recognize and explain every component of an LLM

You'll gain a solid understanding of how LLMs function, enabling you to confidently engage with engineers and technical stakeholders.

AI Literacy for managing technical teams

Build a foundation that equips you with the essential knowledge to explore advanced AI topics, undertake AI projects, or pursue further coursework.

Prepare yourself for further exploration, projects, or coursework in artificial intelligence

Master AI Concepts with a Real LLM Implemented Entirely in a Spreadsheet. No Complex Math. Just Clarity. 

Jan 8—17, 2025

Ishan Anand

December 4-13, 2024

🟢 WHAT WILL I BE ABLE TO BUILD IN THIS COURSE?You’ll build a functional application powered by LLM agents to automate a workflow of your choice. Along the way, you'll learn to design agent workflows, and integrate required tools. By the end of the course, you'll have a working MVP ready to showcase in a public demo. You can see this playlist for examples of what previous students built: https://tinyurl.com/llm-agent-demos 🟢 HOW WILL YOU HELP ME BUILD APPS LIKE THESE IN JUST 7 WEEKS?This course is all about learning by doing. You do a real project, applying concepts you learn about AI agents with our expert guidance. Specifically:👨🏽‍🏫 1:1 sessions with the instructors to help you think through bigger picture questions👨‍🎓 Async and sync sessions with a dedicated TA for constant support, code reviews, and real-time feedback To help you prepare, we have also curated 70+ hours of content, a "Learning Path" covering everything from product design and coding fundamentals to advanced LLM engineering concepts that you can consume at your own pace, as soon as you sign up. (see the next question for details) 🟢 OK! THAT DOES SOUND FUN, BUT HOW DO I KNOW IF I HAVE THE PRE-REQUISITES AND I'M READY FOR BUILDING?That's the most common question we get! The "Learning Path" we have curated should also give you a good sense of what knowledge we assume as pre-reqs. You should get started on that and then sign up for the course as soon as you feel you are ready:https://maven.com/p/bafd83/llm-agents-learning-path 🟢 I SEE! SO, I'LL DO MY PREP BEFOREHAND, THEN WHAT SHOULD I EXPECT TO HAPPEN DURING?Think about it like this (since we're developing a product here, eh?): This is a 3-sprint product dev + 1 week of prep for the public demo.🖌️ SPRINT 1 - DESIGN (weeks 1 &amp; 2)🔨 SPRINT 2 - DEVELOP (weeks 3 &amp; 4)🚢 SPRINT 3 - DEPLOY (weeks 5 &amp; 6)🎭 PUBLIC DEMO (week 7)In each sprint, you communicate your progress or blockers on Slack, you collaborate on your designs / code on GitHub, you show up to provide weekly project updates and get feedback, and finally you do an end of sprint demo. 🟢 OK! HOW WOULD I KNOW IF I'M MOVING IN THE RIGHT DIRECTION?You will get feedback async via Slack and other platforms we use, and also you join weekly group office hours, and when you need you can book the teaching staff for a 20 min 1:1 call. In addition, each sprint will wrap up with a "sprint demo" where you can show what you've done up to that point, and your peers and the teaching staff will provide feedback. We also will invite guest experts for each of the demos to provide additional feedback:🖌️ SPRINT 1 - Sr. AI Product Experts🔨 SPRINT 2 - Sr. ML Engineers🚢 SPRINT 3 - Sr. MLOps Engineers🎭 PUBLIC DEMO - Investors, Experienced Founders, Corporate Directors 🟢 WHAT IF I DON'T HAVE A PROJECT IDEA?We will have a default project (most probably related to automating data science work) that you can participate in. If your goal is to better internalize the concepts rather than working on a specific idea, you can join that project. We commonly see that people re-take the course in the future to further develop specific ideas they have, and focus on building the foundations the first time they take the course. 🟢 COOL! I'M EXCITED TO GET STARTED, AND A DISCOUNT WOULD REALLY SWEETEN THE DEAL!Glad to hear that! There are a few options:🧑🏿‍🤝‍🧑🏼 You can find a buddy or colleague and sign up together. (20% off 2-9 seats&nbsp;|&nbsp;25% off 10+ seats)✴️ We often share discount codes with communities (including AISC members - reach out to community@ai.science if you're not part of our slack). So, check in with the communities you are part of.📆 We regularly hold events and info sessions where we share flash sales discounts valid for a day or two. Join the mailing list on this page to receive notifications about those.👨🏽‍🏫 You can apply to join as a student with additional responsibility and enjoy 50% off. Apply here: https://forms.gle/YnvsoREuEX35DAxv8

Mentorship Program to Help You Build an Agent-based MVP

We will have group discussions and guests lecturers on Thursdays, and project office hours on Sundays.

Thursdays & Sundays

Course will run for 7 weeks in January and February. You will have access to reading / watching material, instructor, and hands-on teaching assistants.

Jan. 13, 2025 - Mar. 1, 2025

There will be a project that you will do alongside the course material with weekly milestones.

You want to build an agentic MVP to demonstrate your skills for career progression purposes.

You want to build an agentic MVP to test the feasibility of your startup idea.

You want to build an agentic MVP to explore the new feature you want to add to your existing product

This course is for you if...

At the end of this course you will ...

Grasp how multiple LLMs can collaborate with each other, get feedback from or assign tasks to humans, ad use tools to tackle complex problems

Understand the core principles of multi-agent LLM systems

Bridge the gap by crafting strategies to seamlessly integrate LLMs with existing products, boosting user experience, productivity, and business metrics.

Integrate LLMs with existing product offerings to enhance user and customer experience

Learn what it takes to build robust multi-agent LLMs. Understand security best practices and ensure system reliability.

Understand key considerations for securing, robust, and reliable LLM systems

Design, develop, deploy, and demo an LLM agent application in 7 weeks!

Cohort-2501

Amir Feizpour, PhD

10 yrs in NLP, Founder of AISC - Community of 5k AI devs and founders

Abhimanyu Anand

Cohort 2409

Cohort-2505

Ready to move from AI uncertainty to AI leadership? In a world where everyone's talking about AI, product &amp; design professionals need to do more than just understand it—they need to master it responsibly. This isn't another theoretical AI course. It's your practical roadmap to becoming the go-to AI product or design leader in your organisation, combining hands-on skills with ethical principles that will set you apart. Why This Course Is Different:While others teach you to use AI tools, we teach you to master AI thinking. Our human-centered learning system doesn't just dump information—it rewires how you work with AI through: - Mental models that make AI decisions intuitive- Micro-habits that make AI integration automatic- Practical workflows that make AI implementation natural- Weekly live sessions that make ethical principles actionable Instead of overwhelming you with AI theory, we build your confidence through: - Practical application in your actual work, starting day one- Real-world case studies, not theoretical scenarios- Active learning through peer discussions and feedback- A proven system for continuous adaptation as AI evolves. Your 6-Week Transformation: Week 1: Understanding the Paradigm Shift to AI-driven worldTransform from wondering about AI's potential to making strategic AI decisions. Build the foundation for responsible AI leadership in your organisation. Live Ethics Session: Intro to AI Ethics &amp; Global Ethical Frameworks Week 2: From AI-User to AI-CommunicatorMaster the art of AI interaction with large-language models while maintaining privacy and trust. Learn to get consistently high-quality outputs that align with your goals. Live Ethics Session: Human Autonomy &amp; Oversight in an AI World Week 3: From Uncertainty to Quality AssuranceStop wondering if AI outputs are reliable. Build robust validation practices that ensure trustworthy results with limited bias every time. Live Ethics Session: Fairness and AI Bias Week 4: From Tool User to Strategic IntegratorLevel up from basic AI usage to strategic implementation. Learn to leverage AI's "collective intelligence" while understanding industry-wide impacts. Live Ethics Session: Building Transparency in AI Systems Week 5: From Single Tools to AI WorkflowsAdvance from using individual AI tools to orchestrating multiple AI capabilities in sophisticated, ethical workflows. Live Ethics Session: Data Protection &amp; Privacy Week 6: From Implementer to AI LeaderEmerge as a responsible AI leader who can drive adoption while ensuring ethical implementation across your organisation. Live Ethics Session: Accountability for AI Implementers The AI landscape is moving faster than you can blink. While others are still debating whether to use AI, you'll be showing them how to use it right. Join progressive product &amp; design leaders from innovative organisations who are transforming their AI approach through this proven methodology. Your Weekly Experience Includes:﻿- Focused e-learning modules that build practical skills- Real-world exercises you can apply immediately in your everyday work- Mental models that transform how you think about AI and makes applying learnings 10x more effective- Micro-habits that make AI integration natural- Live ethical sessions with practical case studies &amp; peer discussions that expand your perspective This course has been designed to reduce the friction of learning to adapt to AI driven ways of work, as well as boosters to accelerate your learning journey. BONUS BOOSTERS- Create Your Personal AI Adoption Blueprint: Giving your a starting point for adapting your ways of working- Create Your AI Writing Partner: A CustomGPT that writes exactly like you (but faster)- Learn a Rapid AI Research &amp; Learning Workflow: Never fall behind on AI developments again- Redesign one of your workflows to be AI+Human collaboration Don't just keep up with AI—learn to lead with it. Join us and become the product or design professional who knows how to harness AI's potential while ensuring it's implemented responsibly. Let's build a future working alongside trustworthy AI we can all be proud of.

Build AI confidence: Responsible implementation for everyday work

Weekly Live Session, where we unpack 1 AI ethical principle using real world case studies and peer to peer discussions.

Wednesdays 

Learning contact time 1 hour self paced lessons + 1.5 hours weekly live session + community engagement. You'll be given practical exercises &amp; micro-habits to apply learnings directly to your AI use in your daily work.

Weekly Time Commitment

Designers, Product Managers responsible for designing and deploying AI Products. You want to scale your impact (without burning out)

Non-technical professional who want to learn AI, without being overwhelmed with technical jargon

Founders, executives &amp; managers who are responsible for AI product success and risk management

Without the right mental models, applying skills you learn is exponentially harder.

Learn new mental models essential for effective Generative AI use

Understanding AI's underlying capabilities helps you use it effectively, spot opportunities in various contexts, and solve specific problems. This knowledge empowers you to leverage AI optimally across different situations.

Learn AI capabilities without the tech jargon

Getting the best out of Large language models like ChatGPT &amp; Claude requires a clear set of instructions and all the necessary context to do a good job. Learn memorable techniques that will rapidly improve your prompting and the quality of AI outputs.

Master your communication with Generative AI system like ChatGPT

Learn practical skills in spot bias and fact-check output from large language models to reduce risk of inaccuracies or hallucinations.

Gain practical skills to critically assess AI-generated outputs, focusing on identifying inaccuracies and biases

Ethics workshops spotlight key principles through real-world case studies. Peer discussions unpack ethical dilemmas, using real world case studies of when AI goes wrong. This practical approach prepares you to apply ethics in your daily work

Learn to apply AI Ethical Principles to AI systems at work and how they could relate your personal life as well. 

Moving from experimenting adhoc with Generative AI to totally redesigning workflows to deeply integrate AI &amp; points for human oversight.

Learn methods to redesign new Human+AI ways of working

Data informed decision making will become critical in every role. Learn the basics of how to leverage AI to help me make better informed decisions.

Learn how to make better data-informed decisions

Master the skills in using Generative AI for work and implementing AI responsibly by building trustworthy AI products that drive adoption

Lightning Lessons

AI Agents & Multimodal LLMs