4 Weeks
·Cohort-based Course
Build LLM-powered software reliably & from first principles. Learn the GenAI software development lifecycle: agents, evals, iteration & more
This course is popular
5 people enrolled last week.
4 Weeks
·Cohort-based Course
Build LLM-powered software reliably & from first principles. Learn the GenAI software development lifecycle: agents, evals, iteration & more
This course is popular
5 people enrolled last week.
Experience building and lecturing at
Course overview
Enroll in this course now for early bird pricing of $800. On December 1st, the cost will revert to the regular cost of $1,000.
It's easy to build a generative AI POC but turning it into robust, reliable software that scales is difficult: most of us still end up in "POC purgatory".
It doesn't have to be this way.
Using the right principles and human-centric tools, you can take proof of concept LLM-powered demos and turn them into robust software.
In this course, you'll learn the first principles necessary to ship robust and reliable LLM applications, along with developing the technical chops and iterative product development mindset necessary.
Course content
- How to integrate AI models and APIs into a practical application.
- Techniques to manage non-determinism and optimize outputs through prompt engineering.
- How to monitor, log, and evaluate AI systems to ensure reliability.
- The importance of handling structured - outputs and using function calling in AI models.
- The software engineering side of building AI systems, including iterative development, debugging, and performance monitoring.
- Practical experience in building an app to query PDFs using multimodal models.
The course includes
- Hands-on sessions building and using LLM applications
- Iteration and experimentation to improve GenAI applications
- Group discussions and reflection on the building process and the end-user experience
- Q&As with expert practitioners
API Credits
- Modal (serverless cloud infrastructure for AI, ML, and data applications) is generously providing $1,000 worth of credits for all students!
- Watch this space for announcement of more API credits you will receive in this course.
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Data scientists, machine learning engineers who are sick & tired of seeing and building prototypes & want to ship reliable LLM applications
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Software engineers who want to learn how to build Generative AI systems and learn the LLM software development lifecycle.
How to integrate AI models and APIs into a practical application.
Over the course we'll build out a simple AI application to ground the principles in the course. We'll successively add to it, and take if from a simple LLM pipeline that processes a PDF, to something that also has some agentic behavior.
Techniques to manage non-determinism and optimize outputs through prompt engineering.
We will show case practical approaches to improving and evaluating your prompts and application outcomes.
How to monitor, log, and evaluate AI systems to ensure reliability.
We'll demystify the engineering required behind these solutions so you can choose to implement them yourself.
The software engineering side of building AI systems, including iterative development, debugging, and performance monitoring.
You'll leave with a better understanding of what is going on, and how to construct a software development lifecycle that fits your reliability needs.
8 interactive live sessions
Lifetime access to course materials
11 in-depth lessons
Direct access to instructor
Projects to apply learnings
Guided feedback & reflection
Private community of peers
Course certificate upon completion
Maven Satisfaction Guarantee
This course is backed by Maven’s guarantee. You can receive a full refund within 14 days after the course ends, provided you meet the completion criteria in our refund policy.
Building LLM Applications for Data Scientists and Software Engineers
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Elijah ben Izzy
Hamel Husain
Host of Vanishing Gradients podcast; ex-Outerbounds; expert in DS/ML.
Hugo Bowne-Anderson is an independent data and AI consultant with extensive experience in the tech industry. He is the host of the industry Vanishing Gradients, where he explores cutting-edge developments in data science and artificial intelligence. As a data scientist, educator, evangelist, content marketer, and strategist, Hugo has worked with leading companies in the field. His past roles include Head of Developer Relations at Outerbounds, a company committed to building infrastructure for machine learning applications, and positions at Coiled and DataCamp, where he focused on scaling data science and online education respectively. Hugo's teaching experience spans from institutions like Yale University and Cold Spring Harbor Laboratory to conferences such as SciPy, PyCon, and ODSC. He has also worked with organizations like Data Carpentry to promote data literacy. His impact on data science education is significant, having developed over 30 courses on the DataCamp platform that have reached more than 3 million learners worldwide. Hugo also created and hosted the popular weekly data industry podcast DataFramed for two years. Committed to democratizing data skills and access to data science tools, Hugo advocates for open source software both for individuals and enterprises.
Ex-Stitch Fix; 13+ Years building / productionizing data, ML, and AI
Stefan Krawczyk is the co-founder and CEO of DAGWorks, an open-source company driving two projects: Hamilton & Burr, whose mission to empower developers to build reliable AI agents & applications. He is a Y Combinator alum, StartX alum, and a Stanford graduate with a Master of Science in Computer Science with Distinction in Research. He has over thirteen years of experience in building and leading data & ML-related systems and teams, at companies like Stitch Fix, Idibon, Nextdoor, and Linkedin, his passion is to make others more successful with data by bridging the engineering gap between data science, machine learning, artificial intelligence, and the business.
Join an upcoming cohort
Cohort 1
$800
Dates
Payment Deadline
4-6 hours per week
Mondays and Wednesdays
4:00pm - 6:00pm PST
Live in person sessions. We'll finalize session times by mid-November.
Weekly projects
2 hours per week
To ensure hands-on practical time, there will be project work to complete throughout the course.
Active hands-on learning
This course builds on live workshops and hands-on projects
Interactive and project-based
You’ll be interacting with other learners through breakout rooms and project teams
Learn with a cohort of peers
Join a community of like-minded people who want to learn and grow alongside you
Join an upcoming cohort
Cohort 1
$800
Dates
Payment Deadline