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Building LLM Applications

4.8

(42 ratings)

·

6 Weeks

·

Cohort-based Course

Gain a thorough understanding of the world of Large Language Models with a deep understanding on how to build your own applications

Previously at

Google
University of Minnesota
Stanford University

Course overview

Build LLM Powered Applications, like a pro!

This course is amongst the top-rated and extremely popular courses on the Maven Cohort. So far I have taught this course to over 250 Professional.


The course is aimed to introduce you to Large Language Models in deeper detail on what is Transformer Architecture and how we utilize the Encoder and Decoder Models.


This is not a Langchain course but much more than that. We go into great depth to explain the building blocks of retrieval systems and how to utilize Open Source LLMs to build your own architecture.


Learning Outcome:


- Gain a comprehensive understanding of the end-to-end LLM architecture


- Construct and deploy robust and effective models in real-world settings using Large

Language Models. 


- Learn to tackle practical machine learning problems and deliver results in production.



Additionally, students will gain a comprehensive understanding of the end-to-end machine learning pipeline, allowing them to construct and deploy robust and effective models in real-world settings using Large Language Models. Overall, students will emerge with greater confidence in their abilities to tackle practical machine learning problems and deliver results in production.


Please Note:

This is not a beginner course for non technical people, it requires knowledge of Python and some basic machine learning background.

Who is this course for

01

You are intrigued about LLMs and would like to build applications powered by LLMs

02

You are ready to deploy your own SOTA AI Models and like to see how they work

03

You want to go beyond Jupyter Notebook and develop batch or real-time prediction

What you’ll get out of this course

Collect and preprocess data for large language models


Train and fine-tune pre-trained large language models for specific tasks


Evaluate the performance of large language models and select appropriate metrics


Deploy large language models in real-world applications using APIs and Huggingface


Understand ethical considerations involved in working with large language models, such as avoiding bias and ensuring transparency

This course includes

7 interactive live sessions

Lifetime access to course materials

21 in-depth lessons

Direct access to instructor

6 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.

Course syllabus

Expand all modules
  • Post-Course

    Modules

    • Demo Day

4.8

(42 ratings)

What students are saying

Excited to have you here

Hamza Farooq

Hamza Farooq

Founder | Ex-Google | Adjunct Professor Stanford & UCLA

I am a Founder by day and Professor by night. My work revolves in the realm of LLMs and Multi-Modal Systems.


My startup, traversaal.ai was built with one vision: provide scalable LLM Solutions for Startups and Enterprises, which can seamlessly integrate within the existing ecosystem, while being customizable and cost efficient.


This course is a cumulation of all my learnings and the courses I teach at other universities

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Course schedule

4-6 hours per week
  • Saturday: Module Teaching

    8am - 10:00am PST

    We will go through each module during this class

  • Weekly projects

    2-4 hours per week

    Students will spend time building projects with their team members or individually

Free resource

Building LLM Applications from Scratch

this course with a focus on production and LLMs is designed to equip students with practical skills necessary to build and deploy machine learning models in real-world settings. Be part of the first 20 people cohort. More in email link..

Join Waitlist!

Learning is better with cohorts

Learning is better with cohorts

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

Frequently Asked Questions

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Building LLM Applications

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