.png&w=1536&q=75)
LLM Bootcamp Pro
1-hour interactive learning three times per week in a live production environment. (Flexible engagement options for busy professionals)
This course is no longer available.
Explore other courses.png&w=1536&q=75)
.png&w=1536&q=75)
Working with the best
Course overview
LLM Bootcamp Pro: Customize & Deploy Large Language Models
🚨 World-Class AI Training in a Live Production Environment 🚨
Master Large Language Models (LLMs) with Orcawise LLM Bootcamp Pro, a 100 days on-the-job program designed for data scientists, AI engineers, developers, product managers, and legal & compliance professionals looking to gain hands-on expertise.
This course is run is a real-life production environment, delivered in a flexible way ensuring that even busy professionals can participate effectively. While the course is running live, you also have the option to engage at your own pace with:
✅ On-demand recordings for all sessions
✅ Comprehensive course materials accessible anytime
✅ 1:1 office hours with instructors for personalized support
✅ Custom cohort options for large teams with special requirements like: local time zones, skill levels, specialized industry applications, etc.
✅ Custom capstone projects so you can work on our in-house applications or build your own custom LLM at your own pace under the guidance of top instructors.
Join this interactive AI bootcamp and work on a real-world, production-level LLM, actively contributing to the:
1. Development of the Orcawise Custom LLM for legal and compliance.
OR
2. Build your own custom application for your company, your start-up or your personal project.
🚀 Secure your spot today!
🚨Why Choose This Bootcamp?
Real-World Project Experience:-
Be Part of Live LLM Development or Build Your Own AI Solution: Work alongside the Orcawise AI team to refine an LLM tailored to the EU AI Act, US AI Guidelines, and global regulatory frameworks—or take the expertise gained and develop your own industry-specific AI application in legal, compliance, finance, healthcare, or beyond.
Production-Ready Skills: Master tools like LangChain, Retrieval Augmented Generation (RAG), PEFT-LoRA, Hugging Face, and PyTorch.
Capstone Project-Centered Learning Tailored Capstone Projects: Starting from Week 4, build a project aligned with your industry’s specific legal and compliance challenges, using real-world data.
Demo Day: Showcase your fully functional LLM solution to peers and industry professionals.
Expert-Led Interactive Sessions Live Workshops & Q&A: Learn from AI and legal tech experts, gaining industry insights to enhance your project.
Collaborative Environment: Join a community of professionals for networking and collaborative problem-solving.
🚨What You’ll Achieve
Master LLM Customization & Deployment: Fine-tune pre-trained models for specific legal and compliance tasks.
Deploy models using platforms like AWS and Hugging Face.
Develop Industry-Specific AI Solutions:
Create models for regulatory compliance, automating legal document reviews, and supporting adherence to the EU AI Act.
Affordable & Tiered Learning: Don't worry about tools costs. We'll start with free foundational models (T5, Bard) from Hugging Face before, optionally, progressing to ChatGPT, Mistral 7B, and Claude, towards the end of the course. So there are no upfront costs while gradually building skills.
Enhance Your Professional Portfolio: Showcase your Capstone Project, highlighting your expertise in AI within the legal and compliance sectors.
Who is this course for
01
Data Scientists and Engineers: Looking to advance your skills in fine-tuning and deploying LLMs.
02
AI Product Managers and Entrepreneurs: Building AI-driven products and seeking a deep understanding of LLMs.
03
Company Teams: Teams aiming to apply AI technologies to solve business challenges, with an option to opt-out of career transition support.
Key outcomes from Orcawise LLM Bootcamp Pro:
Hands-on Experience: Collaborate on a live LLM development project for legal and compliance applications.
Expert Guidance: Learn from top AI and legal tech experts through live workshops and Q&A sessions.
Capstone Project: Create and deploy a custom LLM solution tailored to real-world legal and compliance challenges.
Industry Recognition: Showcase your work during Demo Day to peers and industry professionals.
Career-Boosting Skills: Hugging Face, T5, Bard, Claude, Mistral, ChatGPT, RAG Systems, RAFT Systems, LangChain...
Data Curation Tools, Gradio, AWS, NGINX, Gunicorn, Systemctl, Systemd, PyTorch or TensorFlow, DVC (Data Version Control), Weights & Biases, Docker, Kubernetes, FastAPI, PEFT-LoRA, vLLM.
What’s included
Live sessions
Learn directly from Sanpreet Singh "LLM Fine-Tuning Expert & Bootcamp Trainer" & Kevin Neary "LLM Product Innovator & Bootcamp Leader" in a real-time, interactive format.
Lifetime access
Go back to course content and recordings whenever you need to.
Community of peers
Stay accountable and share insights with like-minded professionals.
Certificate of completion
Share your new skills with your employer or on LinkedIn.
Maven Guarantee
This course is backed by the Maven Guarantee. Students are eligible for a full refund up until the halfway point of the course.
Course syllabus
37 lessons • 12 projects
Week 1
- 📹
Introduction to LLM Architecture
Complete by Mar 11 - 📹
Pre-trained vs. Custom Models
Complete by Mar 12 - 📹
Understanding LLMs in Business Applications
Complete by Mar 13 - 📄
Tools for LLM Development (Hugging Face, PyTorch, TensorFlow)
- ✍️
Revision and doubt session for last 4 lessons
Submit by Mar 16
Foundations of LLMs
Week 2
- ☘️
Best Practices for Data Collection & Cleaning
- ☘️
Creating High-Quality Datasets
- ☘️
Data Version Control (DVC)
- ✍️
Data Preparation Task: Curate a dataset for LLM fine-tuning
Submit by Mar 23
Data Curation & Preparation
Week 3
- ☘️
Importance of Fine-Tuning
- ☘️
Step-by-Step Fine-Tuning Process
- ☘️
Capstone Project Overview and Expectations
- ✍️
Capstone Project Proposal: Submit your Capstone Project idea
Submit by Apr 5
Fine-Tuning Fundamentals & Capstone Project Kickoff
Week 4
- ☘️
Using PEFT-LoRA for Efficient Fine-Tuning
- ☘️
Understanding learning rate, batch size and early stopping
- 📚
Warm-up, weight decay and checkpointing (with Practical Coding)
- ✍️
Capstone Milestone 1: Get started with your own custom LLM
Submit by Apr 13
Technical Workshop: Deep Dive into Fine-Tuning Methods.
Week 5
- ☘️
Inferences Hyperparameters [For both fine tuned and pretrained model]
- ☘️
Designing Effective Prompts with zero, single and few short learning
- 📚
Doubt session and recap session on fine tuning training and inferences
- ✍️
Capstone Milestone 2: Apply prompt engineering techniques
Submit by Apr 20
Deep dive into fine tuning inferences
Week 6
- 📄
Untitled lesson
BREAK
No module content yet
Note: No live sessions this week.
Week 7
- 😀
Understanding RAG using code (Streamlit)
- ☘️
Creating Vector Stores for RAG and practical demo
- 🚀
Introduction to AI Agents
- ✍️
Capstone Milestone 3: Integrate RAG components into your Capstone Project
Submit by May 4
Prompt Engineering & RAG Systems
Prompt Engineering, RAG Systems & AI Agents
Week 8
- ☘️
Creating and deploying Fine tuned Model on Hugging Face Spaces
- ☘️
RAPT vs. Pre-trained Model Interaction vs Distilled model
- ☘️
Summary of RAPT and review
- ✍️
Capstone Milestone 4: Incorporate advanced interaction techniques in Capstone
Submit by May 11
RAPT & Advanced Interaction
RAPT Systems, Advanced Interaction, and AI Agent Architectures
Week 9
- ☘️
Cloud Deployment Basics (AWS, Hugging Face, Gradio)
- 📄
Understanding Systemctl and Journalctl commands
- 📄
Understanding Claude 3.5 Sonet
- ✍️
Capstone Milestone 5: Begin deploying your Capstone Project model to cloud
Submit by May 18
Model Deployment - Part 1
Module: Deploying LLMs to the Cloud
Week 10
- ☘️
Inference and fine tuning using Claude 3.5 Sonet
- ☘️
Live inference with claude 3.5 sonet and Bias mitigation
- 📄
Understanding responsible AI
- ✍️
Capstone Milestone 6: Use claude 3 model on ec2 instance for inference
Submit by May 25
Model Deployment - Part 2
Week 11
- ☘️
Algorithms behind RAG
- ☘️
Understanding libraries and framework for better training and analysis
- ☘️
Devops concepts and practical demo
- ✍️
Capstone Milestone 7: Create your own docker image for training pretrained model
Submit by Jun 1
Deeper understanding of RAPT
Week 12
- ☘️
Understanding System design of Orcawise Information Model
- ☘️
Understanding Graphql, apollo client and apollo server
- ☘️
Deploying Orcawise dashboard on amazon server
- ✍️
Capstone Milestone 8: Create Open information model for your use case
Submit by Jun 8
Case study: Orcawise information extraction model
Case Study of Orcawise Information Extraction Model
Week 13
- ☘️
Presenting Your LLM Solution
- ☘️
Preparing for Demo Day
- ✍️
Capstone Project Completion: Finalize and prepare to present your custom LLM
Submit by Jun 4
Capstone Completion & Demo Day
Module: Capstone Finalization and Presentation
Bonus
Option 1: Career Coaching (for Individuals)
No module content yet
Option 2: AI Leadership (for Company teams)
No module content yet
What people are saying about Sanpreet, Kevin and Orcawise trainings.
Gareth Moan
Marie Pigott
Ike Ogbuchi
Stephanie Myott Beebe
Pritha Chakrobarty
Kajol Kaiya
Sanyam
Dorothy Maiti
Meet your instructors
Sanpreet Singh "LLM Fine-Tuning Expert & Bootcamp Trainer"
Sanpreet Singh "LLM Fine-Tuning Expert & Bootcamp Trainer"
Head of AI & Full-Stack LLM Architect at Orcawise
Sanpreet Singh leads the AI engineering team at Orcawise, with expertise spanning the full AI stack—from data engineering and model transformation to chatbot development.
As the lead instructor for the Orcawise Innovation Program (OIP), Sanpreet has helped numerous graduates and professionals elevate their AI careers through a hands-on, bootcamp-style training.
Sanpreet has led the design and development of advanced data scrapers, and he has fine-tuned cutting-edge LLMs such as ChatGPT, Claude, Gemini, and Mistral, deploying them on industry-standard platforms like Hugging Face. His real-world experience ensures students gain practical, industry-relevant skills.
Sanpeets leadership and technical expertise make him a key figure in shaping AI-driven solutions, guiding both companies and individuals to succeed in the rapidly evolving AI landscape.
Kevin Neary "LLM Product Innovator & Bootcamp Leader"
Kevin Neary "LLM Product Innovator & Bootcamp Leader"
Top AI Voice | AI Product Innovator | Keynote Speaker | Board Advisor | CEO
Kevin Neary is the Co-Founder, CEO, and Product Lead at Orcawise, a leading AI advisory and services firm specializing in Responsible AI.
He also serves as am Industry Steering Board member at CeADAR, one of Europe's top European Digital Innovation Hubs (EDIG), and is a Board Member at the AI Lab at Georgia College and State University, United States.
Since 2016, Kevin has been the Course Director of the Orcawise Innovation Program (OIP), a 100-day bootcamp where he and his expert team have trained hundreds of professionals. Graduates have gone on to transform their careers with leading companies like Accenture, EY, LinkedIn, Google, and Facebook, as well as some of the world’s top startups.
Due to popular demand, this highly sought-after bootcamp is now available on Maven, offering an even more flexible, interactive learning experience designed to help you accelerate your AI career.
Kevin Neary is a Certified Business and Executive Coach and a Keynote Speaker on Responsible AI .
Course schedule
2 - 6 hours weekly
Monday, Wednesday & Thursday 06.00 PST/9.00 EST/14.00 GMT
3 hours per week
Three 1-hour live interactive lessons per week on zoom. Recordings and materials are posted after each session.
Lessons delivered by instructors on zoom, with team discussions, contributions and feedback.
1:1 Office Hours to accommodate busy professionals.
Projects projects
4 hours per week (optional)
Optional Capstone. We encourage our students to build your own custom application based on your learnings and our guidance. Each week your instructors will provide project guidance to the whole cohort and your individual contribution will fall due within 1-week, for feedback.
Live Production Environment
Hands on work experience
The course is delivered form a live development and production environment so participants can acquire real-life work experience of Custom LLM's, RAG Operations and AI Agents.
Learning is better with cohorts
Active hands-on learning
This course builds on live daily interactive lessons and dessions/weekly events.
Interactive and project-based
On the back of the live lessons and sessions you will engage in practical weekly projects developing an production ready LLM. These weekly project build momentum and result in your your Capstone.
Learn with a cohort of peers
Join a community of like-minded people who want to learn and grow alongside you. Work with a team of industry leaders on a real-life high profile custom LLM development.
Frequently Asked Questions
Tools &Techniques
Describe a key outcome or topic covered in your course
Give students an idea of how they can expect to grow throughout your course. Include specificity and precise results so students can benchmark exactly what they’ll learn.
Describe a key outcome or topic covered in your course
Give students an idea of how they can expect to grow throughout your course. Include specificity and precise results so students can benchmark exactly what they’ll learn.
Describe a key outcome or topic covered in your course
Give students an idea of how they can expect to grow throughout your course. Include specificity and precise results so students can benchmark exactly what they’ll learn.
Describe a key outcome or topic covered in your course
Give students an idea of how they can expect to grow throughout your course. Include specificity and precise results so students can benchmark exactly what they’ll learn.