Large Language Models Bootcamp

NEW

. 5 DAYS . 40 HOURS . IN-PERSON / ONLINE

Comprehensive, hands-on curriculum to give you a headstart in building Large Language Model Applications.

$4999

10% OFF

4.95 · 640+ reviews

$4499

Includes:

Software subscriptions and cloud services credit up to USD $500.

Breakfast, lunch and beverages daily.
Course material and access to coding labs, Jupyter notebooks, and hundreds of learning resources for 1 year.

INSTRUCTORS AND GUEST SPEAKERS

Learn From Industry Leaders

Pre-trained Large Language Models like ChatGPT offer impressive capabilities but they cannot be used in scenarios where the underlying data is proprietary and requires industry-specific knowledge. Businesses are rushing to build custom LLM applications that offer enhanced performance, control, customization and most importantly, competitive advantage. This bootcamp offers a comprehensive introduction to get started with building a ChatGPT on your own data. By the end of the bootcamp, you will be capable of building LLM-powered applications on any dataset of your choice.

In collaboration with

Who Is This Course For

Anyone

Anyone interested in getting a headstart by getting a hands-on experience with building LLM applications.

Data professionals

Data professionals who want to supercharge their data skills using cutting-edge generative AI tools and techniques.

Product leaders

Product leaders at enterprises or startups seeking to leverage LLMs to enhance their products, processes and services.

Curriculum Highlights

Generative AI and LLM Fundamentals

A comprehensive introduction to the fundamentals of generative AI, foundation models and Large language models

Canonical Architectures of LLM Applications

An in-depth understanding of various LLM-powered application architectures and their relative tradeoffs

Embeddings and Vector Databases

Hands-on experience with vector databases and vector embeddings

Prompt Engineering

Practical experience with writing effective prompts for your LLM applications

Orchestration Frameworks: LangChain and Llama Index

Practical experience with orchestration frameworks like LangChain and Llama Index

Deployment of LLM Applications

Learn how to deploy your LLM applications using Azure and Hugging Face cloud

Customizing Large Language Models

Practical experience with fine-tuning, parameter efficient tuning and retrieval parameter-efficient + retrieval-augmented approaches

Building An End-to-End Custom LLM Application

A custom LLM application created on selected datasets

$4999

10% OFF

4.95 · 640+ reviews

$4499

Includes:

Software subscriptions and cloud services credit up to USD $500.

Breakfast, lunch and beverages daily.
Course material and access to coding labs, Jupyter notebooks, and hundreds of learning resources for 1 year.

Technologies and Tools

Testimonials

Our customers and partners love us!

"Partnering with Data Science Dojo aligns with our mission to make data science accessible. Their bootcamps contribute to safe AI deployment education."

"LLM bootcamp provides exceptional, hands-on initiation into LLMs and practical applications. A deep dive into the subject with theoretical knowledge."

"Six months of course material access post-training is valuable. Instructors ensure success, making it a top-notch learning experience in AI."

"Instructors simplified complex topics effectively. Hands-on learning enhanced my LLM understanding in 5 days. Intensive but immeasurable rewards."

"A rewarding opportunity to help students of all backgrounds learn new techniques. Being part of a passionate data science community was a real privilege."

"LLM Bootcamp provides hands-on experience with expert instructors, a comprehensive framework, and extensive resources for substantial upskilling."

"The effort in providing resources was commendable. Teachers and assistants were helpful, making it one of the best courses. I learned a lot for future use."

"Top-notch speakers, hands-on workshops, and networking make it a wonderful tech experience. Raja's in-depth teaching focuses on learning concepts."

"Comprehensive curriculum in generative AI, prompt engineering, and data retrieval. Excited about practical training opportunities."

"Collaborating with Data Science Dojo nurtures the next generation of LLM developers, commendable for fostering a dedicated creator community."

"This boot camp provided great content, equipping me with skills and confidence for efficient job execution. Enjoyable class and projects, a rewarding decision."

"The LLM Bootcamp offered an enlightening, well-structured learning experience, invaluable networking, and insights into real-world AI challenges. "

"Seamless navigation, invaluable hands-on exercises, and well-structured technical aspects for optimal, cost-effective results. Highly recommended for practical LLM knowledge."

"Comprehensive curriculum for in-depth understanding, seamless hands-on learning with cloud-based tools, and insightful talks by industry experts. Highly recommended."

"Outstanding boot camp, engaging discussions on coding and data security. A valuable and refreshing experience, recommended for advancing data science skills."

"Explored Data Science Dojo's LLM Bootcamp, gaining confidence with a comprehensive understanding. In-person experience, insightful instructors, and diverse insights."

"LLM Bootcamp surpassed expectations, bridging theory with practical examples. Engaging with cohorts, invaluable insights, and balanced intensity elevated understanding. Highly recommended for language models."

"LLM Bootcamp enriched my understanding of the language-tech intersection. Collaborating with peers was wonderful. Sophie DA's insightful presentation on practical applications is recommended for foundational knowledge."

"LLM Bootcamp shifted my problem-solving approach, sparking creativity with limitless applications. Highly recommended for anyone building their toolkit, fostering creativity in problem solvers, and providing invaluable insights for diverse applications."

"Dedicated a week to a profound learning experience with Data Science Dojo, sparking innovative ideas. The practical approach revolutionized our models. Highly recommended."

"Engaging with diverse participants and the Dojo staff provided valuable insights. Emphasizes the importance of understanding model performance. Highly recommended for all roles."

"The bootcamp's blend of theory and hands-on experience suited learners of all backgrounds. In just five days, I gained invaluable knowledge and tools for navigating the AI landscape. "

"The boot camp surpassed my expectations with insightful talks, practical insights, and comprehensive resources, essential for accelerating knowledge in LLMs."

"The Data Science Dojo Bootcamp exceeded expectations, offering comprehensive learning, hands-on experience, and valuable insights, transforming my confidence in AI."

"The Bootcamp accelerated my text analysis skills by engaging in in-person experience, industry insights, and valuable hands-on learning. Highly recommended!"

"The Bootcamp helped me bridge the gap between academia and industry, offering insightful talks and practical problem-solving exercises. "

"The Bootcamp exceeded my expectations, offering comprehensive training for both beginners and experienced data scientists. Highly recommended for all!"

Earn a Verified Certificate of Completion

In association with

Earn a Large Language Models certificate in association with the University of New Mexico Continuing Education, verifying your skills. Step into the market with a proven and trusted skillset.

Course Syllabus

DAY 1 - LLM Fundamentals

Understanding the LLM Ecosystem

In this module we will understand the common use cases of large language models and fundamental building blocks of such applications. Learners will be introduced to the following topics at a very high level without going into the technical details:

Large language models and foundation models
Prompts and prompt engineering
Context window and token limits
Embeddings and vector databases
Build custom LLM applications by:
- Training a new model from scratch
- Fine-tuning foundation LLMs
- In-context learning
Canonical architecture for an end-to-end LLM application

Adoption Challenges and Risks

In this module, we will explore the primary challenges and risks associated with adopting generative AI technologies. Learners will be introduced to the following topics at a very high level without going into the technical details:

Misaligned behavior of AI systems
Handling complex datasets
Limitations due to context length
Managing cost and latency
Addressing prompt brittleness
Ensuring security in AI applications
Achieving reproducibility
Evaluating AI performance and outcomes

Evolution of Embedding

In this module, we will be reviewing how embeddings have evolved from the simplest one-hot encoding approach to more recent semantic embeddings approaches. The module will go over the following topics:

Review of classical techniques
- Review of binary/one-hot, bag-of-words (BoW) and TF-IDF techniques for vectorization
- Capturing local context with n-grams and challenges
- Semantic Encoding Techniques
  - Overview of Word2Vec and dense word embeddings
  - Application of Word2Vec in text analytics and NLP tasks
- Text Embeddings
  - Word and sentence embeddings
- Text similarity measures
  - Dot product, Cosine similarity, Inner product
Hands-on Exercise
- Creating TF-IDF embeddings on a document corpus
- Calculating similarity between sentences using cosine similarity and dot product

DAY 2 - Vector Databases and Prompt Engineering

Attention Mechanism and Transformers

Dive into the world of large language models, discovering the potent mix of text embeddings, attention mechanisms, and the game-changing transformer model architecture.

Attention mechanism and transformer models
- Encoder decoder
- Transformer networks: tokenization, embedding, positional encoding and transformers block
- Attention mechanism
- Self-Attention
- Multi-head Attention
- Transformer models
Hands-on Exercise
- Understanding attention mechanisms: Self-attention for contextual word analysis

Vector Databases

Learn about efficient vector storage and retrieval with vector database, indexing techniques, retrieval methods, and hands-on exercises.

Overview
- Rationale for vector databases
- Importance of vector databases in LLMs
- Popular vector databases
Different types of search
- Vector search, text search, hybrid search
Indexing techniques
- Product Quantization (PQ), Locality Sensitive Hashing (LSH) and Hierarchical Navigable Small World (HNSW)
Retrieval techniques
- Cosine Similarity, Nearest Neighbor Search
Advanced Retrieval Augmented Generation techniques
- Limitations of embeddings and similarity in semantic search
- Query transformation for better retrieval
- Relevance scoring in hybrid search using Reciprocal Rank Fusion (RRF)
- Using auto-cut feature to remove irrelevant results dynamically
- Improving search relevance by using language understanding to re-rank search results
Challenges using vector databases in production
- Scaling optimization
- Reliability optimization
- Cost optimization
Hands-on Exercise
- Learn how to perform similarity searches with vectors as input.
- Learn how to perform queries using vector similarity searches with embedding models and vectors.
- Learn how to combine the results of a vector search and a keyword (BM25F) search using hybrid search approach.
- Learn how to use multi-tenancy features for the efficient and secure management of data across multiple users or tenants.
- Learn how to compress vectors using product quantization to reduce memory footprint.

Semantic Search

Understand how semantic search overcomes the fundamental limitation in lexical search i.e. lack of semantics . Learn how to use embeddings and similarity in order to build a semantic search model.

Understanding and Implementing Semantic Search
- Introduction and importance of semantic search
- Distinguishing semantic search from lexical search
- Semantic search using text embedding

LLM - Online Courses

Reviews

Consulting

Community

Large Language Models Bootcamp

$4999

$4499

Learn From Industry Leaders

Learn to Build and Deploy Custom LLM Applications

Who Is This Course For

Anyone

Data professionals

Product leaders

Curriculum Highlights

Generative AI and LLM Fundamentals

Canonical Architectures of LLM Applications

Embeddings and Vector Databases

Prompt Engineering

Orchestration Frameworks: LangChain and Llama Index

Deployment of LLM Applications

Customizing Large Language Models

Building An End-to-End Custom LLM Application

$4999

$4499

Technologies and Tools

Testimonials

Earn a Verified Certificate of Completion

In association with

Course Syllabus

DAY 1 - LLM Fundamentals

Understanding the LLM Ecosystem

Adoption Challenges and Risks

Evolution of Embedding

DAY 2 - Vector Databases and Prompt Engineering

Attention Mechanism and Transformers

Vector Databases

Semantic Search