This advanced course trains you for the cutting-edge of AI development by combining the power of Rust with Large Language Model Operations

Learn to build scalable LLM solutions using the performance of Rust
Master integrating Rust with LLM frameworks like HuggingFace Transformers
Integrate Rust with LLM frameworks like HuggingFace, Candle, ONNX

Get trained in the latest AI/ML innovations while mastering systems programming with Rust - your pathway to building state-of-the-art LLM applications.

Optimize LLM training/inference by leveraging Rust's parallelism and GPU acceleration
Build Rust bindings for seamless integration with HuggingFace Transformers
Convert and deploy BERT models to Rust apps via ONNX runtime
Utilize Candle for streamlined ML model building and training in Rust
Host and scale LLM solutions on AWS cloud infrastructure
Hands-on labs: Build chatbots, text summarizers, machine translation
Apply LLMOps DevOps practices - CI/CD, monitoring, security
Techniques for memory safety, multithreading, lock-free concurrency
Best practices for LLMOps reliability, scalability, cost optimization
Real-world projects demonstrating production-ready LLMOps expertise

This course is part of the Rust Programming Professional Certificate.

What you'll learn

Understand how to apply Rust's inherent safety and performance benefits to build a reliable and efficient LLMOps infrastructure.
Create Rust bindings to facilitate seamless integration with widely-adopted LLM frameworks like HuggingFace Transformers.
Master the art of building, training, and deploying large language models at scale, using AWS services harmoniously integrated with Rust.
Implement best practices in DevOps and LLMOps, such as Continuous Integration and Continuous Deployment (CI/CD), to optimize your LLM pipelines.
Acquire hands-on skills to monitor, troubleshoot, and secure deployed LLMs in production environments.
Analyze real-world use-cases and complete projects that demonstrate your LLMOps prowess, preparing you for industry roles requiring expertise in LLMs and Rust.

Syllabus

Module 1: DevOps Concepts for MLOps (6 hours)
\- Instructor Intro (Video - 1 minute)
\- A Function, the Essence of Programming (Video - 6 minutes)
\- Operationalize Microservices (Video - 1 minute)
\- Continuous Integration for Microservices (Video - 6 minutes)
\- What is Makefile and how do you use it? (Video - 2 minutes)
\- What is DevOps? (Video - 2 minutes)
\- Kaizen methodology (Video - 4 minutes)
\- Infrastructure as Code for Continuous Delivery (Video - 2 minutes)
\- Responding to Compromised Resources and Workloads (Video - 4 minutes)
\- Designing and Implementing Monitoring and Alerting (Video - 1 minute)
\- Audit Network Security (Video - 1 minute)
\- Rust Secure by Design (Video - 4 minutes)
\- Preventing Data Races with Rust Compiler (Video - 3 minutes)
\- Using AWS Config for Security (Video - 4 minutes)
\- AWS Security Hub Demo (Video - 3 minutes)
\- Explain How to Secure Your Account with 2FA (Video - 3 minutes)
\- Understanding Access Permissions (Video - 4 minutes)
\- Repository Permission Levels Explained (Video - 2 minutes)
\- Repository Privacy Settings and Options (Video - 2 minutes)
\- Unveiling Key Concepts of the GitHub Ecosystem (Video - 3 minutes)
\- Demo: Implementing GitHub Actions (Video - 3 minutes)
\- Demo: GitHub Codespaces (Video - 6 minutes)
\- Demo: GitHub Copilot (Video - 8 minutes)
\- Source Code Resources (Reading - 10 minutes)
\- Infrastructure as code (Reading - 10 minutes)
\- Continuous integration (Reading - 10 minutes)
\- Continuous delivery (Reading - 10 minutes)
\- Automation and tooling (Reading - 10 minutes)
\- Shared responsibility (Reading - 10 minutes)
\- Identity and access management (Reading - 10 minutes)
\- Infrastructure protection (Reading - 10 minutes)
\- Incident response (Reading - 10 minutes)
\- External Lab: Use GitHub Actions and Codespaces (Reading - 10 minutes)
\- About two-factor authentication (Reading - 10 minutes)
\- Access permissions on GitHub (Reading - 10 minutes)
\- About Continuous Integration (Reading - 10 minutes)
\- About continuous deployment (Reading - 10 minutes)
\- Final Week-Reflections (Reading - 10 minutes)
\- DevOps Concepts for MLOps (Quiz - 30 minutes)
\- Lab: Using a Makefile with Rust (Ungraded Lab - 60 minutes)
\- Lab: Preventing Data Races in Rust (Ungraded Lab - 60 minutes)

Module 2: Rust Hugging Face Candle (4 hours)
\- Candle: A Minimalist ML Framework for Rust (Video - 2 minutes)
\- Using GitHub Codespaces for GPU Inference with Rust Candle (Video - 5 minutes)
\- VSCode Remote SSH development AWS Accelerated Compute (Video - 5 minutes)
\- Building Hello World Candle (Video - 2 minutes)
\- Exploring StarCoder: A State-of-the-Art LLM (Video - 5 minutes)
\- Using Whisper with Candle to Transcribe (Video - 5 minutes)
\- Exploring Remote Dev Architectures on AWS (Video - 2 minutes)
\- Advantages of Rust for LLMs (Video - 1 minute)
\- Serverless Inference (Video - 1 minute)
\- Rust CLI Inference (Video - 2 minutes)
\- Rust Chat Inference (Video - 1 minute)
\- Continuous Build of Binaries for LLMOps (Video - 2 minutes)
\- Chat Loop for StarCoder (Video - 2 minutes)
\- Invoking Rust Candle on AWS G5-Part One (Video - 4 minutes)
\- Invoking BigCode on AWS G5-Part Two (Video - 3 minutes)
\- rust-candle-demos (Reading - 10 minutes)
\- Configuring NVIDIA CUDA for your codespace (Reading - 10 minutes)
\- Getting Started Candle (Reading - 10 minutes)
\- Candle Examples (Reading - 10 minutes)
\- External Lab: Candle Hello World (Reading - 10 minutes)
\- External Lab: Run an LLM with Candle (Reading - 10 minutes)
\- Developer Guide cuDNN (Reading - 10 minutes)
\- cuDNN Webinar (Reading - 10 minutes)
\- Programming Tensor Cores in CUDA 9 (Reading - 10 minutes)
\- Tensor Ops Made Easier in cuDNN (Reading - 10 minutes)
\- External Lab: Using BigCode to Assist With Coding (Reading - 10 minutes)
\- StarCoder: A State-of-the-Art LLM for Code (Reading - 10 minutes)
\- Falcon LLM (Reading - 10 minutes)
\- Whisper LLM (Reading - 10 minutes)
\- Candle Structure (Reading - 10 minutes)
\- Final Week Reflection (Reading - 10 minutes)
\- Rust Hugging Face Candle (Quiz - 30 minutes)

Module 3: Key LLMOps Technologies (3 hours)
\- Introduction to Rust Bert (Video - 1 minute)
\- Installation and Setup (Video - 5 minutes)
\- Basic Syntax and Model Loading (Video - 2 minutes)
\- Building a sentiment analysis CLI (Video - 4 minutes)
\- Introduction to Rust PyTorch (Video - 1 minute)
\- Running a PyTorch Hello World (Video - 2 minutes)
\- PyTorch Pretrained (Video - 3 minutes)
\- Running PyTorch Pretrained (Video - 6 minutes)
\- Introduction to ONNX (Video - 1 minute)
\- ONNX Conversions (Video - 2 minutes)
\- Getting Started Rust Bert (Reading - 10 minutes)
\- External Lab: Translate a Spanish song to English (Reading - 10 minutes)
\- Rust Bert pipelines (Reading - 10 minutes)
\- ONNX Support Rust Bert (Reading - 10 minutes)
\- Loading pretrained and custom model weights (Reading - 10 minutes)
\- External Lab: Run a Pretrained model (Reading - 10 minutes)
\- Rust bindings for PyTorch (Reading - 10 minutes)
\- ONNX Concepts (Reading - 10 minutes)
\- ONNX with Python (Reading - 10 minutes)
\- Converters (Reading - 10 minutes)
\- ONNX Model Hub (Reading - 10 minutes)
\- Final Week-Reflections (Reading - 10 minutes)
\- External Lab: Use ONNX (Reading - 10 minutes)
\- Using Rust Bert (Quiz - 30 minutes)

Module 4: Key Generative AI Technologies (3 hours)
\- Extending Google Bard (Video - 4 minutes)
\- Exploring Google Colab with Bard (Video - 4 minutes)
\- Exploring Colab AI (Video - 4 minutes)
\- Exploring Gen App Builder (Video - 2 minutes)
\- Responsible AI with AWS Bedrock (Video - 4 minutes)
\- AWS Bedrock with Claude (Video - 7 minutes)
\- Summarizing text with Claude (Video - 5 minutes)
\- Using the AWS Bedrock API (Video - 1 minute)
\- Live Coding AWS CodeWhisperer Part One (Video - 6 minutes)
\- Live Coding AWS CodeWhisperer Part Two (Video - 14 minutes)
\- Live Coding AWS CodeWhisperer Part Three (Video - 7 minutes)
\- Using AWS CodeWhisperer CLI (Video - 3 minutes)
\- Bard FAQ (Reading - 10 minutes)
\- External Lab: Build a plot with Colab AI (Reading - 10 minutes)
\- External Lab: AWS Bedrock (Reading - 10 minutes)
\- AWS Cloud Adoption Framework for Artificial Intelligence, Machine Learning, and Generative AI (Reading - 10 minutes)
\- People perspective: Culture and change towards AI/ML-first (Reading - 10 minutes)
\- External Lab: Use CodeWhisperer for Rust Calculator (Reading - 10 minutes)
\- Key LLMOps Technologies (Quiz - 30 minutes)
\- Final-Quiz (Quiz - 30 minutes)