EdX

DevOps, DataOps, MLOps (edX)

DevOps, DataOps, MLOps (edX)

Streamline AI Operations: Leverage DevOps, DataOps, and MLOps for End-to-End Machine Learning Solutions.

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Apply Real-World Machine Learning with DevOps, DataOps & MLOps

  • Master end-to-end MLOps solutions through hands-on AI pair programming
  • Leverage cutting-edge tools like GitHub Copilot, Gradio & Hugging Face
  • Build containerized ML apps deployable across cloud platforms

Course Journey:

  • Explore MLOps landscape and pre-trained models to solve business problems
  • Apply ML/AI in practice through optimization, simulation & heuristics
  • Develop integrated DevOps, DataOps & MLOps pipelines on GitHub
  • Package ML solutions in containers for seamless cloud deployment
  • Transition to Rust for high-performance GPU-accelerated ML tasks
  • Ideal for data scientists, software engineers, analysts & professionals working with machine learning. Gain holistic MLOps skills through real-world projects.

This course is part of the Machine Learning Operations Professional Certificate.

What you'll learn

  • Use web frameworks like Gradio & Hugging Face for interactive ML
  • Build command-line tools for ML/AI applications with Click
  • Leverage Rust's performance for Kubernetes, Docker & Serverless use cases
  • Containerize and deploy ML pipelines across cloud environments

Syllabus

Week 1: Introduction to MLOps
\- Introduction to MLOps (Video, 4 minutes, Preview module)
\- MLOps Background (Video, 2 minutes)
\- MLOps Trends and Techniques (Video, 13 minutes)
\- What is DevOps? (Video, 2 minutes)
\- What is DataOps? (Video, 1 minute)
\- MLOPs: Heavy vs Light (Video, 3 minutes)
\- MLOps: Hierarchy of Needs (Video, 3 minutes)
\- Data Poisoning Machine Learning Systems (Video, 2 minutes)
\- What are the Key Components in MLOPs? (Video, 3 minutes)
\- Considering the MLOps Maturity Models (Video, 4 minutes)
\- What is Continuous Integration? (Video, 32 minutes)
\- What is Continuous Delivery? (Video, 2 minutes)
\- What is a Feature Store? (Video, 2 minutes)
\- What is Data Drift? (Video, 1 minute)
\- Operationalizing a Microservice (Video, 1 minute)
\- CI for Microservices (Video, 7 minutes)
\- End to End MLOps HuggingFace Spaces (Video, 11 minutes)
\- App Runner Example (Video, 5 minutes)
\- Flask Example (Video, 3 minutes)
\- Building Golang GCP App Engine Microservice (Video, 5 minutes)
\- Getting Started with Makefile (Video, 2 minutes)
\- The Three Most Important Files in a Python Project (Video, 3 minutes)
\- Getting Started and Course Gotchas (Reading, 10 minutes)
\- Key Terms (Reading, 10 minutes)
\- Additional Readings (Reading, 10 minutes)
\- Lesson Reflection (Reading, 10 minutes)
\- Key Terms (Reading, 10 minutes)
\- Additional Readings (Reading, 10 minutes)
\- Lesson Reflection (Reading, 10 minutes)
\- Key Terms (Reading, 10 minutes)
\- Additional Readings (Reading, 10 minutes)
\- Lesson Reflection (Reading, 10 minutes)
\- Key Concepts in MLOps (Quiz, 30 minutes)
\- Quiz: What is MLOPs? (Quiz, 30 minutes)
\- Key Concepts in MLOps (Quiz, 30 minutes)
\- Quiz: Key Concepts in Microservices (Quiz, 30 minutes)
\- Meet and Greet (optional) (Discussion Prompt, 10 minutes)
\- Let Us Know if Something's Not Working (Discussion Prompt, 10 minutes)
\- Build CI/CD Solution (Ungraded Lab, 60 minutes)

Week 2: Essential Math and Data Science
\- Doing Data Science Your First Day (Video, 46 minutes, Preview module)
\- What is Colab? (Video, 5 minutes)
\- Understanding the Traveling Salesman Problem (TSP) (Video, 56 minutes)
\- Simulations vs. Experiment Tracking (Video, 6 minutes)
\- Machine Learning and AI in Practice with Clustering (Video, 26 minutes)
\- Key Terms (Reading, 10 minutes)
\- Additional Readings (Reading, 10 minutes)
\- Lesson Reflection (Reading, 10 minutes)
\- Key Terms (Reading, 10 minutes)
\- Additional Readings (Reading, 10 minutes)
\- Lesson Reflection (Reading, 10 minutes)
\- Key Terms (Reading, 10 minutes)
\- Additional Readings (Reading, 10 minutes)
\- Lesson Reflection (Reading, 10 minutes)
\- Essential Math and Data Science (Quiz, 30 minutes)
\- Quiz: Doing Data Science Your First Day (Quiz, 30 minutes)
\- Quiz: Optimization, Heuristics and Simulations (Quiz, 30 minutes)
\- Exploring Jupyter Notebook (Ungraded Lab, 60 minutes)
\- Poker Simulation (Ungraded Lab, 60 minutes)
\- Probability Simulations (Ungraded Lab, 60 minutes)

Week 3: Operations Pipelines: DevOps, DataOps, MLOps
\- Cloud Developer Workspace Advantage (Video, 4 minutes, Preview module)
\- Key Components of GitHub Ecosystem (Video, 3 minutes)
\- Using GitHub Templates (Video, 2 minutes)
\- Demo of GitHub Codespaces (Video, 6 minutes)
\- GPU Code Whisperer (Video, 1 minute)
\- Fine-Tuning with Hugging Face (Video, 3 minutes)
\- Demo of GitHub Copilot (Video, 8 minutes)
\- GitHub Actions (Video, 3 minutes)
\- Pipelines for DataOps using Step Functions (Video, 16 minutes)
\- Query Databricks Pipeline (Video, 26 minutes)
\- Building Data Ingestion Pipelines on AWS (Video, 2 minutes)
\- Marco Polo Step Functions (Video, 8 minutes)
\- Transforming Data in Transit on AWS (Video, 2 minutes)
\- Demo AWS Batch Service (Video, 3 minutes)
\- Serverless Data Engineering Pipelines on AWS (Video, 1 minute)
\- Building Python Functions from Zero (Video, 138 minutes)
\- Building a Python NLP Project with Python Fire (Video, 43 minutes)
\- Extending Google Cloud Functions (Video, 10 minutes)
\- Using Google Cloud Functions (Video, 6 minutes)
\- Deploying a Rust Azure Function with GitHub Actions (Video, 14 minutes)
\- Key Terms (Reading, 10 minutes)
\- Additional Readings (Reading, 10 minutes)
\- Lesson Reflection (Reading, 10 minutes)
\- Key Terms (Reading, 10 minutes)
\- Additional Readings (Reading, 10 minutes)
\- Lesson Reflection (Reading, 10 minutes)
\- Key Terms (Reading, 10 minutes)
\- Additional Readings (Reading, 10 minutes)
\- Lesson Reflection (Reading, 10 minutes)
\- Operations Pipelines: DevOps, DataOps, MLOps (Quiz, 30 minutes)
\- Marco Polo Python (Ungraded Lab, 60 minutes)
\- Greedy Optimizations (Ungraded Lab, 60 minutes)

Week 4: End to End MLOps and AIOps
\- Containerized Microservices (Video, 2 minutes, Preview module)
\- Containerized Continuous Delivery (Video, 8 minutes)
\- Containerized Machine Learning (Video, 39 minutes)
\- Containerized End-to-End Machine Learning (Video, 3 minutes)
\- Building Distroless Containers (Video, 8 minutes)
\- Use AI to Write AI (Video, 1 minute)
\- Learn Key Skills for Python DevOps with Copilot (Video, 171 minutes)
\- Amazon CodeWhisperer vs. GitHub Copilot (Video, 56 minutes)
\- Enabling AI Workflows (Video, 1 minute)
\- Prototyping AI APIs (Video, 14 minutes)
\- Using Transfer Learning (Video, 2 minutes)
\- Assimilate OpenAI Technology using Streamlit (Video, 50 minutes)
\- Key Terms (Reading, 10 minutes)
\- Additional Readings (Reading, 10 minutes)
\- Lesson Reflection (Reading, 10 minutes)
\- Key Terms (Reading, 10 minutes)
\- Additional Readings (Reading, 10 minutes)
\- Lesson Reflection (Reading, 10 minutes)
\- Key Terms (Reading, 10 minutes)
\- Additional Readings (Reading, 10 minutes)
\- Lesson Reflection (Reading, 10 minutes)
\- End to End Containerized MLOps (Quiz, 30 minutes)
\- Convert Code with AI (Ungraded Lab, 60 minutes)
\- Build a Hugging Face Gradio Web Application (Ungraded Lab, 60 minutes)

Week 5: Rust for MLOps: The Practical Transition from Python to Rust
\- Introduction to Switching to Rust from Python (Video, 4 minutes, Preview module)
\- Introduction to Rust Lecture Notes (Video, 4 minutes)
\- Configure Rust for AWS Cloud9 (Video, 8 minutes)
\- GitHub Copilot Enabled Rust Programming (Video, 9 minutes)
\- Using Rust Packaging for Web Development (Video, 9 minutes)
\- Comparing Energy Efficiency of Rust vs. Python (Video, 5 minutes)
\- Comparing Rust vs. Python for MLOps (Video, 7 minutes)
\- Continuous Integration for Rust with GitHub Actions (Video, 7 minutes)
\- Demo Unit Testing Rust (Video, 6 minutes)
\- Building a Deduplication Tool with Rust (Video, 9 minutes)
\- Zero Shot Classification Rust Hugging Face (Video, 9 minutes)
\- Rust GPU Hugging Face Translator (Video, 6 minutes)
\- PyTorch Stable Diffusion Rust with GPU (Video, 7 minutes)
\- Rust PyTorch Demo (Video, 7 minutes)
\- Building GPU Stress Test (Video, 7 minutes)
\- Using Rust ONNX with EFS for AWS Lambda (Video, 9 minutes)
\- Onboarding to GCP with Python and Rust via CloudShell (Video, 8 minutes)
\- Run Rust Actix Microservice with Google Cloud Run (Video, 25 minutes)
\- Build and Deploy Rust Microservice via Google Cloud Run (Video, 7 minutes)
\- Monitoring and Logging with Rust for Google App Engine (Video, 3 minutes)
\- Load Testing a Rust Microservice (Video, 5 minutes)
\- Building a Containerized Rust Microservice with AWS (Video, 8 minutes)
\- AWS Step Functions with Rust (Video, 6 minutes)
\- Deploy an App Engine Rust Microservice (Video, 5 minutes)
\- Size Calculator in AWS S3 (Video, 4 minutes)
\- Key Terms (Reading, 10 minutes)
\- Additional Readings (Reading, 10 minutes)
\- Lesson 1 Reflection: Introduction to Rust (Reading, 10 minutes)
\- Key Terms (Reading, 10 minutes)
\- Additional Readings (Reading, 10 minutes)
\- External Lab: Hugging Face Chatbot Arena (Reading, 10 minutes)
\- Lesson Reflection (Reading, 10 minutes)
\- Key Terms (Reading, 10 minutes)
\- Additional Readings (Reading, 10 minutes)
\- Lesson Reflection (Reading, 10 minutes)
\- Next Steps (Reading, 10 minutes)
\- Rust for MLOps (Quiz, 30 minutes)
\- Quiz: Leveling Up from Python to Rust: An Introduction (Quiz, 30 minutes)
\- Quiz: Build MLOps Solutions using Rust (Quiz, 30 minutes)
\- Quiz: Build Cloud Solutions using Rust (Quiz, 30 minutes)
\- Hello World Rust (Ungraded Lab, 60 minutes)
\- Rust Cargo Lambda (Ungraded Lab, 60 minutes)
\- Rust Sandbox: Discovering Rust (Ungraded Lab, 60 minutes)

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