Master Python for Seamless MLOps: From Fundamentals to Automation and Workflow Efficiency. Master Python for efficient Machine Learning Operations by building strong programming foundations, creating MLOps automation, and gaining applicable experience.
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- Fundamentals of Python programming: Data types, functions, modules
- Testing techniques
- Data manipulation and analysis
- Work with datasets using Pandas
- Leveraging NumPy for data science
- Hands-on coding exercises
- Apply Python in MLOps workflows
This comprehensive course covers the essential Python skills for succeeding in MLOps roles. Through hands-on exercises, you'll learn:
- Core Python programming concepts
- Data manipulation and analysis
- Containerization of ML models
- GitHub Actions for automation
Whether you're new to MLOps or an experienced professional, this course equips you with the foundational Python skills to excel in machine learning operations roles.
This course is part of the Machine Learning Operations Professional Certificate.
What you'll learn
- Interact with APIs and SDKs to build command-line tools and HTTP APIs to solve and automate Machine Learning problems.
- Work with logic in Python, assigning variables and using different data structures.
- Write, run and debug tests using Pytest to validate your work.
Syllabus
Introduction to Python
• Module 1 (9 hours to complete)
◦ Meet your Course Instructor: Alfredo Deza (video, 1 minute)
◦ Lesson Introduction: Variables and Types (video, 0 minutes)
◦ Variables and Assignments (video, 5 minutes)
◦ Working with Different Data Types (video, 7 minutes)
◦ Conditionals and Evaluations (video, 7 minutes)
◦ Catching and Handling Exceptions (video, 6 minutes)
◦ Lesson Recap: Variables and Types (video, 0 minutes)
◦ Lesson Introduction: Python Data Structures (video, 0 minutes)
◦ Introduction to Lists (video, 3 minutes)
◦ Creating and Iterating Over Lists (video, 3 minutes)
◦ Introduction to Dictionaries (video, 3 minutes)
◦ Creating and Iterating Over Dictionaries (video, 4 minutes)
◦ Other Data Structures: Tuples and Sets (video, 4 minutes)
◦ Lesson Recap: Python Data Structures (video, 0 minutes)
◦ Lesson Introduction: Adding and Extracting Data (video, 0 minutes)
◦ Adding Data to Lists (video, 3 minutes)
◦ Extracting Data from Lists (video, 4 minutes)
◦ Extracting Data from Dictionaries (video, 4 minutes)
◦ Lesson Recap: Adding and Extracting Data (video, 0 minutes)
◦ Connect with your instructor (reading, 10 minutes)
◦ Meet your Supporting Instructor: Noah Gift (reading, 10 minutes)
◦ Course Structure and Discussion Etiquette (reading, 10 minutes)
◦ Getting Started and Course Best Practices (reading, 10 minutes)
◦ Key Terms (reading, 10 minutes)
◦ Lesson Reflection (reading, 10 minutes)
◦ Key Terms (reading, 10 minutes)
◦ Minimal Python book: Storing Data (reading, 10 minutes)
◦ Lesson Reflection (reading, 10 minutes)
◦ Key Terms (reading, 10 minutes)
◦ Key Terms (reading, 10 minutes)
◦ Lesson Reflection (reading, 10 minutes)
◦ Quiz-Variables and Types (quiz, 30 minutes)
◦ Quiz-Introduction to Python Data Structures (quiz, 30 minutes)
◦ Quiz-Adding and Extracting Data from Data Structures (quiz, 30 minutes)
◦ Week 1-Final Graded Quiz-Python Basics (quiz, 30 minutes)
◦ Meet and Greet (optional) (discussion prompt, 10 minutes)
◦ Let Us Know if Something's Not Working (discussion prompt, 10 minutes)
◦ Variables and Types (ungraded lab, 60 minutes)
◦ Data Structures (ungraded lab, 60 minutes)
◦ Adding and Extracting Data (ungraded lab, 60 minutes)
◦ Sandbox Week One (ungraded lab, 60 minutes)
Python Functions and Classes
• Module 2 (10 hours to complete)
◦ Lesson Introduction: Working with Functions (video, 0 minutes)
◦ Function Structure and Values (video, 3 minutes)
◦ Function Arguments (video, 5 minutes)
◦ Variable and Keyword Arguments (video, 5 minutes)
◦ Lesson Recap: Working with Functions (video, 0 minutes)
◦ Lesson Introduction: Building Classes and Methods (video, 0 minutes)
◦ Introduction to Classes (video, 7 minutes)
◦ Using a Constructor (video, 6 minutes)
◦ Adding Methods (video, 4 minutes)
◦ Class Inheritance (video, 5 minutes)
◦ Lesson Recap: Building Classes and Methods (video, 0 minutes)
◦ Lesson Introduction: Modules and Advanced Usages (video, 0 minutes)
◦ Introduction to Python Modules (video, 3 minutes)
◦ Working with Imports (video, 4 minutes)
◦ Working with Python Scripts (video, 4 minutes)
◦ Virtual Environments and Dependencies (video, 5 minutes)
◦ Lesson Recap: Modules and Advanced Usages (video, 0 minutes)
◦ Key Terms (reading, 10 minutes)
◦ Minimal Python book: Create functions (reading, 10 minutes)
◦ Generators (reading, 10 minutes)
◦ Lesson Reflection (reading, 10 minutes)
◦ Key Terms (reading, 10 minutes)
◦ Inheritance (reading, 10 minutes)
◦ Ungraded Lab Sandbox Key Terms (reading, 10 minutes)
◦ Lesson Reflection (reading, 10 minutes)
◦ Key Terms (reading, 10 minutes)
◦ Python for Beginners Learning Path (reading, 10 minutes)
◦ Understanding 3rd Party Packaging (reading, 10 minutes)
◦ Lesson Reflection (reading, 10 minutes)
◦ Quiz-Functions (quiz, 30 minutes)
◦ Quiz-Ungraded Lab Python Classes Sandbox (quiz, 30 minutes)
◦ Quiz-Building Classes and Methods (quiz, 30 minutes)
◦ Quiz-Modules (quiz, 30 minutes)
◦ Python Functions and Classes (quiz, 30 minutes)
◦ Functions (ungraded lab, 60 minutes)
◦ Python Functions Sandbox (ungraded lab, 60 minutes)
◦ Python Classes (ungraded lab, 60 minutes)
◦ Python Classes Sandbox (ungraded lab, 60 minutes)
◦ Python Modules (ungraded lab, 60 minutes)
Testing in Python
• Module 3 (7 hours to complete)
◦ Lesson Introduction: Writing and Executing Tests (video, 0 minutes)
◦ Motivations for Testing in Python (video, 5 minutes)
◦ Testing Conventions (video, 8 minutes)
◦ Testing with pytest (video, 6 minutes)
◦ Lesson Recap: Writing and Executing Tests (video, 0 minutes)
◦ Lesson Introduction: Writing Useful Tests (video, 0 minutes)
◦ Using Plan Asserts in pytest (video, 5 minutes)
◦ Writing Test Classes (video, 4 minutes)
◦ Test Classes vs. Test Functions (video, 3 minutes)
◦ Parameterizing Tests (video, 7 minutes)
◦ Lesson Recap: Writing Useful Tests (video, 0 minutes)
◦ Lesson Introduction: Testing Failures (video, 0 minutes)
◦ Test Failure Output (video, 5 minutes)
◦ Python Debugging with PDB (video, 5 minutes)
◦ Other pytest Runner Options (video, 3 minutes)
◦ pytest Fixtures (video, 6 minutes)
◦ Lesson Recap: Testing Failures (video, 0 minutes)
◦ Key Terms (reading, 10 minutes)
◦ Lesson Reflection (reading, 10 minutes)
◦ Key Terms (reading, 10 minutes)
◦ Lesson Reflection (reading, 10 minutes)
◦ Key Terms (reading, 10 minutes)
◦ Lesson Reflection (reading, 10 minutes)
◦ Quiz-Introduction to Testing (quiz, 30 minutes)
◦ Quiz: Writing Useful Tests (quiz, 30 minutes)
◦ Quiz- Testing Failures (quiz, 30 minutes)
◦ Python Testing (quiz, 30 minutes)
◦ Testing Conventions (ungraded lab, 60 minutes)
◦ Testing with Pytest (ungraded lab, 60 minutes)
◦ Test Failures (ungraded lab, 60 minutes)
Introduction to Pandas and NumPy
• Module 4 (7 hours to complete)
◦ Lesson Introduction: Basic Pandas Usage (video, 0 minutes)
◦ Introduction to Pandas (video, 5 minutes)
◦ Loading Data into Pandas (video, 5 minutes)
◦ Writing Data from Pandas DataFrames (video, 3 minutes)
◦ Exploratory Analysis with Pandas (video, 6 minutes)
◦ Lesson Recap: Basic Pandas Usage (video, 0 minutes)
◦ Lesson Introduction: Working with DataFrames (video, 0 minutes)
◦ Common DataFrame Operations (video, 7 minutes)
◦ Manipulating Text in DataFrames (video, 4 minutes)
◦ Applying Functions with Pandas (video, 3 minutes)
◦ Visualizing Data with Pandas (video, 4 minutes)
◦ Lesson Recap: Working with DataFrames (video, 0 minutes)
◦ Lesson Introduction: NumPy Basics (video, 0 minutes)
◦ Introduction to NumPy Arrays (video, 5 minutes)
◦ Common NumPy Array Operations (video, 3 minutes)
◦ More NumPy Array Operations (video, 6 minutes)
◦ Lesson Recap: NumPy Basics (video, 0 minutes)
◦ Key Terms (reading, 10 minutes)
◦ Lesson Reflection (reading, 10 minutes)
◦ Key Terms (reading, 10 minutes)
◦ Lesson Reflection (reading, 10 minutes)
◦ Key Terms (reading, 10 minutes)
◦ Lesson Reflection (reading, 10 minutes)
◦ Quiz - Basic Pandas Usage (quiz, 30 minutes)
◦ Quiz-Working with DataFrames (quiz, 30 minutes)
◦ Quiz-NumPy Basics (quiz, 30 minutes)
◦ Pandas and NumPy (quiz, 30 minutes)
◦ Introduction to Pandas (ungraded lab, 60 minutes)
◦ Pandas DataFrames (ungraded lab, 60 minutes)
◦ NumPy (ungraded lab, 60 minutes)
Applied Python for MLOps
• Module 5 (9 hours to complete)
◦ Lesson Introduction: APIs and SDKs (video, 0 minutes)
◦ Installing Azure Command-Line Interface (CLI) (video, 6 minutes)
◦ AzureML Studio with Python (video, 6 minutes)
◦ Hugging Face Transformers (video, 6 minutes)
◦ Hugging Face Datasets (video, 8 minutes)
◦ Azure Open Datasets (video, 6 minutes)
◦ Lesson Recap: APIs and SDKs (video, 0 minutes)
◦ Lesson Introduction: Automation with Command-Line Tools (video, 0 minutes)
◦ Creating a Single File Script (video, 4 minutes)
◦ Using the ArgParse Framework (video, 6 minutes)
◦ Declaring Dependencies (video, 3 minutes)
◦ Using the Click Framework (video, 7 minutes)
◦ Packaging your Project (video, 4 minutes)
◦ Solving a Machine Learning Problem with a CLI Tool (video, 8 minutes)
◦ Lesson Recap: Automation with Command-Line Tools (video, 0 minutes)
◦ Lesson Introduction: Building Machine Learning APIs (video, 0 minutes)
◦ Introduction to Flask Framework (video, 6 minutes)
◦ Building an API with Flask (video, 8 minutes)
◦ Introduction to the FastAPI Framework (video, 7 minutes)
◦ Building an API with FastAPI (video, 6 minutes)
◦ Python API Best Practices (video, 7 minutes)
◦ Lesson Recap: Building Machine Learning APIs (video, 0 minutes)
◦ Key Terms (reading, 10 minutes)
◦ Lesson Reflection (reading, 10 minutes)
◦ Key Terms (reading, 10 minutes)
◦ Lesson Reflection (reading, 10 minutes)
◦ Key Terms (reading, 10 minutes)
◦ External Lab: GPU Powered MLOps Template (reading, 10 minutes)
◦ Lesson Reflection (reading, 10 minutes)
◦ Next Steps (reading, 10 minutes)
◦ Quiz-Working with APIs and SDKs (quiz, 30 minutes)
◦ Quiz-Automating with the CLI (quiz, 30 minutes)
◦ Quiz-Working with GitHub GPU MLOps Template (quiz, 30 minutes)
◦ Automation with Python (quiz, 30 minutes)
◦ MLOps CLI (ungraded lab, 60 minutes)
◦ Linux Desktop Sandbox (ungraded lab, 60 minutes)
◦ Jupyter Final Sandbox (ungraded lab, 60 minutes)
◦ VSCode Final Sandbox (ungraded lab, 60 minutes)
