Python Essentials for MLOps
Python Essentials for MLOps (Machine Learning Operations) is a course designed to provide learners with the fundamental Python skills needed to succeed in an MLOps role. This course covers the basics of the Python programming language, including data types, functions, modules and testing techniques. It also covers how to work effectively with data sets and other data science tasks with Pandas and NumPy. Through a series of hands-on exercises, learners will gain practical experience working with Python in the context of an MLOps workflow.
Monthly Subscription Starting at AED 99 + VAT
- Level Professional
- Duration 23 hours
- Course by Duke University
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Offered by
About
Python Essentials for MLOps (Machine Learning Operations) is a course designed to provide learners with the fundamental Python skills needed to succeed in an MLOps role. This course covers the basics of the Python programming language, including data types, functions, modules and testing techniques. It also covers how to work effectively with data sets and other data science tasks with Pandas and NumPy. Through a series of hands-on exercises, learners will gain practical experience working with Python in the context of an MLOps workflow. By the end of the course, learners will have the necessary skills to write Python scripts for automating common MLOps tasks. This course is ideal for anyone looking to break into the field of MLOps or for experienced MLOps professionals who want to improve their Python skills.Modules
About the Course
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1
Videos
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4
Readings
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2
Discussion
2
Discussions
- Meet and Greet (optional)
- Let Us Know if Something's Not Working
1
Videos
- Meet your Course Instructor: Alfredo Deza
4
Readings
- Connect with your instructor
- Meet your Supporting Instructor: Noah Gift
- Course Structure and Discussion Etiquette
- Getting Started and Course Best Practices
Working with Variables and Types
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6
Videos
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2
Readings
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1
Lab
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1
Assignment
1
Assignment
- Quiz-Variables and Types
1
Labs
- Variables and Types
6
Videos
- Lesson Introduction: Variables and Types
- Variables and Assignments
- Working with Different Data Types
- Conditionals and Evaluations
- Catching and Handling Exceptions
- Lesson Recap: Variables and Types
2
Readings
- Key Terms
- Lesson Reflection
Introduction to Python Data Structures
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7
Videos
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4
Readings
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1
Lab
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1
Assignment
1
Assignment
- Quiz-Introduction to Python Data Structures
1
Labs
- Data Structures
7
Videos
- Lesson Introduction: Python Data Structures
- Introduction to Lists
- Creating and Iterating Over Lists
- Introduction to Dictionaries
- Creating and Iterating Over Dictionaries
- Other Data Structures: Tuples and Sets
- Lesson Recap: Python Data Structures
4
Readings
- Key Terms
- Minimal Python book: Storing Data
- Lesson Reflection
- Key Terms
Adding and Extracting Data from Data Structures
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5
Videos
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2
Readings
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2
Lab
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2
Assignment
2
Assignment
- Quiz-Adding and Extracting Data from Data Structures
- Week 1-Final Graded Quiz-Python Basics
2
Labs
- Adding and Extracting Data
- Sandbox Week One
5
Videos
- Lesson Introduction: Adding and Extracting Data
- Adding Data to Lists
- Extracting Data from Lists
- Extracting Data from Dictionaries
- Lesson Recap: Adding and Extracting Data
2
Readings
- Key Terms
- Lesson Reflection
Working with Functions
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5
Videos
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4
Readings
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2
Lab
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1
Assignment
1
Assignment
- Quiz-Functions
2
Labs
- Functions
- Python Functions Sandbox
5
Videos
- Lesson Introduction: Working with Functions
- Function Structure and Values
- Function Arguments
- Variable and Keyword Arguments
- Lesson Recap: Working with Functions
4
Readings
- Key Terms
- Minimal Python book: Create functions
- Generators
- Lesson Reflection
Building Classes and Methods
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6
Videos
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4
Readings
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2
Lab
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2
Assignment
2
Assignment
- Quiz-Ungraded Lab Python Classes Sandbox
- Quiz-Building Classes and Methods
2
Labs
- Python Classes
- Python Classes Sandbox
6
Videos
- Lesson Introduction: Building Classes and Methods
- Introduction to Classes
- Using a Constructor
- Adding Methods
- Class Inheritance
- Lesson Recap: Building Classes and Methods
4
Readings
- Key Terms
- Inheritance
- Ungraded Lab Sandbox Key Terms
- Lesson Reflection
Modules and Advanced Usage
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6
Videos
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4
Readings
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1
Lab
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2
Assignment
2
Assignment
- Python Functions and Classes
- Quiz-Modules
1
Labs
- Python Modules
6
Videos
- Lesson Introduction: Modules and Advanced Usages
- Introduction to Python Modules
- Working with Imports
- Working with Python Scripts
- Virtual Environments and Dependencies
- Lesson Recap: Modules and Advanced Usages
4
Readings
- Key Terms
- Python for Beginners Learning Path
- Understanding 3rd Party Packaging
- Lesson Reflection
Introduction to Testing
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5
Videos
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2
Readings
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1
Lab
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1
Assignment
1
Assignment
- Quiz-Introduction to Testing
1
Labs
- Testing Conventions
5
Videos
- Lesson Introduction: Writing and Executing Tests
- Motivations for Testing in Python
- Testing Conventions
- Testing with pytest
- Lesson Recap: Writing and Executing Tests
2
Readings
- Key Terms
- Lesson Reflection
Writing Useful Tests
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6
Videos
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2
Readings
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1
Lab
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1
Assignment
1
Assignment
- Quiz: Writing Useful Tests
1
Labs
- Testing with Pytest
6
Videos
- Lesson Introduction: Writing Useful Tests
- Using Plan Asserts in pytest
- Writing Test Classes
- Test Classes vs. Test Functions
- Parameterizing Tests
- Lesson Recap: Writing Useful Tests
2
Readings
- Key Terms
- Lesson Reflection
Testing Failures
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6
Videos
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2
Readings
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1
Lab
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2
Assignment
2
Assignment
- Python Testing
- Quiz- Testing Failures
1
Labs
- Test Failures
6
Videos
- Lesson Introduction: Testing Failures
- Test Failure Output
- Python Debugging with PDB
- Other pytest Runner Options
- pytest Fixtures
- Lesson Recap: Testing Failures
2
Readings
- Key Terms
- Lesson Reflection
Basic Pandas Usage
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6
Videos
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2
Readings
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1
Lab
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1
Assignment
1
Assignment
- Quiz - Basic Pandas Usage
1
Labs
- Introduction to Pandas
6
Videos
- Lesson Introduction: Basic Pandas Usage
- Introduction to Pandas
- Loading Data into Pandas
- Writing Data from Pandas DataFrames
- Exploratory Analysis with Pandas
- Lesson Recap: Basic Pandas Usage
2
Readings
- Key Terms
- Lesson Reflection
Working with DataFrames
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6
Videos
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2
Readings
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1
Lab
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1
Assignment
1
Assignment
- Quiz-Working with DataFrames
1
Labs
- Pandas DataFrames
6
Videos
- Lesson Introduction: Working with DataFrames
- Common DataFrame Operations
- Manipulating Text in DataFrames
- Applying Functions with Pandas
- Visualizing Data with Pandas
- Lesson Recap: Working with DataFrames
2
Readings
- Key Terms
- Lesson Reflection
NumPy Basics
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5
Videos
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2
Readings
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1
Lab
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2
Assignment
2
Assignment
- Pandas and NumPy
- Quiz-NumPy Basics
1
Labs
- NumPy
5
Videos
- Lesson Introduction: NumPy Basics
- Introduction to NumPy Arrays
- Common NumPy Array Operations
- More NumPy Array Operations
- Lesson Recap: NumPy Basics
2
Readings
- Key Terms
- Lesson Reflection
Working with APIs and SDKs
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7
Videos
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2
Readings
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1
Assignment
1
Assignment
- Quiz-Working with APIs and SDKs
7
Videos
- Lesson Introduction: APIs and SDKs
- Installing Azure Command-Line Interface (CLI)
- AzureML Studio with Python
- Hugging Face Transformers
- Hugging Face Datasets
- Azure Open Datasets
- Lesson Recap: APIs and SDKs
2
Readings
- Key Terms
- Lesson Reflection
Automation with Command-Line Tools
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8
Videos
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2
Readings
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1
Assignment
1
Assignment
- Quiz-Automating with the CLI
8
Videos
- Lesson Introduction: Automation with Command-Line Tools
- Creating a Single File Script
- Using the ArgParse Framework
- Declaring Dependencies
- Using the Click Framework
- Packaging your Project
- Solving a Machine Learning Problem with a CLI Tool
- Lesson Recap: Automation with Command-Line Tools
2
Readings
- Key Terms
- Lesson Reflection
Building Machine Learning APIs
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7
Videos
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4
Readings
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4
Lab
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2
Assignment
2
Assignment
- Automation with Python
- Quiz-Working with GitHub GPU MLOps Template
4
Labs
- MLOps CLI
- Linux Desktop Sandbox
- Jupyter Final Sandbox
- VSCode Final Sandbox
7
Videos
- Lesson Introduction: Building Machine Learning APIs
- Introduction to Flask Framework
- Building an API with Flask
- Introduction to the FastAPI Framework
- Building an API with FastAPI
- Python API Best Practices
- Lesson Recap: Building Machine Learning APIs
4
Readings
- Key Terms
- External Lab: GPU Powered MLOps Template
- Lesson Reflection
- Next Steps
Auto Summary
"Python Essentials for MLOps" is a focused and practical course tailored for individuals aiming to excel in the field of Machine Learning Operations (MLOps). This course delves into the crucial Python programming skills essential for success in MLOps roles. Learners will explore fundamental concepts such as data types, functions, modules, and testing techniques. Additionally, the course emphasizes effective data handling with powerful libraries like Pandas and NumPy. Guided by Coursera, participants will engage in hands-on exercises, gaining real-world experience in applying Python within an MLOps workflow. By the course's conclusion, learners will be equipped to write Python scripts that automate various MLOps tasks, enhancing their efficiency and capability in the field. Ideal for aspiring MLOps professionals and experienced individuals seeking to refine their Python expertise, this professional-level course spans approximately 1380 minutes. Subscriptions are available through Starter and Professional plans, providing flexible options to fit different learning needs. Embark on this learning journey to master Python for MLOps and advance your career in Data Science & AI.
Noah Gift
Alfredo Deza