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Python Essentials for MLOps

Noah Gift and Alfredo Deza

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.

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What's inside

Syllabus

Introduction to Python
This week, you will learn how to effectively use variables, logic, and Python’s data structures to load, persist, and iterate over data. You will apply these data structures to solve different problems as well as extract data from them.
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Traffic lights

Read about what's good
what should give you pause
and possible dealbreakers
Explores foundational theory and application of Python, Pandas, and NumPy, which is standard in industry
Teaches the essentials of Python for MLOps, which helps learners succeed in an MLOps role
Provides practical experience with Python in the context of an MLOps workflow
Covers the basics of the Python programming language, including data types, functions, modules, and testing techniques
Develops skills to write Python scripts for automating common MLOps tasks
Core audience may include experienced MLOps professionals or individuals looking to break into the field

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Reviews summary

Python for mlops: essential and practical foundation

Learners say this course provides a strong, practical foundation in Python, specifically tailored for MLOps. Many find the hands-on exercises and projects highly valuable for gaining real-world experience, making it particularly useful for those new to MLOps or needing to solidify their Python skills. While the course excels at teaching core Python concepts, Pandas, NumPy, and Pytest, some experienced Python users may find the initial content too basic. However, the unique focus on creating APIs for Machine Learning models is frequently highlighted as a significant strength, preparing students for practical automation in MLOps. The lectures are generally clear, though the pace can feel quite fast for absolute beginners.
Covers Pytest and API creation for ML models.
"The section on Pytest was incredibly useful and something often overlooked in other general Python courses."
"Learning to create HTTP APIs for machine learning models was a unique and highly practical takeaway for me."
"I particularly enjoyed the Applied Python for MLOps week, as it directly addressed real-world deployment challenges."
Focuses on practical application with effective labs.
"The hands-on coding and projects are the strongest part of the course for me; they truly solidified my understanding."
"I really appreciated the practical exercises; they allowed me to immediately apply what I learned."
"Unlike other courses, this one delivers actual coding tasks that are relevant to MLOps."
Builds essential Python skills for MLOps effectively.
"This course really helped me bridge my Python knowledge to MLOps concepts, giving me a solid start."
"I feel much more confident in writing Python scripts for MLOps tasks after completing this course."
"It's a great intro for anyone looking to understand the Python side of machine learning operations."
Lectures are clear but can move at a fast pace.
"The instructor explains concepts very clearly, but I sometimes had to pause and rewatch due to the fast pace."
"While the content is well-structured, a complete beginner might find the speed of delivery challenging."
"I found the lectures engaging, but occasionally wished for more pauses or slower explanations on complex topics."
Excellent for beginners, potentially basic for experts.
"If you're new to MLOps or need a Python refresher, this course is perfect. For advanced users, it might be a bit slow at first."
"As someone with a fair bit of Python experience, the initial modules felt too basic for my needs."
"I found it to be a fantastic introduction, but a more experienced colleague felt some sections were introductory for them."

Activities

Be better prepared before your course. Deepen your understanding during and after it. Supplement your coursework and achieve mastery of the topics covered in Python Essentials for MLOps with these activities:
Seek a mentor in the Python community
Identify and connect with an experienced Python professional who can provide guidance, support, and advice on your learning journey, offering valuable insights and perspectives to enhance your understanding and accelerate your progress.
Browse courses on Python
Show steps
  • Attend Python meetups and conferences to network with potential mentors.
  • Reach out to Python professionals on LinkedIn or other online platforms.
Review 'Python Crash Course' by Eric Matthes
Read and review 'Python Crash Course' to gain a comprehensive understanding of Python's core concepts, including variables, data types, control flow, and functions.
View Python Crash Course, 3rd Edition: A Hands-On,... on Amazon
Show steps
  • Read through the book, taking notes on important concepts.
  • Work through the hands-on exercises in the book to apply your knowledge.
  • Complete the end-of-chapter quizzes to test your understanding.
Join a Python study group
Collaborate with peers in a Python study group to exchange knowledge, work on assignments together, and enhance your understanding through group discussions and problem-solving.
Browse courses on Python
Show steps
  • Find or create a Python study group.
  • Attend group meetings regularly and participate actively.
  • Discuss course topics, share resources, and help each other with challenges.
Five other activities
Expand to see all activities and additional details
Show all eight activities
Practice Python coding exercises
Solve coding exercises in Python to reinforce your understanding of the basics of Python programming, such as data types, functions, and data structures.
Browse courses on Python
Show steps
  • Find a collection of Python coding exercises online or in a textbook.
  • Choose a few exercises that cover the topics you want to practice.
  • Work through the exercises step-by-step, testing your code as you go.
  • Review your solutions and identify any areas where you need to improve.
Follow tutorials on Python data analysis with Pandas
Complete tutorials on data analysis with Pandas to enhance your skills in loading, cleaning, and manipulating data in Python.
Browse courses on Pandas
Show steps
  • Find a series of tutorials on Python data analysis with Pandas.
  • Follow the tutorials step-by-step, working through the examples.
  • Apply what you learn to your own data analysis projects.
Build a simple Python application
Engage in a hands-on project where you develop a Python application from scratch, providing a practical outlet for your Python skills and reinforcing your understanding of the language's features and functionalities.
Browse courses on Python
Show steps
  • Plan the functionality and design of your application.
  • Write the Python code for your application.
  • Test and debug your application.
  • Deploy and share your application.
Write a blog post on a Python topic
Create a blog post that delves into a specific Python topic, providing a comprehensive explanation and sharing your insights, which will help you to solidify your understanding of the subject matter and enhance your communication skills.
Browse courses on Python
Show steps
  • Choose a Python topic that you are knowledgeable about.
  • Research and gather information on the topic.
  • Write a well-structured blog post that explains the topic clearly.
  • Publish your blog post on a relevant platform.
Create a Python script to automate an MLOps task
Develop a Python script that automates a common MLOps task, such as data preprocessing or model deployment, to enhance your hands-on experience in applying Python skills to real-world MLOps scenarios.
Browse courses on MLOps
Show steps
  • Identify an MLOps task that can be automated.
  • Design the architecture of your Python script.
  • Write and test the code for your script.
  • Deploy and monitor your script in a production environment.

Career center

Learners who complete Python Essentials for MLOps will develop knowledge and skills that may be useful to these careers:
Machine Learning Engineer
Machine Learning Engineers build, deploy, and maintain machine learning models to solve business problems. Python Essentials for MLOps is a good foundational course for someone considering a career as a Machine Learning Engineer. It covers how to load, persist, and iterate over data; work effectively with data sets and other data science tasks with Pandas and NumPy; and perform transformations and export data into different formats.
See salaries and explore the career path for Machine Learning Engineer
Data Scientist
Data Scientists use scientific methods and machine learning algorithms to extract knowledge and insights from data. Their work helps businesses make informed decisions. Python Essentials for MLOps is a helpful foundational course for anyone considering a career as a Data Scientist. It covers not only the basics of the Python programming language, but also how to load, persist, and iterate over data; work effectively with data sets and other data science tasks with Pandas and NumPy; and perform transformations and export data into different formats.
See salaries and explore the career path for Data Scientist
Data Engineer
Data Engineers design, build, and maintain the infrastructure needed to store and process data. Python Essentials for MLOps would provide a foundation in Python for someone considering a career as a Data Engineer. In particular, the course's coverage of how to load, persist, and iterate over data; work effectively with data sets and other data science tasks with Pandas and NumPy; and perform transformations and export data into different formats would be useful.
See salaries and explore the career path for Data Engineer
Data Analyst
Data Analysts gather, clean and analyze data to uncover insights for businesses to make informed decisions. Python Essentials for MLOps would teach the fundamentals of Python and help build a foundation for working with data. The course will teach how to load, persist, and iterate over data; work effectively with data sets and other data science tasks with Pandas and NumPy; and perform transformations and export data into different formats.
See salaries and explore the career path for Data Analyst
Software Engineer
Software Engineers design and develop software programs that fulfill business needs. They are often responsible for the ongoing maintenance and improvement of these software programs. A course on Python, like Python Essentials for MLOps, would provide the foundation needed to write programs used in this field. The course covers data types, functions, modules and testing techniques. It also covers how to work with data sets and other data science tasks with Pandas and NumPy.
See salaries and explore the career path for Software Engineer
Software Developer
Software Developers design, develop, and test software applications. Python Essentials for MLOps would teach the fundamentals of Python. The course covers data types, functions, modules and testing techniques. It also covers how to work with data sets and other data science tasks with Pandas and NumPy.
See salaries and explore the career path for Software Developer
Business Analyst
Business Analysts help businesses identify and solve problems by using data and technology. Python Essentials for MLOps would provide a foundation in Python for someone considering a career as a Business Analyst. In particular, the course's coverage of how to load, persist, and iterate over data; work effectively with data sets and other data science tasks with Pandas and NumPy; and perform transformations and export data into different formats would be useful.
See salaries and explore the career path for Business Analyst
Web Developer
Web Developers design and develop websites and other web applications. Python Essentials for MLOps would be a helpful foundational course for someone considering a career as a Web Developer. It covers the basics of the Python programming language, as well as how to load, persist, and iterate over data; work effectively with data sets and other data science tasks with Pandas and NumPy; and perform transformations and export data into different formats.
See salaries and explore the career path for Web Developer
Technical Writer
Technical Writers create user guides, technical documentation, and other content that explains the use of technical products and services. Python Essentials for MLOps would provide a foundation in Python for someone considering a career as a Technical Writer. In particular, the course's coverage of how to load, persist, and iterate over data; work effectively with data sets and other data science tasks with Pandas and NumPy; and perform transformations and export data into different formats would be useful.
See salaries and explore the career path for Technical Writer
Database Administrator
Database Administrators design, implement, and maintain databases. Python Essentials for MLOps may be helpful for someone considering a career as a Database Administrator, as it would provide a foundation in Python and how to work with data. In particular, the course's coverage of how to load, persist, and iterate over data; work effectively with data sets and other data science tasks with Pandas and NumPy; and perform transformations and export data into different formats would be useful.
See salaries and explore the career path for Database Administrator
Product Manager
Product Managers define the vision for a product and oversee its development and launch. Python Essentials for MLOps may be helpful for someone considering a career as a Product Manager, as it would provide a foundation in Python and how to work with data. In particular, the course's coverage of how to load, persist, and iterate over data; work effectively with data sets and other data science tasks with Pandas and NumPy; and perform transformations and export data into different formats would be useful.
See salaries and explore the career path for Product Manager
Financial Analyst
Financial Analysts help businesses make informed financial decisions. Python Essentials for MLOps may be helpful for someone considering a career as a Financial Analyst, as it would provide a foundation in Python and how to work with data. In particular, the course's coverage of how to load, persist, and iterate over data; work effectively with data sets and other data science tasks with Pandas and NumPy; and perform transformations and export data into different formats would be useful.
See salaries and explore the career path for Financial Analyst
Security Analyst
Security Analysts protect computer systems and networks from cyberattacks. Python Essentials for MLOps may be helpful for someone considering a career as a Security Analyst, as it would provide a foundation in Python and how to work with data. In particular, the course's coverage of how to load, persist, and iterate over data; work effectively with data sets and other data science tasks with Pandas and NumPy; and perform transformations and export data into different formats would be useful.
See salaries and explore the career path for Security Analyst
Operations Research Analyst
Operations Research Analysts use mathematical and analytical methods to solve business problems. Python Essentials for MLOps may be helpful for someone considering a career as an Operations Research Analyst, as it would provide a foundation in Python and how to work with data. In particular, the course's coverage of how to load, persist, and iterate over data; work effectively with data sets and other data science tasks with Pandas and NumPy; and perform transformations and export data into different formats would be useful.
See salaries and explore the career path for Operations Research Analyst
Project Manager
Project Managers plan, organize, and execute projects to achieve specific goals. Python Essentials for MLOps may be helpful for someone considering a career as a Project Manager, as it would provide a foundation in Python and how to work with data. In particular, the course's coverage of how to load, persist, and iterate over data; work effectively with data sets and other data science tasks with Pandas and NumPy; and perform transformations and export data into different formats would be useful.
See salaries and explore the career path for Project Manager

Reading list

We've selected 11 books that we think will supplement your learning. Use these to develop background knowledge, enrich your coursework, and gain a deeper understanding of the topics covered in Python Essentials for MLOps.
Cover image
Python Crash Course, 2nd Edition
Save
Provides a comprehensive overview of the Python programming language, covering the basics of data types, variables, operators, and control flow. It also includes a section on object-oriented programming, which is essential for building more complex Python applications.
Python Crash Course, 2nd Edition: A Hands-On,...
Paperback
$$
Python Crash Course, 2nd Edition: A Hands-On,...
Kindle Edition
$$
Cover image
Hands-On Machine Learning with Scikit-Learn, Keras,...
Save
Comprehensive guide to machine learning using Python. It covers a wide range of topics, including data preprocessing, model selection, and evaluation. It also provides a deep dive into deep learning using TensorFlow and Keras.
Hands-On Machine Learning with Scikit-Learn, Keras,...
Paperback
$$
Hands-On Machine Learning with Scikit-Learn, Keras,...
Paperback
$$$
Hands-On Machine Learning with Scikit-Learn, Keras,...
Kindle Edition
$$
Cover image
Build a Large Language Model (From Scratch)
Save
Comprehensive guide to using Python for machine learning. It covers a wide range of topics, including data preprocessing, model selection, and evaluation. It also provides a deep dive into using scikit-learn, TensorFlow, and Keras for machine learning.
Build a Large Language Model (From Scratch)
Paperback
Check
Build a Large Language Model (From Scratch)
Kindle Edition
Check
Cover image
Deep Learning with Python, Second Edition
Save
Comprehensive guide to deep learning using Python. It covers a wide range of topics, including neural networks, convolutional neural networks, and recurrent neural networks. It also provides a deep dive into using TensorFlow and Keras for deep learning.
Deep Learning with Python, Second Edition
Paperback
$$
Deep Learning with Python, Second Edition
Kindle Edition
$$
Cover image
Fluent Python
Save
Comprehensive guide to Python best practices. It covers a wide range of topics, including code readability, error handling, and performance optimization. It valuable resource for Python developers of all levels.
Fluent Python: Clear, Concise, and Effective...
Paperback
$$
Fluent Python: Clear, Concise, and Effective...
Paperback
$$$
Fluent Python
Kindle Edition
$$
Cover image
On Java 8
Save
Comprehensive guide to testing in Python. It covers a wide range of topics, including unit testing, integration testing, and performance testing. It also provides a deep dive into using Pytest and other testing frameworks.
On Java 8
Paperback
Check
On Java 8
Kindle Edition
Check
Cover image
Python for Data Analysis
Save
Comprehensive guide to using Python for data analysis. It covers a wide range of topics, including data cleaning, data manipulation, and data visualization. It also provides a deep dive into using Pandas and NumPy for data analysis.
Python for Data Analysis
Paperback
Check
Python for Data Analysis
Kindle Edition
Check
Cover image
Pandas for Everyone
Save
Practical guide to using Pandas for data analysis. It covers a wide range of topics, including data loading, data cleaning, and data manipulation. It also provides a deep dive into using Pandas for data visualization.
Pandas for Everyone: Python Data Analysis (Addison...
Paperback
$$
Pandas for Everyone: Python Data Analysis (Addison...
Paperback
$$
Pandas for Everyone: Python Data Analysis (Addison...
Kindle Edition
$$
Pandas for Everyone: Python Data Analysis (Addison...
Kindle Edition
$$
Cover image
Automate the Boring Stuff with Python, 2nd Edition
Save
Practical guide to using Python for automating everyday tasks. It covers a wide range of topics, including web scraping, data analysis, and system administration. It provides a great foundation for learning how to use Python for MLOps tasks.
Automate the Boring Stuff with Python, 2nd Edition:...
Paperback
$$
Automate the Boring Stuff with Python, 2nd Edition:...
Kindle Edition
$$
Cover image
Machine Learning with PyTorch and Scikit-Learn
Save
Practical guide to machine learning using Python. It covers a wide range of topics, including data preprocessing, model selection, and evaluation. It also provides a deep dive into using scikit-learn and TensorFlow for machine learning.
Machine Learning with PyTorch and Scikit-Learn:...
Kindle Edition
$$
Cover image
Python Distilled
Save
Collection of Python recipes for solving common programming problems. It covers a wide range of topics, including data structures, algorithms, and web development. It valuable reference for Python developers of all levels.
Python Distilled
Paperback
Check
Python Distilled
Kindle Edition
Check

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Course image
Effort
5 weeks of study, 4-6 hours/week
Level
Intermediate
Via
Coursera
Institution
Duke University
Instructors
Noah Gift
Alfredo Deza
Language
English
Transcripts
Español Français Português Deutsch Italiano 中文 العربية 한국어 日本語 हिंदी Nederlands Svenska Pусский Türkçe Polski Ελληνικά українська мова magyar nyelv Bahasa Indonesia ไทย қазақша اُردُو, فارسی বাংলা پښتو آذربایجان دیلی
This course belongs to a collection called MLOps | Machine Learning Operations. It's comprised of four courses:
  1. MLOps Tools: MLflow and Hugging Face
  2. Python Essentials for MLOps (viewing)
  3. DevOps, DataOps, MLOps
  4. MLOps Platforms: Amazon SageMaker and Azure ML
Traffic lights
Read about what's good
what should give you pause
and possible dealbreakers
Explores foundational theory and application of Python, Pandas, and NumPy, which is standard in industry
Teaches the essentials of Python for MLOps, which helps learners succeed in an MLOps role
Provides practical experience with Python in the context of an MLOps workflow
Covers the basics of the Python programming language, including data types, functions, modules, and testing techniques
Develops skills to write Python scripts for automating common MLOps tasks
Core audience may include experienced MLOps professionals or individuals looking to break into the field
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