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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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Python Functions and Classes
This week, you will learn how to create functions, classes, and methods. These are the basis of almost any program you might create with Python. Functions and classes are useful for organizing code, increasing maintainability and code reuse.
Testing in Python
This week, you will learn the basics of Python testing. From a brief overview of the standard library to using a more modern approach with Pytest, one of the most popular testing libraries in Python. By the end of this week, you should be comfortable working with existing tests, creating new tests, and debugging test failures.
Introduction to Pandas and NumPy
This week, you will learn how to work with data using Pandas and NumPy. From loading and reading datasets from different sources to plotting graphs and exploring common problems in data. Pandas will allow you to perform transformations and export your data into different formats, and NumPy will boost your ability to work with numerical data.
Applied Python for MLOps
This week you’ll grasp the basics of how to create and use APIs with Python using HTTP and command-line tools. We’ll go through all the details you need to know to create your own command-line tools and HTTP APIs to expose Machine Learning models.

Good to know

Know what's good
, what to watch for
, 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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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.
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  • 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.
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.
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  • 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
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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.
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  • 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.
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  • 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.
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  • 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.
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  • 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.
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  • 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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.

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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.

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