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Seven weeksUp to five hours per week
Starts May 12, 2025
Online course with independent learning and live drop-in sessions

Python has become the de facto language for machine learning due to its user-friendly nature, robust ecosystem, and widespread adoption within the community. Learning how you can use Python for machine learning tasks will give you a competitive edge in the job market and provide you with the necessary tools to excel in this rapidly evolving field.

AI and machine learning jobs have jumped by almost 75% over the past four years. 
Source: John Terra, Simplilearn, July 7 2023

Before you jump into machine learning though, it’s important to know the basics. This course is an essential starting point for machine learning with an approach that is accessible and rooted in practical value. You’ll learn vital pre-machine learning skills, with a focus on data preparation, to avoid common data science risks, like “garbage in, garbage out.”  

Perfect for beginners and professionals looking to advance into roles that include machine learning, this course is designed to introduce you to Python, a programming language known for its simplicity and readability. Python has an extensive library that includes packages specifically designed for machine learning, such as NumPy, Pandas, Scikit-learn, SciPy, and Statsmodels. Through a series of modules, you’ll gain hands-on experience with Python's libraries, syntax, data structures, and functions relevant to machine learning tasks.    

Upon completion of the course, you’ll have a solid understanding of proper data preparation and how to get the results you’re seeking.  

 

 

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Machine Learning Practitioner Certificate

Machine Learning Project Specialist Certificate

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Hear from our learners

I am an experienced software developer (C#/Java) but using Python for the first time. I found the course challenging but I also learned a lot. I would recommend this course!

Deniz Berkin
Python for Machine Learning Certificate Course

 


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Course

Python for Machine Learning

Language

English

Department

LEARN

Course Description

Overview 

 

Python has become the de facto language for machine learning due to its user-friendly nature, robust ecosystem, and widespread adoption within the community. Learning how you can use Python for machine learning tasks will give you a competitive edge in the job market and provide you with the necessary tools to excel in this rapidly evolving field.

Before you jump into machine learning though, it’s important to know the basics. This course is an essential starting point for machine learning with an approach that is accessible and rooted in practical value. You’ll learn vital pre-machine learning skills, with a focus on data preparation, to avoid common data science risks, like “garbage in, garbage out.”  

 

Perfect for beginners and professionals looking to advance into roles that include machine learning, this course is designed to introduce you to Python, a programming language known for its simplicity and readability. Python has an extensive library that includes packages specifically designed for machine learning, such as NumPy, Pandas, Scikit-learn, SciPy, and Statsmodels. Through a series of modules, you’ll gain hands-on experience with Python's syntax, data structures, and functions relevant to machine learning tasks.  

 

Upon completion of the course, you’ll have a solid understanding of proper data preparation and how to get the results you’re seeking.

 

Who Should Enroll 

  • Aspiring data analysts or data scientists looking to build essential machine learning skills and grow their toolkits.
  • Programmers and developers looking to add Python to their list of programming languages.
  • Statisticians who are new to machine learning.

 

What you will learn 

  • Explain the practical benefits and uses of machine learning: Gain an understanding of the real-world applications of machine learning and its significance in various fields such as business, healthcare, finance, marketing, and more. Recognize the difficulties with operationalizing machine learning models and build a broader understanding of the applicability of machine learning. 
  • Create a machine learning portfolio in Jupyter Notebook to show potential employers: Learn how to set up and configure your Python environment using Jupyter Notebook, leveraging the Anaconda distribution platform. Explore the benefits of Jupyter Notebook for interactive coding, data exploration, and documentation, and understand how Anaconda simplifies package management and environment creation. 
  • Identify key components of data preparation in machine learning: Understand the crucial role of data preparation in machine learning pipelines. Identify key components such as data cleaning, missing values, feature scaling, categorical variable encoding, and common manipulations. Recognize the significance of data preprocessing for improving model performance and achieving reliable results. 
  • Gain hands-on experience with some of Python's packages and libraries: Learning the Python libraries and packages NumPy, Pandas, Scikit-learn, SciPy, and Statsmodels is crucial for a well-rounded proficiency in data science and machine learning. From data handling and preprocessing to modeling and analysis, these libraries and packages are the building blocks of modern data-driven decision-making and advanced research.

 

Course Details 

  • Expert instruction from University of Waterloo faculty.
  • Learn at your own pace with weekly independent online learning and hands-on exercises.
  • Drop-in sessions twice weekly via Zoom where you can ask questions and receive instructor support on key course concepts:
    • Wednesdays, 2 - 2:30 p.m. ET
    • Wednesdays, 8:30 - 9 p.m. ET
  • Access to online discussion boards.
  • Up to five hours each week (including drop-in sessions, hands-on exercises, discussion boards, and independent study). 

 

System requirements

  • Anaconda (software that you are required to install)

0379 - 006

Python for Machine Learning

  • available
  • May 12, 2025 to Jun 29, 2025

Schedule

Online - May 12, 2025 to Jun 29, 2025

Distance Learning Session

Details

  • Contact hours: 0
  • CEUs: 0 CEUs
  • Language: English
  • Fees:
    Fee AmountFee Name
    $499.00
  • Drop Request Deadline: May 26, 2025
  • Transfer Request Deadline: Please refer to the withdrawal and transfer policy for details on transfer requests.

0379 - 006

Python for Machine Learning

  • available
  • May 12, 2025 to Jun 29, 2025

Schedule

Online - May 12, 2025 to Jun 29, 2025

Distance Learning Session

Details

  • Contact hours: 0
  • CEUs: 0 CEUs
  • Language: English
  • Fees:
    Fee AmountFee Name
    $499.00
  • Drop Request Deadline: May 26, 2025
  • Transfer Request Deadline: Please refer to the withdrawal and transfer policy for details on transfer requests.