Best Python Machine Learning Courses Online & Certification (April 2025)

Becoming a Machine Learning Engineer is no longer challenging in today’s era. Various online resources can help you master the technology at your own pace. Machine Learning is a part of AI that aims at coding machines to experience and learn from the environment. It also aims to perform any task automatically without being programmed for particular tasks.

I hope you are also here to learn this exciting field and expand your knowledge. Today, we will share the list of Best Python Machine Learning Courses.

Before you should know that, these courses require basic skills of Python to further advance your skills in Machine Learning.

Why is learning Python important for Machine Learning?

As per the report, there has been a 74 % average annual growth rate in the jobs created for AI and Machine Learning Professionals since 2015. AI and ML specialists will remain among the top jobs profiles in 2021.  While complex algorithms and versatile workflows are used for machine learning, Python is the simplest programming language that allows developers to write reliable systems. 

Python is used by one of the most well-known firms on the internet, Amazon, for a number of tasks on its platform. incorporated into Amazon’s system for suggesting goods and deals, which employs artificial intelligence and machine learning to assess customer interests and generate suggestions. If you understand Python, this article is beneficial for you. 

But if you think you are a beginner in machine learning, I would like you to check the bunch of Best Machine Learning with Python courses to start your journey. 

Our product recommendations are unbiased and based on an independent review process. We may receive a commission for links to recommended partners. See our advertiser disclosure for more information.

---

Best Python Machine Learning Courses, Certification, Tutorials, Training, Classes Online

• Best Overall Applied Machine Learning in Python [Coursera]
  
  
• Best Runner-up Intro to Machine Learning with PyTorch [Udacity]
  
  
• Best for Beginner Machine Learning with Python (IBM) [Coursera]
  
  
• Best for Intermediate Machine Learning with Python [DataCamp]
  
  
• Best Budget option Python for Data Science and Machine Learning Bootcamp [Udemy]
  
  
• Best for Professional Machine Learning with Python: A Practical Introduction [edX]

Applied Machine Learning in Python [Coursera]

Coursera Machine Learning Python Course introduces you to machine learning techniques and methods. You will learn how Machine Learning is descriptive than Statistics and how to use Scikit learn toolkit. You are going to learn basic concepts like clustering, regression. Then, you will end this course with advanced techniques such as building ensembles and predictive models. You will be able to identify the difference between supervised and unsupervised learning.

Course Instructor

Kenny Collins is the creator and instructor of this Applied Machine Learning in Python who will guide you all the way. It is designed to understand how to identify which technique you need to apply for particular datasets. Before taking this course, I recommend you to take Applied Data Science with Python Course on Coursera for better understanding.

What You’ll Learn

This Applied Machine Learning Course is designed to be completed in four modules.

1. Intro to Scikit Learn: This lesson will help you discover key fundamental concepts of machine learning and how to process and implement using the scikit-learn library, to explain fundamental machine learning concepts.
   
   
2. Supervised Learning(Part 1): This module explores a wider range of supervised learning techniques, including classification and regression.
   
   
3. Evaluation: The module will introduce methods of  model evaluation and model selection to better understand and improve the performance of your machine learning models.
   

Supervised Machine Learning (Part 2): The supervised learning techniques will be covered in this week’s module such as ensembling of trees, neural networks, and deep learning.

Pros & Cons

Key Highlights & USPs

• Learn the fundamentals of Machine Learning, tasks, and workflow using the Python Scikit learn library.
  
  
• How supervised learning methods work with both classification and regression.
  
  
• Discover different approaches for creating predictive models.
  
  
• Understand how to evaluate and optimize the performance of your machine learning models.
  
  
• Learn about the critical problem of data leakage in Machine Learning and how to detect it.
  
  
• Build features using Python programming to carry out data analysis.

Who is it for?

This Machine Learning in Python Course is for data scientists and programmers who are interested enough to enhance their job profile and prove their competency. Upon completion, you will be able to differentiate between supervised (classification) and unsupervised (clustering) techniques, decide which technique to use for a specific dataset, design features to address that need, and write Python code to perform an analysis.

Intro to Machine Learning with PyTorch [Udacity]

Udacity is the most recommended platform to kickstart your career in Machine Learning. You will learn important aspects of machine learning, starting from data manipulation to unsupervised and supervised algorithms. You will get practical experience by applying your programming skills to hands-on projects.

Course Instructor

Intro to Machine Learning Program created to write algorithms and perform machine learning tasks under the guidance of instructors and machine learning experts. You are going to learn about how to use Python’s library -Pytorch for Machine Learning.

What You’ll Learn

This Udacity Nanodegree Program of Machine Learning is designed into three lessons for students to learn machine learning algorithms. 

1. Supervised Learning: You will learn about supervised learning in this session, a popular category of model creation techniques. Complete this lesson by using supervised learning for a project related to charity organization.
   
   
2. Introduction to Neural Networks with Pytorch:  In this lesson, you will master the fundamentals of designing and training neural networks in PyTorch. Finally, it will help you use fundamentals for creating your own image classifier.
   
   
3. Unsupervised Learning: This lecture will introduce you to unsupervised learning techniques and how to apply them for various problem domains. 

Pros & Cons

Key Highlights & USPs

• Learn Python Skills and write your codes for machine learning models.
  
  
• Understand the concept of supervised learning and the common class methods that are used to construct models.
  
  
• Introduce you to deep learning concepts and neural network design.
  
  
• Get the training in Pytorch for writing codes for machine learning models.
  
  
• Implement unsupervised learning methods for different kinds of real-world problems.
  
  
• Improve performance by applying acquired skills to projects and coding exercises on hands-on projects related to real-world scenarios.

Who is it for?

This Udacity Machine Learning Python program is intended for students with intermediate-level Python programming skills and a little bit of knowledge of Machine Learning. If you are not a Python programmer, you can check this link of the Best Python Online Course. By the end, this Online Machine Learning Program will help you master tech skills that companies want and push you towards your goals.

Machine Learning with Python (IBM) [Coursera]

Machine Learning is the hottest technology to start learning in this era of Artificial Intelligence. Coursera designed a perfect opportunity to dive into the world of Machine learning and how it is changing the real world. This Machine Learning with Python Course will teach you the basics of Machine Learning and how it is implemented in different fields such as banking, health care, telecommunication, and health care. You will understand how to use Python libraries in machine learning algorithms and building machine learning models.

Course Instructor

This IBM Machine Learning Professional Certificate is taught by the two data scientists – Saeed Aghbozorgi and Joseph. They created the course for students to get a general overview of how Machine Learning is used for cancer detection, predicting economic trends, and customer churns. It will enable you to improve your skill sets by adding Python to your portfolio.

What You’ll Learn

This Coursera Python for Machine Learning Online Course is divided into 5 modules, namely:

1. Introduction to Machine Learning: This module will explain applications of Machine Learning in different sectors, including banking, healthcare, and more.
   
   
2. Regressions:  This module covers Linear, Non-linear, Simple, and Multiple regression. Then, you apply all these methods to two datasets and evaluate your regression model.
   
   
3. Classification: This session will help you practice classification algorithms, such as KNN, Decision Trees, Logistic Regression, and SVM.
   
4. Linear Classification: In this module, you will determine applications of Linear classification and understand how to use it to measure accuracy metrics.
   
   
5. Clustering: This module will teach you about k-means clustering, explain how it operates, and show you how to use it for consumer segmentation.
   
   
6. Final Project: You will complete a project in this module that is based on what you have already learnt and submit a report on your project for peer review.

Pros & Cons

Key Highlights & USPs

• Learn the purpose of Machine Learning and topics such as supervised vs unsupervised learning.
   
• Get a brief introduction about regression and how to apply it for evaluating machine learning models.
  
• Learn about different classification algorithms such as KNN, Decision Trees, Logistic Regression, and SVM.
  
  
• How to use clustering for real-life problems and understand three main types of clustering including partitioned-based, Hierarchical, and Density-based clustering.
  
  
• Discover how recommended engines work for Google, Youtube, or any content-based site. What is Content-based and collaborative filtering?
  
  
• You get to perform what you have learned on real-life examples.

Who is it for?

This Python Machine Learning Course is for Data Analysts and Python programmers who are eager to specialize in Machine Learning and earn an IBM digital badge upon successful Completion. You will graduate from this course with abilities that are suitable for the job market and a certificate in machine learning that will serve as documentation of your proficiency.

Machine Learning with Python [DataCamp]

This Machine Learning with Python Tutorial offers you a must-learning opportunity to dive into the world of Machine Learning. You will get started with Machine Learning fundamentals in Python. In this track, you will introduce the two main types of machine learning methods such Supervised learning including classification and regression, and Unsupervised learning including clustering, and dimensionality.

Course Instructor

A series of Datacamp Machine Learning with Python Tutorials will be taught by several instructors from data science and machine learning backgrounds. It is prepared to sharpen your skills and strengthen your profile to participate in this emerging industry. It comprises five courses that can help you to start an excellent career by the end.

Pros & Cons

Key Highlights & USPs

• Learn how to build predictive models using Supervised Learning.
  
  
• Evaluate machine learning models using Scikit Learn Python Library to see how well they perform.
  
  
• Know how to use unsupervised learning methods in Python for clustering, transforming, visualizing, and extracting data. From unlabeled datasets.
  
  
• Grasp a firm knowledge of linear classification like logistic regressions and SVM.
  
  
• Introduce Deep Learning using Keras 2.0 and the fundamentals of neural networks design.
  
  
• Gain practice experience by building a model to automatically classify items in a school budget.

Who is it for?

Python developers and data scientists can opt any course to enhance their resume and look out for better job opportunities. It includes a top machine learning python course on Datacamp that help you become proficient in implementing machine learning concepts with Python.

Python for Data Science and Machine Learning Bootcamp [Udemy]

This Python Data Science and Machine Learning Bootcamp offer you the top-recommended Machine learning tools and Python libraries such as Pandas, Seaborn, Numpy, Scikit-Learn, TensorFlow, etc. You will learn about the general-purpose programming language and its use in analyzing data, creating a visualization, and writing algorithms for machine learning. This Data Science with Python course covers all the topics to get a deep knowledge of how data science and how machine learning uses Python to solve the world’s problems.

Course Instructor

Jose Portilla is the author and instructor who included each piece of information to enhance your knowledge. It is packed with hundreds of HD video lectures and detailed code notebooks for every lecture. This Comprehensive program has both beginner and intermediate-level courses to learn how Python libraries for Data Science works.

Pros & Cons

Key Highlights & USPs

• This Udemy Machine Learning with Python Course includes 27 sections and 165 video lectures
  
  
• Learn to use Pandas for Data Analysis and Seaborn for statistical plots.
  
  
• Develop an understanding of machine learning fundamentals such as logistic regression, neural networks, linear regressions, and so on.
  
  
• Learn How to use Scikit-Learn for machine learning tasks.
  
  
• Use Python’s libraries like Matplotlib and Seaborn for Data Visualization.
  
  
• Create in-built interactive and dynamic visualization to visualize patterns in datasets.
  
  
• Understand Natural Language Processing and Spam filters to work with machine learning models.
  
  
• Get full lifetime access to 25 hours of on-demand video, 13 articles, and five downloadable resources.

Who is it for?

The Python Machine Learning tutorial is for those who have experience in programming and developers who want to build a rewarding career in Data science and machine learning. Upon completion, you will develop skills of writing Python programs, creating data visualizations, and usage of Machine Learning algorithms.

Machine Learning with Python: A Practical Introduction [edX]

IBM Machine Learning with Python Professional Certificate will be beneficial for you to learn how to uncover hidden insights and predict future trends. You will get to use machine learning tools to automate real-world tasks. It is the best time to study Data Science and Machine Learning for making better business decisions. You can get started with the fundamentals of Machine Learning concepts such as regression, classification, and recommended systems. You will study suitable Python libraries for machine learning.

Course Instructor

Dr. Saeed Aghabozorgi is a data scientist to teach you this Machine learning with Python tutorial. He designed the course to motivate the students to take Machine Learning as a rewarding career and enhance their skill sets to get high-paying jobs.

Pros & Cons

Key Highlights & USPs

• Complete this edX Machine Learning Course in 5 modules, namely:
  • Introduction to Machine Learning
  • Regression
  • Classification
  • Unsupervised learning
  • Recommender systems
    
    
• Learn about the two types of Machine learning Methods – Supervised and Unsupervised Learning.
  
  
• You will know about the difference between Supervised and Unsupervised Learning.
  
  
• Discover two main methods of Supervised Learning – Classification and Regression.
  
  
• How to use Clustering and Dimensionality to write Unsupervised learning algorithms.
  
  
• Get an overview of how statistical modeling relates to Machine Learning and what is the main difference between them.
  
  
• Gain practical experience by working on how content-based and collaborative filtering are used for recommended engines.

Who is it for?

This intermediate machine learning python course is for professionals and Python programmers familiar with basic Python and knowledge of probability. You can take the Best Python for Data Science course before enrolling in this certificate program. Once you complete this certification, you will earn an IBM badge to showcase your skills and enhance your expertise in supervised and unsupervised learning with Python.

Machine Learning Certification Training using Python [Edureka]

Edureka Python Machine Learning Certification is the ultimate pack of gaining valuable expertise to become a part of the high-in-demand profession. It covers all the aspects of Machine Learning such as regressions, clustering, decision trees, and more. This Machine Learning using Python Course includes all the different classes of machine learning algorithms like supervised, unsupervised. You will get to solve real-life case studies related to social media, health care, the Aviation industry, etc.

Course Instructor

Edureka created this Machine Learning Certification Training using Python for Analysts, data scientists, and programmers to improve Python skills by writing algorithms for machine learning. The main goal of this course is to introduce data science to Machine Learning and see how it helps to analyze data.

Pros & Cons

Key Highlights & USPs

• Learn the importance of Machine learning and how to implement Python programming language.
  
  
• Discover how to automate real-life scenarios using machine learning algorithms.
  
  
• Learn machine learning techniques and methods for predictive modeling.
  
  
• Get a brief on Reinforcement learning which is an important aspect of Artificial Intelligence.
  
  
• Develop knowledge about time series analysis to forecast dependent variables based on time.
  
  
• How to convert weaker algorithms to stronger ones.
  
  
• Understand how to approach a project and implement a Project end to end.

Who is it for?

This machine learning python training is for aspiring machine learning engineers, data analysts, information architects, python programmers to gain expertise. The prerequisites for this Machine Learning Course include intermediate-level experience with Python and know the fundamentals of Data Analysis beforehand. After completing this Python certification course, you will be able to perform techniques to analyze and process companies data and be able to secure a lucrative job.

---

FAQ