Best Machine Learning Courses & Certificates (September 2023)

Have you heard a lot about machine learning? Do you get to listen to how machine learning is impacting our daily lives? One of the quickest-growing sectors in information technology is machine learning, which uses computers to process data that would otherwise be impossible to comprehend by human intelligence. Making a career in this demanding field will help you stand out in the crowd.  As a programmer or developer, if you are curious about this highly in-demand technology and looking for the best machine learning course to teach yourself, then you have come to the right place.

Why is Machine Learning important?

A growing number of big tech companies are offering generous salaries to machine learning specialists who want to join their teams. According to the US Bureau Labor of Statistics, 11.5 million jobs will be created by 2026 in data science. In 2022, the top emerging role was data scientist and analysts around the world as per World Economic Forum.

Based on IDC estimates, AI investment grew 19.6% annually through 2023 and reached $432.8 billion, surpassing $500 billion in 2023. The market demand of machine learning experts is growing rapidly and requires highly technical knowledge and a strong mindset. So, I have reviewed courses from top platforms and created a list of the best machine learning courses and programs. 

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 Machine Learning Courses, Certification, Classes, Tutorials

These are our picks for the best machine learning courses:

• Best Overall Become a Machine Learning Engineer for Microsoft Azure by Microsoft [Udacity]
  
  
• Best Runner-up Machine Learning Certification by Stanford University [Coursera]
  
  
• Best for Working Professional Applied Machine Learning Course [Columbia Engineering]
  
  
• Best for Google Cloud Machine Learning on Google Cloud Specialization [Coursera]
  
  
• Best Budget option Machine Learning A-Z™: Hands-On Python & R In Data Science [Udemy]
  
  
• Best for Basics Introduction to Machine Learning [Datacamp]
  
  
• Best Free Intro to Machine Learning [Udacity]
  
  
• Best for Python Machine Learning with Python: A Practical Introduction [edX]
  
  
  
• Best for Data Science Machine Learning Data Science Certification from Harvard University [edX]

Become a Machine Learning Engineer for Microsoft Azure by Microsoft [Udacity]

If you are searching for how to get into machine learning and become a machine learning engineer, this course is all you need to know. It is the best way to learn and strengthen machine learning skills using Microsoft Azure. This Udacity machine learning program enables the students to build advanced machine learning models and deploy them using open source tools and frameworks.

Course Instructor

The Machine Learning Engineer for Microsoft Azure provides the best learning experience to enhance their skills and apply them on hands-on projects inspired by real-life examples. This nanodegree machine learning program was created by data scientists and software developers.

What You’ll Learn

1. Using Azure Machine Learning: This course will introduce you to machine learning and how to use it for critical business operations. Also, discuss the method of configuring machine learning pipelines in Azure and identify use cases for Automated Machine Learning.
   
   
2. Machine Learning Operations: This course will help you understand the key concepts of machine learning including deploying models, enabling Application Insights, identifying problems in logs, and harnessing Azure’s Pipelines.
   
   
3. Capstone Project: This Nanodegree program capstone gives you the chance to apply your knowledge to a challenging situation. The solution requires the use of Azure’s Automated Machine Learning as well as HyperDrive in order to solve the issue. As a final step, you will have to deploy the model as a web service and test the endpoint of the model.

Pros & Cons

Key Highlights & USPs

• Learn to run complex machine learning tasks with accessible in-built Azure labs inside the Udacity classroom.
  
  
• Get to know how to design, evaluate and validate machine learning models. This machine learning curriculum covers the fundamentals of shipping machine learning models into production.
  
  
• Develop your practice skills by performing on real-world projects and get feedback from experienced reviewers.
  
  
• Knowledgeable mentors are always available to give full-time technical support and keep you on track.

Who is it for?

This Machine Learning Nanodegree Program is for those who want to advance their career and strengthen machine learning skills. It is the best option for learners with prior experience in Python, Machine learning, and Statistics.  With the completion of this online machine learning program, you will master the skills of using Azure ML pipelines, Azure data services, machine learning methods, and cloud strategy and security for organizations.

Machine Learning Certification by Stanford University [Coursera]

This Stanford Machine Learning Course is the most highly-rated course on Coursera. It introduces key topics such as machine learning, data mining, and statistical pattern recognition. You’ll gain a practical approach to learn the machine learning techniques and practice to implement them effectively. Machine learning has become a critical component to build progress towards Human-level AI.

Course Instructor

This Andrew Ng Machine Learning program is probably the best machine learning certification taught by AI & ML pioneer and Co-founder of Coursera, Andrew Ng, to simplify the complicated machine learning concepts for the students. That’s also an excellent tool to test your algorithms.

What You’ll Learn

This course is part of the Machine Learning Specialization and divided into three modules for each week. The following modules will help you learn these topics:

1. Introduction to Machine Learning: This module will introduce you to the fundamentals of machine learning and learn about its applications. You will learn how to implement basic and practice concepts through exercises.
   
   
2. Regression with multiple input variables: This module covers linear regression for handling multiple input features and vectorization, feature scaling, engineering, and polynomial regression for improving the training and performance of your model.
   
   
3. Classification: This lesson will teach you how to predict categories using the logistic regression model and other methods of supervised learning. Get a grasp of how to deal with a regularization challenge as well.

Pros & Cons

Key Highlights & USPs

• Get to learn theoretical topics of machine learning and gain practical experience by applying those techniques to solve complex problems.
  
  
• Understand the core concepts of how to use mathematics behind all the Machine learning programs.
  
  
• Enables you to practice Silicon Valley’s best innovation that pertains to machine learning and AI.
  
  
• Test all the learning algorithms before implementing them for building robots, web search tools, medical informatics, audio-based applications, etc.
  
  
• Provide full lifetime access to video lectures, notes, and assignments to enhance your knowledge.

Who is it for?

This machine learning course adds value to beginners and data scientists’ careers. It is the best way to master key concepts and gain the practical knowledge of applying machine learning to real-world problems. Upon completion, you will have the opportunity to break-through into AI or get a job as a machine learning specialist.

Applied Machine Learning Course [Columbia Engineering]

The Machine Learning Course Online will introduce you to various techniques of supervised and unsupervised learning. You will learn how to use those techniques using the Python programming language. In this machine learning course with a certificate, you will understand key methods to build real-world applications, including recommender system and classification models. You will first work on your foundational skills in Python, followed by the supervised and unsupervised techniques. 

Course Instructor

DR. JOHN W. PAISLEY is the instructor of this Applied Machine Learning Course from Coursera. He has a  Ph.D. from Duke and is working as a researcher in the Computer Science departments at Princeton University and UC Berkeley. He always focuses on developing models for large-scale text and image processing applications. Also, he worked with Bayesian models and used posterior inference techniques to address big data problems.

Pros & Cons

Key Highlights & USPs

• This Machine Learning Online Tutorial from Columbia University is divided into two parts and each comprises 12 modules to teach models and methods in machine learning.
  
  
• Make a model that learns from your data and uses regression models to predict unknown outputs.
  
  
• Analyze datasets such as email messages and categorize them as spam or not.
  
  
• Extract hidden patterns from large amounts of data using unsupervised models such as topic models or recommender systems
  
  
• Determine hidden parameters in data to improve your model’s prediction accuracy.
  
  
• Predict outcomes based on probabilistic models that incorporate risks and uncertainties in real-life situations.
  
  
• Get unlimited access to 240+ faculty video lectures, 45 quizzes, 18 discussion boards, 12 application projects, and online training sessions.

Who is it for?

This Online Machine Learning Course is designed for those seeking to implement or lead machine learning projects or incorporate machine learning into their software applications. Students will be tested on their math skills before the course begins. At the end of the course, you will be able to use machine learning algorithms and applications to solve enterprise-level problems. As a Data Science or Machine Learning professional, your skill set will be enhanced as you take the Applied Machine Learning course.

Machine Learning A-Z™: Hands-On Python & R In Data Science [Udemy]

This Machine Learning udemy Program is the best way to learn Machine learning algorithms. It will teach you how to create algorithms in Python and R. You will gain in-depth knowledge of complex algorithms from tutorial videos and develop skills to write them. It opens the best way to learn machine learning online and enables you to use techniques for personal purposes. It provides lessons to create added value for the business.

Course Instructor

Curators of this machine learning course are two data scientists who shared their pool of knowledge to simplify the subject and make it easy for the participants to walk into the world of machine learning. You will get to understand from A to Z of this high-tech technology.

Pros & Cons

Key Highlights & USPs

• This Udemy Machine Learning and Data Science Course consists of 46 sections and 382 video lectures, enough content to create machine learning algorithms in Python and R.
  
  
• Learn complex theory, algorithms, and coding libraries in the simplest way.
  
  
• Get the full support of the instructors to master the skills of building machine learning models and know how to use them for solving problems.
  
  
• Enables you to make accurate predictions using data science and analytics.
  
  
• Guide your way through the course to handle specific topics like NLP ( Natural Language Processing) and Deep Learning.
  
  
• Get hands-on projects based on real-life examples to develop the skills.
  
  
• Get full lifetime access to 73 articles, 38 downloadable resources, and code templates to use for your projects.

Who is it for?

This top machine learning course is available for all the students and intermediate-level professionals who have at least high school knowledge in math and computers. Having no interest in coding but can opt this course to boost your career. In the end, you will start a job as a data analyst or data scientist and add value to the business by using powerful machine learning tools. 

Machine Learning on Google Cloud Specialization [Coursera]

This Coursera Machine Learning Certification program is the ultimate course for you to get an idea about machine learning and how it works. You will learn machine learning using Google cloud platform and do experiments on real-world examples. This machine learning specialization course guides through the key concepts and what kinds of problems can be solved using ML techniques.

Course Instructor

The Machine Learning with TensorFLow Course promises to teach you the importance of Machine learning and assist you to build machine learning models. This Google cloud training course was created to let the learners know how Google thinks about machine learning. It’s not only about data, but logic.

What You’ll Learn

This course is divided into 5 courses which gives you detailed application of machine learning and its key concepts.

1. How Google does Machine Learning: This course covers training custom models, building component pipelines, and performing both online and batch predictions. Also, we discuss how to convert a candidate’s use case to be driven by machine learning.
   
   
2. Launching into Machine Learning: The course begins with a discussion of improving data quality and performing exploratory data analysis. You will learn how to set up, train, and deploy a Vertex AI AutoML model without coding.
   
   
3. TensorFlow on Google Cloud: This course will teach you how to design and develop a TensorFlow input data pipeline, how to build ML models using TensorFlow and Keras, how to improve the accuracy of ML models, and how to write ML models for scaled use.
   
   
4. Feature Engineering: During this course, you’ll learn how to preprocess and transform positive versus negative features for optimal use in your models. In addition, it shares content on feature engineering using BigQuery ML, Keras, and TensorFlow.
   
   
5. Machine Learning in the Enterprise: This course will help you determine data management, governance, and learn to identify when to utilize BigQuery ML, custom training, and Vertex AutoML.

Pros & Cons

Key Highlights & USPs

• Learn how to write machine learning models in tensorflow and train those models with high-performance predictions.
  
  
• Gain a deep understanding of how to convert raw data in such a way that allows machine learning to extract useful data and brings out insights to solve specific h problems.
  
  
• Get the chance to experiment with end-to-end machine learning, i.e Building an ML-focused strategy and progress into model training, optimization and productionalization with Google cloud platform.
  
  
• Five courses of machine learning syllabus are available to prepare a candidate into a data scientist.
  
  
• Chance to perform with hands-on labs using Qwiklabs platform and let you apply the skill learned from the video tutorials.
  
  
• Self-paced learning option provided with free lifetime access to quizzes, programming assignments, and study materials.

Who is it for?

This machine learning program is all designed to give a broad perspective of machine learning and where it can be used. Any person who is willing to learn machine learning online can opt this specialization course to boost their career. By completing this certificate specialization, you will be able to implement machine learning solutions using Google Cloud Platform for a wide variety of environments, ranging from startups to global companies.

Machine Learning with Python: A Practical Introduction [edX]

This machine learning edX course brings you tools and techniques to learn and enhance your skill sets. It has become an incredible technology to uncover data insights and predict an uncertain future. You will introduce the supervised and unsupervised learning and Python libraries for creating machine learning algorithms.

Course Instructor

Saeed Aghabozorgi, a senior data scientist in IBM, created the IBM machine learning with Python program to teach you how to use the powerful and flexible programming language Python and understand how to implement algorithms for production use.

Pros & Cons

Key Highlights & USPs

• This Python Machine Learning Course is divided into 5 modules, which are further divided into 2-4 topics each that covers key concepts of machine learning.
  • Introduction to Machine Learning
  • Regression
  • Classification
  • Unsupervised Learning
  • Recommender Systems
    
    
• Learn two types of machine learning methods: Supervised and Unsupervised Learning
  
  
• Understand the supervised learning algorithms that include classification and regression.
  
  
• Check the unsupervised learning algorithms include clustering and dimension reduction.
  
  
• Build models from statistics to dynamics using machine learning and evaluate them.
  
  
• Practice real-life case studies and understand how to identify machine learning problems.

Who is it for?

This python machine learning offers courses to learners who have a little bit of knowledge of Python and data analysis. You can take Python courses to improve your programming knowledge and prepare yourself for edX machine learning with Python tutorial. After weeks of studying this IBM course, you will earn a set of skills to try at a professional level with an IBM certificate.

Machine Learning Data Science Certification from Harvard University [edX]

Advance your career with this Edx machine learning course, the best way to learn machine learning. This Harvard Machine learning certification introduces real-world case studies to apply machine learning algorithms. It comprises nine skill-building courses that include R basics, statistical concepts, and data analysis techniques.

Course Instructor

The creator of this professional certificate in Data Science, Rafael Irizarry, is a professor of biostatistics from Harvard University. This best machine learning program prepares you with the necessary skills and enhanced knowledge to tackle real-life data analysis challenges.

Pros & Cons

Key Highlights & USPs

• Learn the fundamentals of R programming and how to apply them.
  
  
• Develop an essential skill set that includes data wrangling with dplyr, data visualization with ggplot2.
  
  
• Know the role and use of analytical tools such as Unix/Linux, git, and GitHub
  
  
• Use R software to solve specific problems and ask machine learning questions.
  
  
• dataBuild a better understanding of the basic operation of data science through motivating real-world case studies.

Who is it for?

This ML data science certification is for all types of aspirants who wish to acquire knowledge and skills in data science and machine learning. You must have basic coding and mathematics knowledge to enroll in this professional certification. Taking the Data Science program will equip you with the necessary knowledge and skills to analyze real-world data.

Python for Data Science and Machine Learning Bootcamp [Udemy]

This Udemy machine learning Bootcamp is the best online machine learning course to kickstart your career. You will learn the powerful Python programming language to analyze and visualize data and then use machine learning algorithms to get valuable insights into problems. This comprehensive course is the fastest way to learn Python and solve world problems as a data scientist.

Course Instructor

The author of this course is Jose Portilla, a professor of Data science and programming. It will teach students how to use NumPy, Pandas, Matplotlib, Plotly, Scikit-Learn, Machine Learning, and more. You will get to perform tasks with Machine learning using Python.

Pros & Cons

Key Highlights & USPs

• This Udemy Data Science and Machine Learning Course will teach key concepts of ML in 27 sections and 165 lectures. Each video lecture’s length varies between 3 minutes and 2 hours.
  
  
• Learn how to program with Python.
  
  
• Know how to create data visualizations and use machine learning algorithms.
  
  
• Understand the use of pandas data frames for data analysis and seaborn for statistical plots.
  
  
• Create interactive dynamic visualization using Plotly.
  
  
• Develop deep knowledge of the key concepts like Linear and Logistics Regression, K Means Clustering, Decision Trees, NLP, and Deep Learning.
  
  
• Get full lifetime access to 13 articles, five downloadable resources, and over 100 HD video lectures to master machine learning.

Who is it for?

This top machine learning certification course is ideal for professional tech experts and students with programming experience. It is one of the best comprehensive courses to become a data scientist and successfully land a job in the industry. After completing this data science online tutorial, you will build confidence in using the power of Python for creating data visualization and powerful machine learning algorithms.

How to Think About Machine Learning Algorithms [Pluralsight]

A tricky question has a complicated answer. This Pluralsight machine learning online course brings you the magic of machine learning. You will learn about the basics of machine learning and also understand in-depth knowledge of identifying the right machine learning questions. This machine learning class provides an approach to find out the right machine learning questions for real-world problems.

Course Instructor

When you read the title how to Think about Machine Learning algorithms, what comes to your mind? Now, you’ll have to think about ML algorithms and how they will work for complex tasks. This machine learning curriculum created by Swetha Kolapuddi enables you to know when to use machine learning.

Pros & Cons

Key Highlights & USPs

• This Pluralsight Machine Learning Course is divided into small video lessons which covers methods of writing machine learning algorithms.
  
  
• Learn to model real-world situations into well-understood machine learning problems.
  
  
• Develop the understanding of four basic ML approaches for solving the problem: classification, regression, clustering, or recommendation.
  
  
• Gain knowledge on how to determine which one of four is the right approach.
  
  
• Next, learn how to set up the problem statement and its features. Then, write an algorithm for that particular problem.
  
  
• Upon completion, Grasp the knowledge required to validate a machine learning opportunity.

Who is it for?

This machine learning course for beginners is the perfect choice for those who want to solve real-world problems using machine learning algorithms. Just make sure you are familiar with mathematics and statistics for a better understanding. Upon completion, you will gain the confidence and skills required to plug in a machine learning algorithm for any problem.

Introduction to Machine Learning [Datacamp]

Machine Learning by datacamp is the top online machine learning course that requires no coding experience. Machine learning becomes hype and the quickest growing sector in the IT industry. This comprehensive course gives you the best introduction to machine learning and its relation to data science, artificial intelligence. You will get to unpack the machine learning jargon and build machine learning models.

Course Instructor

Datacamp presents you with an online machine learning course for everyone. It gives you a chance to dive into the hottest technologies. You will get thorough knowledge of the basics of machine learning.

Pros & Cons

Key Highlights & USPs

• Learn how this exciting technology programmed everything from self-driving cars to your favorite browser Google to provide you with valuable suggestions.
  
  
• Answer the following questions: How does machine learning work, when should we use it, and what’s the exact difference between AI and machine learning?
  
  
• Get to perform hands-on exercises to improve your skills in this hugely in-demand field.
  
  
• Take a closer look at Deep learning with neural networks that comprise two use – cases: computer vision and Natural language processing.
  
  
• Discover why machine learning is a must-learn opportunity with 12 videos and 37 practice exercises.

Who is it for?

This machine learning class is ideal for those with non-technical background and wants to learn about machine learning. No coding experience is required to take this Skillshare online class. With the completion, you will build a deeper understanding of machine learning and improve your skill sets.

Deep Learning Certification by DeepLearning.ai – Andrew Ng [Coursera]

Master the machine learning skills with the best deep learning certification program. You will get to learn about the capabilities, challenges, and consequences of deep learning. This deep learning specialization course will prepare you to participate in the development of AI technology. It provides a pathway to understand both theoretical and practical concepts of deep learning using Python and Tensorflow.

Course Instructor

The Author of this deep learning course is Andrew Ng, founder, and instructor of deeplearning.AI. Along with two other experts, he designed this deep learning curriculum to give the students an overview of how deep learning with AI is transforming many industries.

What You’ll Learn

There are 5 courses in this Deep Learning Specialization Program from Coursera, where you will cover all topics related to deep learning.

1. Neural Networks and Deep Learning: The first course in the Deep Learning Specialization will teach you the fundamentals of neural networks and deep learning.
   
   
2. Improving Deep Neural Networks: This course will teach you to open the deep learning black box and understand the processes that drive performance. This will enable you to generate positive results systematically.
   
   
3. Structuring Machine Learning Objects: The third course will teach you how to establish a successful machine learning project and put your decision-making skills to the test as a machine learning project leader.
   
   
4. Convolutional Neural Networks: This course will help you understand the existing applications using deep learning such as autonomous driving, face recognition, reading radiology images, and more.
   
   
5. Sequence Models: In this last course, you will become acquainted with sequence models and their fascinating applications, such as speech recognition, music synthesis, chatbots, machine translation, natural language processing (NLP), and others. 

Pros & Cons

Key Highlights & USPs

• Learn to build neural network architectures such as Convolutional Neural Networks, Recurrent Neural Networks, LSTMs, Transformers.
  
  
• Practice to train and develop test sets for building deep learning applications. Run machine learning algorithms and construct neural networks in Tensorflow.
  
  
• Improve machine learning models with better strategies and reduce errors in machine learning systems.
  
  
• Know how to construct CNN and apply it to tackle real-world challenges such as speech recognition, chatbots, music synthesis, and other 2D/3D data.
  
  
• You’ll need to complete hands-on projects to gain technical knowledge and level up your career.

Who is it for?

The Deep learning specialization is a good training online course for software developers or tech experts who are looking to strengthen their portfolio by learning machine learning and deep learning skills. Learners should have intermediate-level experience in Python and mathematics.  In the end, you’ll gain the knowledge and skills you need to level up your career in AI. In addition, you will receive career advice from deep learning experts.

Machine Learning: From Data to Decisions [MIT Professional Education]

The best online machine learning course makes you a machine learning expert in a few weeks. The MIT profession program prepares you to harness the power of machine learning. You will learn how to use machine learning models and algorithms to make better decisions using data insights. You will understand the process of transforming the raw data to inputs for making decisions by machine with no manual programming.

Course Instructor

The Curator of this online machine learning course, is Devavrat Shah,  a director of Statistics and Data Science at MIT. He will guide students through the pathway and teach them about the machine learning tools and how to use them on real-world examples such as which marketing platform is best or to predict whether the borrower will pay the loan.

Pros & Cons

Key Highlights & USPs

• It gives an overview of the four building blocks of machine learning: regression, classifications, predictions, and decision making.
  
  
• Understand the basics of data analysis and how to use data for building machine learning models to predict future outcomes.
  
  
• Understand how neural networks work with machine learning algorithms to program machines to solve complex problems.
  
  
• Focus on machine learning approaches the situation and makes optimal decisions in uncertainties.
  
  
• Gain a practical understanding of how machine learning applications work.

Who is it for?

The MIT professional education provides machine learning training to learn everything at one stop. You don’t have to be a math genius to understand this course, although professional experience in information technology is helpful. It grants a certificate of completion to enhance your job profile.

Intro to Machine Learning [Udacity]

This udacity machine learning course will boost your abilities through innovative learning techniques. To join the path for machine learning, Udacity recommends you go for its Intro to Programming course to learn to program and covers all the prerequisites for machine learning.

Course Instructor

Learn the course under the guidance of industry experts. The Intro to machine learning course is the perfect course for starting to learn machine learning. It covers the fundamentals of machine learning and prepares you for future job opportunities.

Pros & Cons

Key Highlights & USPs

• Covers Python and SQL-related topics for data analysis.
  
  
• Build predictive machine learning models using supervised and unsupervised machine learning algorithms.
  
  
• To deploy models using Amazon SageMaker and evaluate their performance.
  
  
• Using Tensorflow API for deploying a model to a website and check its response to user input.
  
  
• In-depth knowledge of creating real-life projects and developing expertise in the field of machine learning.
  
  
• Full lifetime access to rich learning content, interactive quizzes, and expert feedback.

Who is it for?

This free machine learning course has been designed for beginners who are interested in learning the basics of Machine Learning. It is not necessary to have any prior experience to take part in this free online machine learning course. After completion, you can take more steps toward careers in Machine Learning, Data Science, AI, and more!

---

Frequently Asked Questions

Final Words

I hope you find this article suitable for your needs and answer some of your questions about machine learning. There are plenty of machine learning courses out there. You can enroll in one of them and start your journey as an ML engineer.