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11 Best Machine Learning Courses on Udemy for Beginners

11 Best Machine Learning Courses on Udemy for Beginners


 Complete Machine Learning 11 in 1 course

Note: We included courses with more than 800 reviews and a rating of 4.2 stars or better.
Machine Learning, Data Science and Deep Learning with Python

Description: If you’ve got some programming or scripting experience, this course will teach you the techniques used by real data scientists and machine learning practitioners in the tech industry – and prepare you for a move into this hot career path. This comprehensive machine learning tutorial includes over 100 lectures spanning 14 hours of video, and most topics include hands-on Python code examples you can use for reference and for practice. Each concept is introduced in plain English, avoiding confusing mathematical notation and jargon. It’s then demonstrated using Python code you can experiment with and build upon, along with notes you can keep for future reference.

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Introduction to Machine Learning for Data Science

Description: In this introductory course, you will be guided through wilderness of machine learning for data science.  Accessible to everyone, this introductory course not only explains machine learning, but where it fits in the “technosphere” around us, why it’s important now, and how it will dramatically change our world today and for days to come. This course is a great primer for starting Python or R, introducing the fundamentals that you need before going hands-on. 

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Cluster Analysis and Unsupervised Machine Learning in Python

Description: In this course, you will first talk about clustering. This is where instead of training on labels, you will try to create your own. You’ll do this by grouping together data that look alike. Next, the instructors will go into Gaussian mixture models and kernel density estimation, where they will talk about how to “learn” the probability distribution of a set of data. All the algorithms they’ll talk about in this course are staples in machine learning and data science, so if you want to know how to automatically find patterns in your data with data mining and pattern extraction, without needing someone to put in manual work to label that data, then this course is for you.


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Machine Learning with Javascript

Description: There are many courses on machine learning already available. The instructor built this course to be the best introduction to the topic.  No subject is left untouched, and students never leave any area in the dark.  If you take this course, you will be prepared to enter and understand any sub-discipline in the world of machine learning. Requirements include a basic understanding of terminal and command line usage, and the ability to read basic math equations.

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Data Science: Supervised Machine Learning in Python

Description: This course focuses on “how to build and understand”, not just “how to use”. Anyone can learn to use an API in 15 minutes after reading some documentation. It’s not about “remembering facts”, it’s about “seeing for yourself” via experimentation. It will teach you how to visualize what’s happening in the model internally. If you want more than just a superficial look at machine learning models, this course is for you.

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An Introduction to Machine Learning for Data Engineers

Description: This course is part of a series on data engineering and will show you the basics of machine learning for data engineers. The module is geared toward answering questions for the Google Certified Data Engineering exam. This is not a general course or introduction to machine learning. This is a very focused course for learning the concepts you’ll need to know to pass the certification. 

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Python for Data Science and Machine Learning beginners

Description: This course, which is instructed by a data scientist with 4-years of experience, is designed for absolute beginners to data science and machine learning. It covers each aspect of Python languages required in data science, machine learning and deep learning. This course is for beginners in Python development, programming, data science, and machine learning. Python for Data Science has a nearly perfect 4.9 stars.

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Machine Learning Practical Workout | 8 Real-World Projects

Description: The purpose of this course is to provide students with knowledge of key aspects of deep and machine learning techniques in a practical, easy and fun way. The course provides students with practical hands-on experience in training deep and machine learning models using real-world datasets. This course covers several techniques in a practical manner as well. The course is targeted towards students wanting to gain a fundamental understanding of deep and machine learning models. Basic knowledge of programming is recommended. 

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Best Machine Learning Courses on Udemy for Intermediate

Note: We included courses with more than 1,000 reviews and a rating of 4.2 stars or better.


AWS Certified Machine Learning Specialty 2021 – Hands On!

Description: This certification prep course is taught by Frank Kane, who spent nine years working at Amazon itself in the field of machine learning. Frank took and passed this exam on the first try, and knows exactly what it takes for you to pass it yourself. Joining Frank in this course is Stephane Maarek, an AWS expert and popular AWS certification instructor on Udemy. In addition to the 9-hour video course, a 30-minute quick assessment practice exam is included that consists of the same topics and style as the real exam. You’ll also get four hands-on labs that allow you to practice what you’ve learned, and gain valuable experience in model tuning, feature engineering, and data engineering. 

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Deployment of Machine Learning Models

Description: This is the first and only online course where you can learn how to deploy machine learning models. In this course, you will learn every aspect of how to put your models in production. The course is comprehensive and yet easy to follow. Throughout this course, you will learn all the steps and infrastructure required to deploy machine learning models professionally. In this course, you will have at your fingertips, the sequence of steps that you need to follow to deploy a machine learning model, plus a project template with full code, that you can adapt to deploy your own models. 

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Machine Learning Practical: 6 Real-World Applications

Description: Machine Learning Practical brings the best industry professionals together. Each presenter has a unique style which is determined by their experience. Students will need to adjust on the fly to complete the course. The module will demystify how real data science projects like instead of looking at only polished samples which are only introducing you to the matter but not providing the real experience. This course provides a hands-on approach to real-life challenges and covers exactly what you need to succeed in the real world of data science. 

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NOW READ: The Best Machine Learning Courses and Online Training to Consider (All platforms)

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