Machine learning is a vast and incredibly relevant subject in today’s world. It’s a subtopic under artificial intelligence (AI) that is employed in several large industries such as healthcare, finances, transportation, retail, and so many more.
If you’re here, you’re probably looking to start learning or broaden your already existing knowledge base concerning machine learning. Well, online courses are definitely a worthwhile option to consider to achieve your goals! Not only are they convenient and relatively more affordable, but they also offer a wealth of easily accessible information if you find the right courses. I’m here to help you do exactly that!
The following listed courses are some of the top courses on Udemy to learn machine learning in my opinion. This opinion is based on careful analysis of reviews, course rating, course content, and learning outcomes. Now, let’s dive right into it, shall we?
Machine Learning A-Z™: Hands-On Python & R In Data Science
This one is the most well-known machine learning course on Udemy. It has successfully taught over 700,000 students by employing a combination of theory classes and practical exercises. This means that you will get to cultivate a solid foundation of knowledge as well as technical know-how. Many people hesitate to sign up for online classes because they fear that will miss out on the application component of learning. That is not at all true as can be seen by this course’s organization.
Starting from the basics such as simple linear regression, you will be able to build up towards learning more complex topics and maybe even start a career as a data scientist. Topics covered include data preprocessing, deep learning, dimensionality reduction, NLP, and so much more.
If you’re already familiar with machine learning, rest assured because Udemy courses are set up so that you can directly access the information that you need. Although a refresher never hurts anyone! You do not need any prior experience with machine learning to start.
| Course Name | Machine Learning A-Z™: Hands-On Python & R In Data Science |
| Instructor | Kirill Eremenko, Hadelin de Ponteves, SuperDataScience Support, Ligency Team |
| Rating | 4.5/5 (142,033+ ratings) |
| Duration | 44+ hours |
Click here to check out the course on Udemy.
Python For Data Science And Machine Learning Bootcamp
This is another great machine learning course based on Python. It may be the one for you if you already have a bit of programming experience. With Jose Portilla as your instructor, you will be learning how to program with Python using NumPy, Pandas, NLP, spam filters, support vector machines, and more! You will get clear explanations with well-structured class material so that you’re able to get the most out of the experience.
| Course Name | Python for Data Science and Machine Learning Bootcamp |
| Instructor | Jose Portilla |
| Rating | 4.6/5 (97,095+ ratings) |
| Duration | 25 hours |
Click here to check out the syllabus and course details on Udemy.
Machine Learning With JavaScript
The only thing you need to know before starting this course is a basic comprehension of the terminal and command-line usage. It is an excellent introductory course that covers just about any topic you can think of. This includes machine learning algorithms, Tensorflow JS, data loading techniques, linear algebra, and more!
The goal of the instructor is to give you a solid foundation of knowledge concerning JavaScript machine learning so that you can build complex projects from scratch. By the end of this course, you should be able to build single-page applications and browser extensions!
| Course Name | Machine Learning With JavaScript |
| Instructor | Stephen Grider |
| Rating | 4.7/5 (2,385+ ratings) |
| Duration | 17.5 hours |
If you’re interested in machine learning with JavaScript, check out this course on Udemy.
Introduction To Machine Learning For Data Science
What makes this course a bit different from the ones that have been discussed so far is that it’s more general and broader. It essentially functions as an introductory course on machine learning and data science and is a suitable choice if you’re someone who is looking to just get started.
Developed by David Valentine, also known as “the backyard data scientist”, this course covers a wide range of information including technical concepts, their use in the modern world, and their future prospects. There will also be numerous opportunities to get some hands-on experience by creating real-life examples!
In addition to this, the latest update contains a crash course on Python, Jupyter Notebook, NumPy, Pandas, Matplotlib, and much more! You will also receive access to additional resources if you’re interested in continuing to learn more about machine learning on your own.
The instructor is known for his ability to break down complex concepts into subcomponents that are easier to understand. If you think you could profit from this style of teaching, this course is definitely worth exploring!
| Course Name | Introduction To Machine Learning For Data Science |
| Instructor | David Valentine |
| Rating | 4.4/5 (8,941+ ratings) |
| Duration | 5.5 hours |
Click here to check out the course syllabus and contents on Udemy.
Machine Learning, Data Science And Deep Learning With Python
The main objective of this course is to teach you the fundamentals of machine learning with Python and help you get started on your career in data science. To accomplish this, you will get access to lectures followed by demonstrations, real-life examples, guide notes, and a final project to apply what you’ve learned! The emphasis here is on learning how to apply the theoretical content and skills that you learn. After all, that’s what you’ll need when you venture out into the real world.
Deep learning, principal component analysis, Tensorflow, Keras, data visualization, and regression analysis are only some of the topics covered by this comprehensive course! You will even learn machine learning with Apache Spark. It is worth noting that you will need some prior knowledge of coding and high school level math before beginning this course. However, a quick crash course is provided before plunging into the real content so it shouldn’t be too difficult to keep up.
| Course Name | Machine Learning, Data Science and Deep Learning with Python |
| Instructor | Frank Kane |
| Rating | 4.6/5 (24,348+ ratings) |
| Duration | 14.5 hours |
If you’re interested in this course, click here to check it out on Udemy.
Data Science And Machine Learning Bootcamp With R
This course is a bit different from the others on the list because it uses R programming for machine learning. It is beginner-friendly and all you need to get started is a functioning computer! The course content includes programming with R, data analysis, machine learning algorithms, learning ggplot2, and a lot more.
There are also a bunch of exercises, tests, and exercises spread throughout the coursework so that you can regularly assess your own progress in building this skill. Furthermore, the instructor teaches in such a way that topics are easily understandable. In sum, it is quite a comprehensive course that teaches machine learning in a very hands-on manner.
| Course Name | Data Science and Machine Learning Bootcamp with R |
| Instructor | Jose Portilla |
| Rating | 4.6/5 (12,874+ ratings) |
| Duration | 17.5 hours |
Click here to check out more details about this course on Udemy.
Data Science: Supervised Machine Learning In Python
The instructor of this course strives to impart applicable skills by emphasizing students on understanding concepts rather than merely using them. A deeper understanding of a subject leads to building better machine learning models and that’s exactly what happens after taking this course!
K-Nearest Neighbors in Python, Bayes classifiers, perceptron, decision tree, sci-kit learn, and hyperparameters are just a few of the concepts that you will learn through the lessons. At the end of the course, you will be able to test your knowledge by building a real-life web service! It is recommended that you have former experience with Python, Numpy, and Pandas before beginning.
| Course Name | Data Science: Supervised Machine Learning in Python |
| Instructor | Lazy Programmer Team |
| Rating | 4.6/5 (2,165+ ratings) |
| Duration | 6.5 hours |
If you’re interested in this course, click here to check out more details about it on Udemy.
Final Thoughts
I hope you were able to gain some valuable information from this article! If you’re new to online learning, taking that first step can be difficult but these courses were structured to account for this. Like I’ve mentioned at the beginning of this article, online courses can offer a wealth of information and plenty of unique advantages.
With that being said, I hope you were able to find a suitable course through this article. If you’re confused about choosing one course from this list, I would suggest you pick this one and just go forward.
Check out this article if you’re looking for more ML courses on platforms other than Udemy.
Machine learning is a field full of opportunities right now so I wish you all the best moving forward with your career!
