Review —Is Machine Learning A-Z Hands-On Python and R in Data Science Course on Udemy worth it?
Machine Learning A-Z Hands-On Python and R in Data Science course by Kirill Eremenko on Udemy is a detailed, engaging, and informative course to learn Machine Learning with Python and R.
Hello folks, If you want to learn Machine Learning using Python or R programming language and think about joining Udemy’s Machine Learning A-Z — Hands-On Python and R in Data Science online course by Kirill Eremenko and his SuperDataScience team, then you have come to the right place.
In this article, I have reviewed Udemy’s Machine Learning A-Z — Hands-On Python and R in Data Science by Kirill Eremenko and Hadelin De Ponteves so that you will know whether it's worth your time or money or not.
Honestly, this is one of the best Machine Learning courses you can get at an affordable price and is suitable for both beginners and intermediate programmers and people who want to pursue Machine Learning.
It’s comprehensive yet engaging; it's detailed but at the same time very to-the-point and full of real-life examples and hands-on coding. Almost 800K people have joined this course, and it has on average a 4.5 rating which speaks a lot about the quality of the course.
If you are in a hurry, I suggest you join the course now (90% Discounted at the moment). You will not regret it, but if you have some time, stay and read the full review of the Machine Learning aZ-A Hands-on Python and R in Data Science course to make an informed decision.
This industry known as machine learning has grown to be one of the most demanding fields in the IT industry. Some endless options and industries can benefit from machine learning, such as chatbots, self-driving cars, fake news detection, and much more.
Machine learning is the concept of making computers learn using data instead of being programmed. Glassdoor has estimated the salary for a machine learning engineer is around $114,121 a year. The good thing is that you don’t actually need a college degree to start a career in this industry because many online courses can teach you these concepts.
While I’m browsing the internet for some online courses to learn machine learning on platforms like Coursera, Educative, and Pluralsight, I have landed on a Udemy course that promises to teach you all of what you need to start a career in this industry and you are now reading a review of that course.
Is Machine Learning A-Z — Hands-On Python and R in Data Science Worth? Review
Without wasting any more of your time, here is my review of Udemy’s Machine Learning A-Z — Hands-On Python and R in Data Science. I have divided reviews into multiple sections considering the Instructor’s reputation, content structure, what is covered in this course, and overall course material and delivery.
1. The Instructor Reputation
Before start exploring the content, let’s first introduce the two main instructors for this machine learning course:
Kirill Eremenko: is a data science consultant with years of experience in the industry and a Udemy instructor of over 114 courses in different fields such as machine learning, tableau, deep learning, data science, python language, and much more, with over 1.6 million students enrollments.
Hadelin de Ponteves: is also a Udemy instructor with over 80 online courses in different fields such as blockchain, deep learning, computer vision, artificial intelligence, and many more fields. He is also an entrepreneur and the founder of BlueLife AI.
Kirill is one of the best Udemy instructors for learning Data Science, Machine Learning, and Artificial Intelligence, and he has authored many best-selling courses, including this one. You can further check his profile to find more about his other Data Science courses.
2. The Course Structure and Content
The nice things are that the instructors started with an introduction to machine learning and some other key machine learning concepts before deep-diving into the practical section of the course.
2.1. Data Preprocessing
Before applying machine learning algorithms to your data, the first step is preprocessing that data into the right format, and this section is all about it. You will see how to preprocess data using the two languages Python and R.
2.2. Regression
The next step after preprocessing your data is applying some machine learning algorithms to that data. This section shows you six different Machine learning algorithms such as simple linear regression, support vector machine, random forest, and much more and evaluates these algorithms' performance.
2.3. Classification
Machine learning regression algorithms are used to predict continuous data, but what about predicting categories? Well, this is what you will learn in this section using some algorithms such as logistic regression, kernel SVM, and much more, with the pros and cons of every algorithm in detail.
2.4. Clustering
This section will teach you to use some clustering algorithms such as K-means clustering to perform grouping on some datasets based on some parameters, and some of these algorithms are not good for big datasets.
2.5. Association Rule Learning
This section will teach you a technique you use to find the relationship between various items, known as association rule learning. It is usually used in the recommendation systems many more.
2.6. Reinforcement Learning
In an abbreviation, reinforcement learning is a subset of machine learning where the computer can make a sequence of decisions. This section as well shows you how to perform this using Python and R.
2.7. Natural Language Processing
NLP is a subset of machine learning where computers can work with text such as translation, speech recognition, and more. This section will introduce you to the NLP libraries and how to use them with python and R.
2.8. Deep learning
Machine learning is designed to work with small to medium data, but what about large data like big data and more. Here comes the power of deep learning, where you can create neural networks to deal with and process this large data.
2.9. Dimensionality Reduction
This technique is used to reduce or transform your data from a high-dimension to a low-dimension space because less variable makes it easy to be plotted and better for comparisons.
2.10. Model Selection & Boosting
After you have learned all of the machine learning and deep learning techniques and algorithms, you are probably confused about which one I need to use for my problem or project. This section will teach you what algorithms and techniques you should use for your model or data.
3. People Review
The course has got more than 700k student enrollment, which is insane, and few courses in the Udemy platform of all industries have got this number of enrollment, which proves the success and quality of this program.
You can clearly see that 54% of students have given five stars for the course and they are delighted with the course content and recommend it to everyone who wants to start a career in this industry.
Here is the link to join this course — Machine Learning A-Z — Hands-On Python and R in Data Science
That’s all on this review of Machine Learning A-Z: Hands-On Python and R in Data Science course on Udemy by Kirill Eremenko and his SuperDataScience team.
This is one of the best Machine Learning online course. It’s comprehensive (44 hours of content) yet engaging, it's hands-on yet detailed, and most importantly, it's very informative. The teaching style of Kirill Eremenko makes this a complete course to learn Machine Learning using Python and R.
You will learn really amazing things that will make you professional in this industry, and I couldn’t even mention all things you will explore in this course, so this is your chance to become a machine learning engineer.
If you are serious about learning Python and Machine Learning in-depth, here are some more free and paid resources for Further Learning
- Top 8 Python libraries for Data Science and Machine Learning
- 10 Reasons to learn Python in 2024
- 15 Free Python Programming Courses for Beginners
- 10 Python Courses and Certifications For Programmers
- Top 5 Python books to learn Data Science
- 10 Free Python Programming Books for Programmers
- The 2024 Web Developer RoadMap
- Top 5 Web Development Frameworks for Python Developers
- 5 Data Science and Machine Learning course in Python
- Python vs. JavaScript — Which is better to start with?
- 10 Free Online courses to learn Python in depth
- 8 Python Projects for Beginners to learn Python
- Why Python is the best Programming language for Data Science
- Top 5 Websites to learn Python Coding for FREE
Thanks for reading this article so far. If you like this Machine Learning A-Z — Hands-On Python and R in the Data Science course review, please share this article with your friends and colleagues.
If you have any questions or feedback, please drop a note, and if you have a Machine Learning course or book that I should join or read, feel free to share it with us.
P. S. — If you are a fan of Coursera courses and want to know which Coursera course to join to learn Machine Learning from scratch then I highly recommend you to join Machine Learning Specialization, offered by the University of Washington.
It’s a great collection of courses to master machine learning fundamentals. More than 410K people have joined this program to learn Machine learning concepts in detail.
