Learn Machine Learning online step by step
Interested in Machine Learning but don’t know how to start?
Have little or zero knowledge and want to become a pro of Data Science and Machine Learning?
Know a little bit about the theory but lack implementation practice?
Looking to step up your knowledge to get a job in data science?
Then Udemy’s Machine Learning A-Z is the course for you.
It is an amazing course that can take people with very little knowledge to being very confortable implementing and building real Machine Learning applications: perfect for those looking to learn the skills necessary to get a job in Machine Learning and start working in the industry.
You need no previous programming skills: Udemy Machine Learning A-Z will get you up and running in Python and R for Data Science: the two most used languages in the Machine Learning world. This is great, as you will be able to highlight your knowledge in your CV, and will gain a competitive advantage over people that only have expertise in one of the two.
It is a great course to complement with a book like AI and Machine Learning for coders. With this tandem you will be very very comfortable building Machine Learning applications.
The course is fun and well paced, but at the same time really comprehensive, covering everything you need to know about this amazing world. Also, it is highly practical and to the point, explaining the algorithms in a way that you will understand where each of them should be applied, but without diving heavily into the math, which sometimes can be a bit tedious and time consuming.
All you need for this course is some light high-school math, nothing else. Awesome, lets see what it contains!
Contents of Udemy Machine Learning A-Z
- Part 0 – Introduction: What is Machine Learning, its most common applications, and a description of Udemy Machine Learning A-Z course.
- Part 1 – Data Preprocessing: A fundamental step before any Machine Learning model can be trained.
- Part 2 – Regression: Simple Linear Regression, Multiple Linear Regression, Polynomial Regression, SVR, Decision Tree Regression, Random Forest Regression
- Part 3 – Classification: Logistic Regression, K-NN, SVM, Kernel SVM, Naive Bayes, Decision Tree Classification, Random Forest Classification
- Part 4 – Clustering: K-Means, Hierarchical Clustering: Unsupervised clustering models. This section misses DBSCAN, which we think would have been a good addition to the curriculum to cover density based models.
- Part 5 – Association Rule Learning: Apriori, Eclat. This chapter is very interesting, and it contains content that is rarely covered in other Data Science courses.
- Part 6 – Reinforcement Learning: Upper Confidence Bound, Thompson Sampling. Despite RL not being widely used in the Industry, it is a highly promising area of Machine Learning for the future years, so we think it is awesome that it is included here.
- Part 7 – Natural Language Processing: Bag-of-words model and algorithms for NLP
- Part 8 – Deep Learning: Artificial Neural Networks, Convolutional Neural Networks
- Part 9 – Dimensionality Reduction: PCA, LDA, Kernel PCA
- Part 10 – Model Selection & Boosting: k-fold Cross Validation, Parameter Tuning, Grid Search, XGBoost
Moreover, the course is packed with practical exercises that are based on real-life examples. So not only will you learn the theory, but you will also get some hands-on practice building your own models, which is essential if you later want to get a job in Machine Learning. By completing this course you will start building your portfolio of projects.
And as a bonus, this course includes both Python and R code templates which you can download and use on your own projects.
Who is Udemy’s Machine Learning A-Z for?
- Anyone interested in Machine Learning.
- Students who have at least high school knowledge in math and who want to start learning Machine Learning.
- Any intermediate level people who know the basics of machine learning, including the classical algorithms like linear regression or logistic regression, but who want to learn more about it and explore all the different fields of Machine Learning.
- Any people who are not that comfortable with coding but who are interested in Machine Learning and want to apply it easily on datasets.
- Any students in college who want to start a career in Data Science.
Udemy’s Machine Learning A-Z course is an amazing course for beginners that want to understand everything about Data Science, and that want to become fluent in writing code in Python and R.
We highly value this course as a resource for those with some previous knowledge of Machine Learning that want to look for a job in the field, and that are willing to expend some cash, make an effort, and give it a push.
Our you can complement it with Hands-On Machine learning, our favourite book to learn for beginners.
- Géron, Aurélien (Author)
- English (Publication Language)
- 856 Pages - 10/15/2019 (Publication Date) - O'Reilly Media (Publisher)
Duration: It has more than 40h of video content, so you can probably complete this course in about a month with daily moderate dedication.
Cost: The price of the course is about 100$ with no discount, but Udemy constantly offers discounts on these kind of courses. If you can’t manage to get a discount, the full price still is worth it!
Prerequisites: High school maths. No previous coding skills required, although you will learn faster and make the most out of the course if you do know how to program.
Tags: Machine Learning online course, Udemy Machine learning, Job in Machine Learning, Data Science Course, Python, R.