Top 10 Machine Learning, Deep Learning, and Data Science Courses for Beginners (Python and R)
This article includes a list of some of the best courses to learn Data Science, Machine Learning, and Deep Learning.
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Data Science, Machine Learning, Deep Learning, and Artificial Intelligence are really hot at this moment and offering a lucrative career to programmers with high pay and exciting work. It's a great opportunity for programmers who are willing to learn these new skills and upgrade themselves. It's also important from the job perspective because Robots and Bots are getting smarter day by day, thanks to these technologies and most likely will take over some of the jobs which many programmers do today. Hence, it's important for software engineers and developers to upgrade themselves with these skills. Programmers with these skills are also commanding significantly higher salaries as data science is revolutionizing the world around us. Machine Learning specialist is one of the top paid technical jobs in the world. However, most developers and IT professionals are yet to learn these valuable set of skills.
For those, who don't know what is a Data Science, Machine Learning, or Deep Learning, they are very related terms with all pointing towards machine doing jobs which is only possible for humans till date and analyzing the huge set of data collected by modern day application.
Data Science, in particular, is a combination of concepts such as Machine Learning, visualization, data mining, programming, data mugging, etc.
If you have some programming experience then you can learn Python or R to make your carer as a Data Scientist. There are a lot of popular scientific Python libraries such as Numpy, Scipy, Scikit-learn, Pandas, which is used by Data Scientist for analyzing data.
To be honest with you, I am also quite new to Data Science and Machine Learning world but I have been spending some time from last year to understand this field and have done some research in terms of best resources to learn Machine Learning, data science etc.
I am sharing all those resources in a series of a post like this. Earlier, I shared some courses to learn TensorFlow, one of the most popular Machine Learning libraries, and today, I'll share some more information to learn these technologies. This is a combination of both free and paid resources, which will help you understand key data science concepts and become a Data Scientist.
10 Useful Data Science Courses for Programmers
Here is my list of some of the best courses to learn Data Science, Machine Learning, and Deep Learning. As I said, Data Science and Machine Learning work very close together, hence some of these courses also cover Machine Learning.
I personally like Python because of its versatile usage, it's the next best in my list of language after Java. I am already using it for writing scripts and other web stuff, so it was an easy choice for me. It has also got some excellent libraries like Sci-kit Learn and TensorFlow.
Data Science is also a combination of many skills e.g. visualization, data cleaning, data mining etc and these courses provide a good overview of all these concepts and also presents a lot of useful tools which can help you in the real world.
1. Machine Learning A-Z: Hands-On Python and R — In Data Science
This is probably the best hands on course on Data Science and Machine Learning online. In this course, you will learn to create Machine Learning Algorithms in Python and R from two Data Science experts.
This is a great course for students and programmers who want to make a career in Data Science and also Data Analysts who want to level up in Machine Learning.
It's also good for any intermediate level programmers 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.
2. Data Science with R by Pluralsight
Data science is the practice of transforming data into knowledge, and R is one of the most popular programming language used by data scientists.
In this course, you'll learn first learn about the practice of data science, the R programming language, and how they can be used to transform data into actionable insight.
Next, you'll learn how to transform and clean your data, create and interpret descriptive statistics, data visualizations, and statistical models.
Finally, you'll learn how to handle Big Data, make predictions using Machine Learning algorithms, and deploy R to production.
3. Harvard Data Science Course
The course is a combination of various data science concepts such as Machine Learning, visualization, data mining, programming, data mugging, etc.
You will be using popular scientific Python libraries such as Numpy, Scipy, Scikit-learn, Pandas throughout the course.
I suggest you complete the Machine Learning course on course before taking this course, as Machine Learning concepts such as PCA (dimensionality reduction), k-means and logistic regression are not covered in depth.
But remember, you have to invest a lot of time to complete this course, especially the homework exercises are very challenging
In short, if you are looking for an online course in data science(using Python), there is no better course than Harvard's CS 109. You need some background in programming and knowledge of statistics to complete this course.
4. Want to be a Data Scientist? (FREE)
This is a great introductory course on what Data Scientist do and how you can become a data science professional. It's also free and you can get it on Udemy.
If you have just heard about Data Science and excited about it but doesn't know what it really means then this is the course you should attend first.
It's a small course but packed with big punches. You will understand what Data Science is? Appreciate the work Data Scientists do on a daily basis and differentiate the various roles in Data Science and the skills needed to perform them.
You will also learn about the challenges Data Scientists face. In short, this course will give you all the knowledge to make a decision on whether Data Science is the right path for you or not.
5. Intro to Data Science by Udacity
This is another good Introductory course on Data science which is available for free on Udacity, another popular online course website.
In this course, you will learn about essential Data science concepts e.g. Data Manipulation, Data Analysis with Statistics and Machine Learning, Data Communication with Information Visualization, and Data at Scale while working with Big Data.
This is a free course and it's also the first step towards a new career with the Data Analyst Nanodegree Program offered by Udacity.
6. Data Science Certification Training — R Programming
The is another good course to learn Data Science with R. In this course, you will not only learn R programming language but also get some hands-on experience with statistical modeling techniques.
The course has real-world examples of how analytics have been used to significantly improve a business or industry.
If you are interested in learning some practical analytic methods that don't require a ton of maths background to understand, this is the course for you.
7. Intro To Data Science Course by Coursera
This course provides a broad introduction to various concepts of data science. The first programming exercise "Twitter Sentiment Analysis in Python" is both fun and challenging, where you analyze tons of twitter message to find out the sentiments e.g. negative, positive etc.
Btw, It's not so good for beginners, especially if you don't know Python and SQL but if you do and have a basic understanding of Data Science then this is a great course.
8. Python for Data Science and Machine Learning Bootcamp
There is no doubt that Python is probably the best language, apart from R for Data Analysis and that's why it's hugely popular among Data Scientists.
This course will teach you how to use all important Python scientific and Machine Learning libraries Tensorflow, NumPy, Pandas, Seaborn, Matplotlib, Plotly, Scikit-Learn, Machine Learning, and many more libraries which I have explained earlier in my list of useful Machine Learning libraries.
It's a very comprehensive course and you will how to use the power of Python to analyze data, create beautiful visualizations, and use powerful Machine Learning algorithms!
9. Data Science A-Z: Real-Life Data Science Exercises Included
This is another great hands-on course on Data Science from Udemy. It promises to teach you Data Science step by step through real Analytics examples. Data Mining, Modeling, Tableau Visualization and more.
This course will give you so many practical exercises that the real world will seem like a piece of cake when you complete this course.
The homework exercises are also very thought-provoking and challenging. In short, If you love doing stuff then this is a course for you.
10. Data Science, Deep Learning and Machine Learning with Python
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 help you to become a data scientist.
The topics in this course come from an analysis of real requirements in data scientist job listings from the biggest tech employers, that makes it even more special and useful.
That's all about some of the popular courses to learn Data Science. As I said, there is a lot of demand for good Data Analytics and there are not many developers out there to fulfill that demand. It's a great chance for the programmer, especially those who have good knowledge of maths and statistics to make a career in Machine Learning and Data analytics. You will be awarded exciting work and incredible pay.
Other useful Data Science and Machine Learning resources:
Top 8 Python Machine Learning Libraries
5 Free courses to learn R Programming for Machine Learning
5 Free courses to learn Python in 2018
Top 5 Data Science and Machine Learning courses
Thanks for reading this article so far. If you find these Data Science and Machine Learning courses useful then please share with your friends and colleagues. If you have any questions or feedback then please drop a comment.
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