7 Great Resources for Learning Data Science Online
Tags: datascience
Published: 2021-04-21 10:43:32

Thanks to technology, we can learn skills and knowledge in any field. It’s a fantastic opportunity, and we should use it!
Do you want to become a data science expert? There are many platforms out there where you can find relevant learning materials to study and practice. 

We have hand-picked the best resources for learning data science online. Check them out!

## Data Science for Everyone Course by DataCamp
If you are a newbie in the field of data science, enroll in a free course Data Science for Everyone designed by DataCamp. This course is an introduction to data science. It includes 15 videos and 48 exercises and doesn’t involve coding. 
Videos and exercises will help you learn more about the different data scientist roles, the fundamental principles of A/B testing, and the concepts of time series analysis and machine learning. 
Upon completing this course, you will understand how data scientists extract knowledge and insights from real-world data and how they further use them.
 

## The Data Science Course 2021 at Udemy
Udemy offers lots of great courses for programmers, and it might be challenging for you to pick the one that is right for you. 
If you don’t have previous knowledge in the area of data science, we recommend you enroll in the course called The Data Science Course 2021: Complete Data Science Bootcamp.
It’s a comprehensive course that includes 28.5 hours of on-demand video, 90 articles, and around 500 downloadable resources. The course involves coding – you will start [coding in Python](https://dev.to/catmcgeecode/from-never-writing-code-to-becoming-a-python-dev-in-19-steps-5a0l) and learn how to use this programming language for statistical analysis. 
Also, you will learn some basic principles of how to improve machine learning algorithms by studying training, validation, n-fold cross-validation, and testing.
The only requirements for this course are that you need to install Anaconda and Microsoft Excel. 

## Data Science Course by SimpliLearn
If you have already chosen data science as your career path, consider getting an industry-recognized Data Scientist Master’s certificate from SimpliLearn.
This Data Science course was developed in collaboration with IBM, and it includes 220+ hours of live interactive learning. 
As a student, you will be exposed to advanced technologies including R, Python, machine learning, Tableau, Hadoop, and Spark.  You will interact with practitioners (in an online mode) and participate in real-life industry projects. 
On top of that, you will get an opportunity to attend exclusive hackathons and enjoy live interaction with IBM leadership.
 
## Data Science Specialization Course at Coursera
At Coursera, you can get free access to Data Science Specialization that includes ten courses starting from the basic Data Scientist’s Toolbox course to Developing Data Products course. This specialization program is offered by Johns Hopkins University.
What will you learn from these courses? You will learn how to use R to clean, analyze, and visualize data. Also, you will acquire practical skills that will allow you to perform regression analysis and use regression models.
Another benefit of this educational resource is that it will familiarize you with GitHub and give you a better understanding of data science project management.
## Data Science Course by Harvard Extension School
In case if money is not an object for you, you can use learning materials offered by Harvard and obtain Data Science Graduate Certificate.
At Harvard Extension School, you will learn the key concepts related to data investigation, such as data wrangling, cleaning, sampling, management, exploratory analysis, regression and classification, prediction, and data communication. Top-tier instructors will introduce you to numerical algorithms, parallel computing, simulation, and analysis.
You will become an expert in such subject areas as game theory, statistical quality control, exponential smoothing, seasonally adjusted trend analysis, and data visualization.
 
## Analytics Vidhya
Analytics Vidhya is a data science community that unites 725K members and more than 500 companies worldwide. At this platform, you can find not only free courses but also interesting-to-read blog posts and information about the upcoming hackathons. 
Here is a short list of free Analytics Vidhya’s tutorials that you may found helpful:
* A Complete Tutorial to learn Data Science in R from Scratch
* A Complete Tutorial on Time Series Modeling in R
* Complete R Tutorial To Build Probabilistic Graphical Models

## Non-technical reading
To become a successful data scientist, you don’t really need to learn programming languages 24/7. As a student, you should find time for [additional reading](https://subjecto.com/essay-samples/) in order to expand your worldview. You should read articles, essays, research papers, and non-technical literature to get ideas on how you can apply data science to solve real-life problems. 
Here is a non-technical reading list for data scientists:
* Weapons of Math Destruction: How Big Data Increases Inequality and Threatens Democracy by Cathy O’Neil
* Everybody Lies: Big Data, New Data, and What the Internet Can Tell Us About Who We Really Are by Seth Stephens-Davidowitz
* Algorithms to Live By by Brian Christian and Tom Griffiths
* Superforecasting: The Art and Science of Predictionby Philip E. Tetlock and Dan Gardner
* The Signal and the Noise: Why Most Predictions Fail – but Some Don’t by Nate Silver
* How Not to Be Wrong: The Power of Mathematical Thinking by Jordan Ellenberg.

## Dev.to
If you want to boost your learning efforts, you should [join the online community](https://dev.to/enter?state=new-user) of data scientists and programmers. 
Dev.to is a platform where you can read blog posts written by IT specialists, listen to podcasts, and participate in discussions with other experts in the field. 
It’s a place where you can gain extra knowledge, make new connections, and learn more about the real challenges, struggles, and achievements of modern data scientists.

## In conclusion
Don’t wait for “the right moment” to start learning data science. Make the first step today. Check out the resources listed above and immerse yourself in the learning process.
The sooner you will take this step, the sooner you will accomplish your dream and become a data science pro.

BIO: Diana Adjadj is a tech writer, researcher, and blogger. She worked for edtech and biotech companies for four years. Now she is a freelancer. Diana is passionate about advanced technologies, data science, and digital marketing.