The era of big data is here. But this data is worthless unless a meaning is drawn out of it. It is exactly here that data science comes into play. Data science is nothing but a combination of different algorithms, tools, and machine learning principles. The main objective here is to identify hidden patterns out of raw data. With organizations relying heavily on data, the need for data scientists is at an all-time high. A data scientist is concerned with discovering insights from raw data and adding different machine learning algorithms to recognize a specific event in the future. A career in data science is promising and if you aspire to become a successful data scientist, there cannot be a better time than now to start. On that note, here are the top 10 free data science courses to take up in 2022.

Machine learning Course for Beginners (YouTube -FreeCodecamp)

You'd be surprised to know that this course is developed by a kid. However, the content and exposure you get here are unmatchable. This course is available for free on YouTube at FreeCodecamp's YouTube channel. Topics such as fundamentals of machine learning, linear and logistic regression, decision tree, boosting, hierarchical clustering, etc. are covered in detail.

Python for data science

Presented by the University of California, San Diego, this course introduces you to a wide range of powerful, and open-source tools such as Python, Git, Pandas, etc. On the completion of this course, you'd be in a position to make the best of large datasets by using python tools in importing data, exploring it, learning from it, analyzing it, and visualizing it.

Data-driven Decision making – Coursera

This course is provided by PwC and covers the spectrum of tools and techniques that are used to tackle business data challenges. This is a four-week long course. In the end, there is a task that involves deploying a data solution in a simulated business environment.

Introduction to data science

As the name suggests, this course gives you every possible detail pertaining to the basics of data science. Right from defining data science, introduction to regression, R and Python, to understanding the applications, this free data science course has got you covered.

Data science Tools

Data science has practically no meaning without making use of relevant tools to make the best of data. This free data science course is designed to give you a fair understanding of Data science tools like Jupyter Notebooks, RStudio IDE, and Watson Studio.

Data science Methodology

One of the major problems faced by the organizations is that they lack a solid understanding of the questions being asked and how to apply the data correctly to the problem at hand. This is where the Data science Methodology course is targeted at. The course will help you learn the major steps involved in tackling a data science problem.

Become a data scientist

"Become a data scientist" is a course offered by Dataquest, an independent online training provider. In this course, a lot of ideas are encapsulated in order to provide aspiring data scientists a better learning experience. This course aims at making the aspirants well versed with Python.

Hadoop platform and application framework

If you are keen on understanding the basic tools used in wrangling and analyzing big data, this free data science course is for you. Here, you'll get a chance to walk through hands-on samples with Spark and Hadoop frameworks. This five-week free data science course will take you through the basic processes of the Hadoop architecture, execution environment, and software stack.

Data Science: R Basics

This free data science course will introduce you to the basics of R programming. The course will take you through R's functions and data types, then tackle how to operate on vectors and when to use advanced functions like sorting. As data scientists are associated with data visualization and data wrangling as well, this course will help you learn these skills also.

High-dimensional data analysis

The course starts with a brief introduction to machine learning. As you proceed, you'll learn how to apply machine learning to high-throughput data. It is an intermediate-level course throwing light on topics such as factor analysis, multiple dimensional scaling plots, and a lot more.