The need for capable data scientists is swiftly increasing. According to a forecast presented by the IBM, the demand for data scientists will surge to 28% by the year 2020. Data is critical to businesses, as information is linked to every operation process at a company. With big industries like refineries and manufacturing plants creating a tremendous amount of data, they need data scientists who can help generate value from it. Online data science courses can help provide tools and resources to those already in the industry. There are also many modules available for beginners to grow their careers.

Here are 9 free online data science courses for beginners and professionals alike.

• Big Data Basics
• Hadoop
• Machine Learning Basics
• Structured Query Language
• Python
• Spark
• R-Programming Basics
• Data Management with R
• Artificial Intelligence for Beginners

Keep reading to learn more about each of these online courses.

1. Big Data Basics

For beginners, basic understanding of big data is vital. These courses let you get a grounded understanding of the common terminology behind data optimisation. There are also multiple resources obtainable online offering big data certification courses for beginners and experts.

2). Hadoop

Hadoop is an open source big data framework which processes large data set models across the cluster computing. Basic knowledge of Hadoop can be found from Hadoop’s documentations. The only baseline you’ll need to dig into this material is a ground level understanding of Java programming and the Linux operating systems commands.

3). Machine Learning Basics

Machine learning algorithms learn from the data. Online data science courses offered by various platforms introduce these algorithms. Python offers a free tutorial on their website explaining the basics and other technical integration with ML.

4). Structured Query Language

SQL is a language to create, update and manage other related operations on the relational database tables. These Microsoft modules offer ways for both beginners and advanced users to gain skills in SQL.

5). Python

The Python Software Foundation offers this free course for big data and analytics. Python is a robust programming language framework with its broader implementation in various fields. It assimilates modules, expressions, variables, dynamic typing, classes, functions, high-level data types and more to combine their power and do more with code.

6). Spark

Spark, invented by Databricks, is the analytical framework widely adopted by enterprises due to its fast data processing speed. In comparison with Hadoop, it can accelerate much quicker for large-scale data processing. Databricks offers online free courses for understanding Spark and its step-by-step processing.

7). R-Programming Basics

R is one of the most widely adopted programming languages in data science. The critical steps involved in the R-programming are: import, tidy, explore and communicate. The exploration part derives the transformation, visualisation and modelling. A basic R course is obtainable at Udemy which offers the complete installation to the implementation of the supported packages to execute the program.

The integrated development environment for R programming, called RStudio, is also available online. A step by step installation guide is available here, which allows you to download the framework for free.

8). Data Management with R:

Your analytical approach to big data can be improved by pursuing this data management course offered by Microsoft. The modules provided in training include the use of R in the analysis, statistics and for graphical understanding.

9). Artificial Intelligence for Beginners

This free artificial intelligence tutorial can help you develop an upgraded understanding of AI and its implementation in the future.

If you are interested in developing a career as a data scientist, it’s necessary to start learning the fundamentals of code now. These 9 online data science courses can help you improve your skills and focus on the aspects of data you find most interesting.

The basic understanding of the core concepts are not only enough to get you a qualified job, but you also need to sum up the practical explanation of the work with your culture. The voyage to become a data scientist is marked with the enormous set of data and the analytical approaches to transform these data sets into valuable results.

This is a guest post to UniversityWebinars.org. For more helpful resources on data science, technology, and education, make sure to check out the rest of our articles on our blog.