DataCamp is an online resource that was launched in 2013 and focuses on subjects like data science and analytics. There are more than 350 courses available, each taught by one of the 260+ knowledgeable instructors from Datacamp and other prestigious institutions like Duke University.
So, DataCamp can be the ideal online platform for you if you're trying to develop or enhance your data skills. Its interactive classes are all created so you may learn at your own pace.
DataCamp is for whom ?
Let me give you a brief overview of what to expect from DataCamp. It is an online learning environment where you can study data skills at your own speed. Its four-part learning methodology—Assess, Learn, Practice, and Apply—helps students have a well-rounded educational experience.
DataCamp courses that are completely free:-
1) Introduction to Python: -
A general-purpose programming language called Python is growing in popularity for data science. Python is being used by businesses all around the world to extract insights from their data and achieve a competitive advantage. This course, in contrast to previous Python tutorials, focuses on Python specifically for data science. You will discover effective methods for manipulating and storing data as well as useful data science tools to start doing your own analysis in our Introduction to Python course. Start learning Python immediately with DataCamp.
Course Link:- Introduction to Python
2) Introduction to SQL:-
In this two-hour introduction to SQL, you will learn the theory and the practise through short films and hands-on activities that will let you put your newly acquired knowledge to use.
A variety of occupations in the data sector and beyond are accessible thanks to SQL, which is a crucial language for creating and maintaining relational databases. This course will begin with a discussion of data organisation, tables, and recommended practises for building databases.
Two of the most widely used SQL variants are PostgreSQL and SQL Server. This course will come to a close with an examination of the distinctions, advantages, and practical uses of each. By the end of the course, you'll have gained some practical SQL knowledge and the foundation necessary to start using it on projects or continue your education in a more specialised area.
Course Link:- Introduction to SQL
3) Introduction to R:-
R is the most well-liked programming language in the data sector. It can handle AI, machine learning, financial analysis, and much more, and there is a significant demand for data scientists, analysts, and statisticians alike. The fundamentals of this open source language, such as vectors, factors, lists, and data frames, are covered in this introduction to R course. You'll learn practical coding techniques and be equipped to launch your own R data analysis project. Next, you'll discover how to use matrices in R, including how to build them and carry out calculations using them. You'll also look at how R stores categorical data using factors. You'll investigate working with R data frames and lists in the last section. You will be able to apply the fundamentals of R for your own data analysis once you have finished our Introduction to R course. These in-demand abilities can help you advance in your work and pave the way for more education. This course is a component of multiple tracks, including R Programming, Data Analyst with R, and Data Scientist with R, all of which can aid in your knowledge growth.
Course Link:- Introduction to R
4) Understanding Machine Learning:-
What is the excitement surrounding machine learning? You will discover everything about machine learning that you have been too frightened to ask in this non-technical session. No coding is necessary. You may learn how this innovative technology underpins everything from self-driving vehicles to your customised Amazon shopping recommendations through practical exercises that will help you cut through the technical language. What is the difference between AI and machine learning, when can you use it, and how does it operate? Each one is protected. Learn the skills needed in this very prominent and in-demand sector, and find out why machine learning is beneficial to everyone.
Course Link:- Understanding Machine Learning
5) Data Science for Everyone:-
What is data science, why is it so well-liked, and why was it dubbed the "sexiest job of the 21st century" by the Harvard Business Review? Without writing a single line of code, you will learn everything about this rapidly expanding and intriguing topic that you have ever been too frightened to ask in this non-technical course. You'll discover the various roles of a data scientist, the fundamentals of A/B testing, time series analysis, and machine learning, as well as how data scientists derive information and insights from actual data, through practical exercises. So don't let the trendy terms deter you. Start your education, develop your skills in this highly sought-after industry, and learn why data science is for everyone.
Course Link:- Data Science for Everyone
6) Data Engineering for Everyone:-
You will learn about the fundamental duties of a data engineer, how they differ from data scientists, and how they help the flow of data within a company in this course. You'll follow Spotflix, a made-up music streaming service, to learn how their data engineers gather, clean, and classify their data through practical exercises. By the end of the course, you'll have a strong understanding of what data engineers perform at your company, be prepared to speak with one, and be ready to embark on your own journey as a data engineer.
Course Link:- Data Engineering for Everyone
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