Data analytics is getting increasingly important as a 21st-century digital skill. It is one of the most in-demand skills among companies and organizations. In fact, Data Scientist was recently ranked as the number one job on a top job recruiting platform, Glassdoor. In this article, we are going to explore top free online courses to master data science.
Individuals with a broad understanding of data analytics concepts are now more in demand, regardless of the role they hold, despite the ongoing demand for traditional data scientists with their expertise.
So whether you’re looking at specializing in data analytics or simply securing your career for the future, a free online course is an excellent way to get started.
Read on, as I introduced you to some of the best free online courses to master data science. While some of the courses don’t follow a particular schedule and you might not always have access to a tutor, if you are someone who is capable of learning at a personal pace, they could be an amazing resource for you. All of the courses feature readily available syllabi, lecture, and assignment information and some are even sourced from real courses in top-ranking universities.
While all of the courses’ learning materials are freely accessible to anybody looking to advance their data knowledge and skills, some of them may charge fees at the end of the program if you want formal certification or accreditation of completing the course.
So are you ready to kick-start your career in data science? Then read on! And don’t forget to leave a comment if you have further inquiries.
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Top Free Online Courses To Master Data Science
There are many free courses online that can help you learn and master data science. These courses are highly rated and can provide a strong foundation in data science. They cover a wide range of topics, including programming in Python, working with data, and using machine learning algorithms. Additionally, they are taught by experienced instructors from top universities and companies, so you can be confident that you are learning from experts in the field.
Some of the best ones include:
1. Data 8: The Foundations of Data Science by UC Berkeley:
Foundations of Data Science by UC Berkeley is a three-course sequence that teaches you how to combine real-life data with Python programming skills to ask questions and explore any problems that you encounter in any field of study or a future job, or even in everyday life. It is intended for students who have not already taken statistics or computer science courses.
As soon as you sign up, you get two options:
1) the ability to audit the courses for free, or
2) you can pay to take the courses and also receive a professional certificate at its completion.
However, the audit option is your friend if you’re looking for free.
2. Data Science Fall- Skiena:
Data Science Fall was produced 5 year ago by Steven Skiena. The course covers data mining, machine learning, data visualization, and statistical analysis. It also includes practical exercises and projects.
3. Distributed Data Analytics(HPI University of Potsdam):
The many technologies used to develop distributed, data-intensive systems are covered in this free data science course. Theoretical ideas (such as data models, encoding, replication, etc.) and some of their real-world applications (such as Akka, MapReduce, Spark, etc.) are also discussed in great detail. The course specifically focuses on data analytics because workload distribution is a concept with numerous applications.
4. Data Science by Harvard University:
The lectures and course materials for Harvard’s data science course are all made freely available online so that you can learn at your own speed. The course is thorough and technical enough to turn you into an expert by the time it is finished, even if you don’t earn a degree from one of the most prominent institutions in the world.
This course is a component of a data science degree and is intended for students who have some background in, or are currently studying, core subjects like programming, maths, and statistics. But if you’re committed enough, there are enough free materials on those topics to make this a practical choice for individuals who aren’t in academics.
5. Introduction To Computational Thinking And Data Science by Massachusetts Institute of Technology (MIT):
This free online data science course is ideal for students with little to no programming expertise. Students are encouraged to set modest goals and feel at ease with coding during the course’s programming component. By the end of the course, you will be able to perform engaging projects in Excel that include programming components and also have a better understanding of the role computing plays in problem resolution.
6. Introduction to Data Science by Johns Hopkins University on Coursera:
Designed to provide a thorough summary of what data science is, how it operates, and what it may be used for, this course provides a technical introduction to data science, but it focuses on helping those who need to oversee data scientists or data science projects comprehend the ‘big picture’.
It is a relatively quick course that only has one module and can be finished in under a week. It’s a great introduction for those who just want to learn the terminology and understand how to create a data science strategy without necessarily needing specific instructions on how to use the technical tools involved.
7. Introduction to Data Analytics by IBM on Coursera:
Python, SQL, and data visualization are just a few of the key data science ideas and technologies that are covered in this course by IBM. It is intended primarily for first-year students from any major who have never taken a statistics or computer science course before.
The course consists of lectures, homework assignments, and projects that require you to use real data to address real-world problems. In a fresh, cutting-edge, practical manner, the course teaches you all the essential concepts of an introductory statistics course. It incorporates contextual considerations like bias and data privacy. It also helps you gain a solid understanding of important computing concepts.
8. Introduction To Data Science In Python by the University of Michigan on Coursera:
Python is one of the programming languages that is most frequently used in the industry, and for good reason, as anyone who wants to get their hands dirty with some real coding will quickly discover. When paired with a number of free, open-source libraries, it may be learned in a reasonably short amount of time and used to conduct a variety of extremely strong data science tasks.
By presenting Python functions that are used to prepare and manipulate large datasets as well as proven methods for drawing conclusions from data, this course acts as a beginning step on that journey. It is expected to take four weeks to complete, with three to six hours per week spent learning or working on activities.
9. Data Science Methodology by IBM on Coursera:
This IBM course offers thorough hands-on labs and projects that will allow you to practice your newly learned skills and knowledge on actual data sets while also learning the technique involved in solving data science problems. It covers the fundamental ideas and methods of data science methodology, such as data preparation, data cleaning, and data exploration. The vast syllabus of this course is what made it rank among our top free courses to learn data science online.
In addition, at the completion of the course, you will receive a digital badge from IBM designating you as a specialist in data science fundamentals in addition to a Specialisation completion certificate from Coursera. The IBM Data Science Professional Certificate accepts this Specialization as credit.
Final Thoughts on Top Free Online Courses to Master Data Science
Data Science is an exciting career that allows you to solve some of the most interesting problems in the world and the best way to master it is to practice and get hands-on experience working with real-world data. The courses listed above can provide a solid foundation, but you will need to continue learning and practicing to become an expert in the field.
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