IBM recently predicted that the number of people employed as data scientists will rise by 28% over the next two years, reflecting the high demand for these professionals.
As the amount of data grows and new big data technologies become available, companies across all industries are beginning to reap the benefits.
As a result, it’s an excellent option for anyone seeking a lucrative job in a dynamic, cutting-edge industry
Even if you’re not pursuing an academic degree, you can still reap the benefits of learning more about data science through one of the best US data science masters degree programs I covered in a recent article.
Motivated individuals can also take advantage of the numerous free online tutorials and courses available as a launching pad for an exciting and financially rewarding career.
A free online data science course could benefit whom?
Data and analytics skills are becoming increasingly valuable to employers, regardless of their background or position in an organization..
The proliferation of self-service infrastructure and tools, which automate many of the technical but repetitive tasks associated with data cleaning, preparation, and analysis, has a lot to do with this. As a result, workers no longer need to get their hands dirty coding complex algorithms from scratch to perform increasingly complex data-driven operations, such as predictive modeling and automation.
A person who understands the principles, on the other hand, can more effectively use these tools than someone who doesn’t! To that end, if you’re looking to improve your analytical skills on your resume, check out these courses. One thing to keep in mind is that while these courses are free to take, some charge a fee upon completion for certification.
Specialization in Data Science at Coursera
John Hopkins University is one of the most well-known universities to offer online data science education through Coursera. There is a course and certification fee that must be paid if you want to complete the program, but this is waived for students who cannot afford it.
The specialisation is made up of 10 courses that cover statistical programming in R, cluster analysis, natural language processing, and practical machine learning applications. Students must produce a data product that can be applied to a real-world problem in order to complete the program.
Coursera – Making Decisions Based on Data
This PwC-provided Coursera course, which also focuses on business applications rather than theory, is also available through Coursera. To address today’s data challenges, businesses are using a wide range of tools and techniques, as well as a variety of roles for data specialists in modern organizations. In addition, students learn how to pick the best frameworks and tools to solve data problems. To wrap things up, students are given a project to implement a data solution in an actual company.
A Data Science Essentials course on EdX
However, it can be taken as a stand-alone course through EdX by Microsoft, which is part of their Professional Program Certificate in Data Science. Students are expected to know at least the basics of R or Python, the two most popular programming languages for data science. In addition to probability and statistics, students will learn about data exploration and visualization, as well as machine learning basics using the Microsoft Azure framework Despite the fact that the course content is free, students can purchase a certificate of completion for an additional fee of $90 (in this case).
Udacity – Machine Learning Introductory Course
An important part of data science is machine learning, and this course aims to give students an in-depth look at both the theory and practice of machine learning. As part of Udacity’s paid “nanodegree” in data analysis, this course teaches students how to select data sources and select the best algorithms for a given problem.
Getting Started with Data Science at IBM
IBM’s portal, formerly known as Big Data University and now renamed Cognitive Class, offers a number of free online courses. For those who want to learn the fundamentals of data science, this course is for you. As a whole, they should take about 20 hours to complete, but those who have previously studied computer science will likely progress more quickly than those who are completely new.
Data-driven learning at the California Institute of Technology
Video lectures and homework assignments are part of this course, which teaches machine learning. Students are expected to have a basic understanding of matrices and calculus before enrolling in this course, so it is not suitable for those who are new to math.
Become a Data Scientist with Dataquest
Dataquest, unlike the majority of the other companies represented here, is not a part of a university. In addition to free access to the majority of its course materials, the site also offers paid premium services, such as tutored projects. Uber, Amazon, and Spotify have all given their endorsements to the program, so it appears to be a good way to see if studying data science is something you’d be interested in doing without having to spend a dime.
Course on Data Mining at KDNuggets.com
KDNuggets, a well-known business and data science website, has compiled its own free data mining syllabus. There are modules on machine learning, statistical concepts like decision trees, regression, clustering, and classification (see my data science glossary for an introduction to these terms), as well as an introduction to practical implementations of the technology..
Master of Science in Open Source Data Science
This course is not provided by an organization or institution, but rather is made up of a variety of open-source materials and resources that can be accessed for free on the Internet. Natural language processing of the Twitter API using Python, Hadoop MapReduce, SQL and noSQL databases, and data visualization are among the topics covered. Additionally, it provides an introduction to the fundamentals of data science through the study of algebra and statistics. However, despite the lack of a certification, the program is a great starting point for anyone interested in learning more about data science.