Top 3 Free Online Courses for Data Science Certification: Learning about data science can seem very daunting, but many different online courses can help. Since the primary functions of data science are carried out online, it only makes sense that you learn about them online. Using Online Course Report’s exclusive methodology, we’ve searched high and low for the best no-fee courses for data science. The courses on the list below are all entirely free for students and are hosted by preeminent learning institutions and educational sites. If you have always been curious about data science and wondered whether or not you could do it, look no further than our list of these free online courses for data science certification.
1. IBM Data Science Professional Certificate by Coursera
IBM is perhaps the most prolific company in computer history and is undoubtedly a reputable resource from which to learn about data science. IBM has partnered with Coursera to create this data science specialization, which includes 9 courses that take approximately 11 months to fully complete. This is truly an in-depth look at data science that will fully prepare you to enter the IT world and start working. The courses within this specialization include topics like what exactly data science is, tools for data science, data science methodology, Python, databases and SQL, and data visualization. At the end of the specialization, you will also complete a capstone project that is designed to give you a sense of what real data scientists deal with in their everyday careers. Nearly 40 per cent of the students who completed this best free data science online program began a new career upon finishing, and you can earn a shareable certificate for free when you fully complete the specialization.
Cost: Free
Certificate: Yes
Time to Complete: Approximately 11 months
Curriculum: Beginner
2. Data Science Specialization by John Hopkins University by Coursera
This selection of ten courses from Coursera will leave you fully prepared to take on a career in data science, all for free! More than 400,000 students have already enrolled in the course, and it has a 4.5 out of 5-star rating with more than 80,000 reviews. You have the option for a flexible schedule when you enrol in this specialization, meaning you can set your own deadlines for projects that work with your schedule. When you finish the coursework, you will also earn a shareable certificate that you can share on a resume or with employers. Throughout the free online course, you will delve into topics like GitHub, machine learning, R programming, regression analysis, data analysis, debugging, data manipulation, data cleansing, and cluster analysis. The specialization takes about 11 months to complete if you work at a pace of 7 hours a week, and it is taught by three professors from the John Hopkins University Bloomberg School of Public Health.
Cost: Free
Certificate: Yes
Time to Complete: Approximately 11 months
Curriculum: Beginner
3. Become A Data Scientist Specialization by LinkedIn Learning
Everyone in the professional world is familiar with LinkedIn, as it is perhaps the most expansive and trusted professional networking site on the internet. Typically, the site operates on a subscription basis where users pay to access all of the site’s content. Luckily for you, they offer a 1-month free trial for new users where you can access the entirety of this specialization for free. Whether you have experience in IT or not, this data science specialization will help to prepare you for a new job. There are 8 learning items that make up more than 17 hours of content within the course, meaning you will do a deep dive on many important topics including data science fundamentals, statistics foundations, data governance, and data mining. At the end of the free online data science course, you will earn a certificate of achievement courtesy of LinkedIn, which can easily be shared with your profile.
Cost: Free
Certificate: Yes Try a free trial for Linkedin Learning.
Time to Complete: Approximately 17 hours
Curriculum: Beginner
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