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2. 5 free resources every data scientist should start using today

   www.aol.com/5-free-resources-every-data...

   Before jumping into popular MOOCs or purchasing recommended books on Amazon, I started by subscribing to various data science and data engineering newsletters. 5 free resources every data ...

3. SWAYAM - Wikipedia

   en.wikipedia.org/wiki/SWAYAM

   SWAYAM has accumulated 203 partnering institutes, 2,748 completed courses, 12,541,992 student enrollments, 915,538 exam registrations, and 654,664 successful certificates. [ 7 ] SWAYAM (meaning 'Self' in Sanskrit ) [ 8 ] is an acronym that stands for "Study Webs of Active-Learning for Young Aspiring Minds" [ 9 ]

4. Coursera - Wikipedia

   en.wikipedia.org/wiki/Coursera

   A free course can be "upgraded" to the paid version of a course, which includes instructor's feedback and grades for the submitted assignments, and (if the student gets a passing grade) a certificate of completion. [57] [60] Other Coursera courses, projects, specializations, etc. cannot be audited—they are only available in paid versions ...

5. Data science - Wikipedia

   en.wikipedia.org/wiki/Data_science

   Data science is multifaceted and can be described as a science, a research paradigm, a research method, a discipline, a workflow, and a profession. [4] Data science is "a concept to unify statistics, data analysis, informatics, and their related methods" to "understand and analyze actual phenomena" with data. [5]

6. Massive open online course - Wikipedia

   en.wikipedia.org/wiki/Massive_open_online_course

   A data science MOOC began in May 2013. [74] In May 2013, Coursera announced free e-books for some courses in partnership with Chegg, an online textbook-rental company. Students would use Chegg's e-reader, which limits copying and printing and could use the book only while enrolled in the class. [75]

7. Computer science - Wikipedia

   en.wikipedia.org/wiki/Computer_science

   Computer science is the study of computation, information, and automation. [1] [2] [3] Computer science spans theoretical disciplines (such as algorithms, theory of computation, and information theory) to applied disciplines (including the design and implementation of hardware and software).