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2. 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 ...

3. Online Classes That Are Worth the Investment - AOL

   www.aol.com/online-classes-worth-investment...

   The course is free to audit or pay $139 for a verified certificate. Check with your employer to see if they will reimburse you for your learning expenses. See: 20 Hot Jobs That Pay More Than $150,000

4. 50 Incredibly Cool Things That Are Free Online That Everyone ...

   www.aol.com/52-helpful-things-free-everyone...

   Coursera - Online courses & Certifications. Not all courses/certifications are free, but worth it) Cybrary - The Cybersecurity and IT Career Development Platform

5. Massive open online course - Wikipedia

   en.wikipedia.org/wiki/Massive_open_online_course

   Course developers could charge licensing fees for educational institutions that use its materials. Introductory or "gateway" courses and some remedial courses may earn the most fees. Free introductory courses may attract new students to follow-on fee-charging classes. Blended courses supplement MOOC material with face-to-face instruction.

6. Top 10 free Coursera courses to learn something new

   www.aol.com/top-10-free-coursera-courses...

   Coursera is a leading online learning platform for higher education that offers courses from more than 200 of the world's top universities and industry educators — from Ivy League American ...

7. Andrew Ng - Wikipedia

   en.wikipedia.org/wiki/Andrew_Ng

   His machine learning course CS229 at Stanford is the most popular course offered on campus with over 1,000 students enrolling some years. [24] [25] As of 2020, three of most popular courses on Coursera are Ng's: Machine Learning (#1), AI for Everyone (#5), Neural Networks and Deep Learning (#6). [26]