How To Choose Your Online Course
Most online courses lack these aspects—your guidebook to choose the best among the best.
Pandemic impact laid the foundations for e-learning more than ever. As a result, hundreds of courses on every subject have been floating around on various platforms — Coursera, Udemy, LinkedIn, E-learning from Universities, etc.
So, given a choice, there need to be criteria for choosing a course.
Judgment Criteria :
- Date created and how often updated: I do want to point out that some of the most popular courses are outdated. These courses cover the pretext that they make the basics very clear. However, I don’t find it to serve any purpose as there exist several courses which cover basic to end with clarity. The syllabus is outdated because of rampant improvements, and the hard truth is that you keep on the need to update yourself.
- Depth in the subject: Online courses (most of them) just offer an introduction or an overview and will never cover any topic in-depth. You will always find it difficult to understand research on this topic. E.g., After taking a 6-month course on AI/ML, I will not be able to understand fully the latest research on GPT 3 mentioned by Open AI — but more online search may be required to build the wall. After taking a Fintech specialisation course, I will not be able to build a blockchain on my own — but I at least will be able to understand the terms and can help myself with a DIY video.
- Practicals (Hands-on): Git-hub posting, projects on real-world data, presentations on self-developed products, tricky real-world case studies, working models should all form part of the course syllabus.
- Presentation: Of course, a dull presentation, insufficient lighting, and unclear voice recording would deter the students from completing the course.
- Reviews: Obviously, you will look at course reviews online and then discuss with people who completed the course.
- Resolving doubts & Support: Courses that encourage more participation also have a window open for asking queries. In return, the platform should provide an excellent response to the queries raised.
- Post-course seminars: Some courses such as “The Science of well-being” on Coursera keep sending articles, scientific research conducted, new course material, updates years after completing the course. Great Learning’s course for ‘AI for Leaders’, which I attended, has been conducting some Data science sessions on a quarterly basis from the University of Texas at Austin post completion of the course. Such additional support post-course completion will bring in customer delight.
Your learning should never end with the online course completion certificate.
The above is just a starting step. After course completion, keep doing your research online to stay abreast of the latest updates and keep moving forward.
Note: Above can also be used as guidance criteria for course providers. So, please buzz me if the above comes to use while preparing your course.
