Took me 3 years to finish this Coursera Course
The average completion rate of MOOCs is 15% and after almost 3 years, I am finally done with the Machine Learning Stanford Coursera course taught by Andrew Ng. It’s been a VERY LONG JOURNEY, and this is what I’ve learnt so far.
Before you take a course
1. Look at the level
It is normally written there: Beginner, Intermediate or Advanced. If you haven’t taken any courses on that topic or did not study that topic in school, it is best to stick to Beginner level courses.
I have a friend that took an Intermediate course on Coursera even though she was a beginner. I knew more about the topic than she did and didn’t enroll for the course because I knew it was too advanced for me. I didn’t say anything because I didn’t want to sound discouraging and it was a mutual friend that advised we take the course. A while later, I saw her taking another course, this time a beginner course and she said it was because she wasn’t able to follow the first course.
2. Look at the Programming Language
Don’t mistakenly enroll for a course that is taught in R when you only know Python or it is taught in C++ and you only know R
3. Look at the reviews of the course
I didn’t do this for this machine learning course, because at the time I had just joined Coursera but I was lucky. Some people aren’t so lucky.
What you need to do is look at 5 reviews each at 5 stars, 3 stars and then 1 star. This gives you an overall view of the experience of those who took the course.
4. Pay close attention to what the reviews are saying
For example, someone might put 3 stars and write “The coding challenges are too easy but the course is really good for understanding theoretical knowledge”. If you already have theoretical knowledge and you’re looking for practical knowledge, this might not be the course for you.
“This course is really great at explaining AWS Cloud but you need to get the hardware”. If you have the hardware that the course requires or can purchase it then go ahead but if you can’t, look for another course.
Look for comments regarding feedback, if the course does not have a good feedback system (i.e Instructors helping students out when they run into problems) then just look for another course
5. Look through all the topics being taught in every single week
Do the topics look familiar or foreign? Are they sparse or too many? Do they look random, or do they look like a gradual progression?
6. Speak to your mentors
Show them the course and politely ask that they review it and send you feedback on whether you should go ahead, or if they have another course they can recommend to you. Don’t waste your time doing a course that you mentor does not approve.
Once you have decided to enroll for the course
1. Set a timeline
A REASONABLE TIMELINE!! You’re not the Flash, nor do you have a photographic memory. You are human, you have other things happening in your life. Set a timeline unique to you. For example, I spend 2 hours watching and documenting a 15-minute video. THAT IS ME! I need to write things down, draw what has been illustrated [If I think it is relevant], add my own opinions and so on. Because of this, I can only watch 2 videos a day.
2. Try to get an accountability buddy
Someone who is doing an online course too. Motivate each other to keep going.
3. Set a separate space for your learning
I have a desk where I sit when I want to start watching my ML Coursera videos. Try not to rest on your bed when you’re watching your Coursera videos because you will SLEEP, take it from me.
Once you have enrolled for the course
1. BE CONSISTENT
I was doing this course ON and OFF for 3 years!! I kept on going. I’ve started and finished other online courses while doing this course. I never forgot about it. It is not going to be EASY but remember why you’re doing it.
2. Take written notes
Get a big 80 leaves note just for your course depending on how long the course is. I used approximately 2 80 leaves notes to fully document my ML Coursera course. Writing things down, helps to cement what you’ve been taught and, in the future, when you want to revisit the course, you don’t have to start watching all the videos again, you can just read your jottings
3. Don’t be afraid to ask questions
If you are having issues, search for it on the “Discussion Forum” and if you can’t find it then post it on the “Discussion Forum”. Most times, an instructor will get back to you within a few hours or within a week
4. PLEASE! Read the modules
I remember downloading Octave because I couldn’t afford MATLAB only to find out after finally sitting down to read one of the modules that I could have access to free MATLAB Online as a result of taking the course. I was so shocked at my lack of patience and most especially the time WASTED downloading and installing Octave
After taking the course
1. Take on a SIMPLE project
I plan on taking on a Recommender System Project very soon, to make use of all that I’ve learnt in this course
2. Pick up a textbook
Apparently, textbooks are better than courses, I’m yet to confirm that myself but I’ve picked a Deep Learning Textbook to help ease me into Deep Learning and its tools
3. Search for the next step
Reach out to people working in the ML Industry, tell them you’ve finished this ML course and ask what steps you should take after that. Most will advise you to take up a project. Some, might recommend a higher level course to you since you’ve now passed the Beginner level
4. Take time off to rest
If you have the privilege, take time off to rest. Finishing an MOOC course is really not easy, and it can be EXTREMELY DRAINING. So, take time off to rest and rediscover your hobbies and passions
