Personal Journey:
My passion in computers and technology started way back in my secondary school days where I'm afforded the opportunity to not just play with the latest iMac (1997) doing 3D designs for robots and other multimedia assignments or days just "club camps" where it simply involves being in the lab playing Counter-Strike or Unreal Tournament when lan shops are simply too expensive for poor students like us.
Somehow across the years, things change and I took on Accountancy as my Bachelors Degree at Singapore Management University (SMU). At my last semester at school, I got bitten by the entrepreneurial bug and decided to join my Dad in the Family Business in Construction.
First languages include Perl, HTML, Javascripts or rather - cut and paste jquery.
Well, then how did I get my foot in the AI door?
Started with Massive Open Online Courses:
- Machine Learning - Stanford - Andrew Ng
- Python for Everyone Specialization - University of Michigan - Charles Russell Severance
Completed:
- AI4I Singapore
- DataCamp (Python Programmer and Data Scientist with Python)
Finally my curiosity led me to complete an in person Masters:
My next journey into AI takes me to explore the depths of Software Engineering and that will be found in another post.
Now, how might I do it differently if I were to start over again today?
If you love building an online course backlog like me, let me provide a shortlist here
Months 1 & 2 (Math and Coding)
- Mathematics for Machine Learning Specialization (Imperial College London)
- Python for Everyone Specialization (University of Michigan)
Months 3 & 4 (Understanding Machine Learning)
Months 5 & 6 (Diving into Deep Learning)
- Deep Learning Specialization (deeplearning.ai)
- This will cover most of the common topics from Artificial Neural Networks, Convolutional Neural Networks etc.
If you like reading books, here is where I will go:
Months 1 & 2 (Math and Coding)
Months 3 & 4 (Understanding Machine Learning)
Months 5 & 6 (Diving into Deep Learning)
Other Learning Resources:
- AI Apprentice Field Guide - AI Singapore (disclaimer: I am an AI Apprentice)
- Google AI Education
- Coursera - Machine Learning - Stanford - Andrew Ng
While many of the above resources, excluding books are paid resources, they can be audited for free. But I do believe in some sort of "no pain, no gain" mentality. Thus, paying for the courses will motivate you to complete them hopefully just like it did for me. It will also help you plan and structure to complete them in the fastest possible way to spend the least possible.
That being said, I will be adding more free resources like books and videos in future posts as well as an exciting project that I have been working on at AI Singapore. Talk to you soon!
Disclaimer: All the resources above belongs to their owners. I do not own any of the copyright. Should you want them remove, please contact me at kenneth at ainewbie.org