EDIT: DataLit and the ShoolOfAI have officially been taken down as the courses online were all bogus, poorly edited compilations of other peoples hard work. I leave this post up here ONLY for completion and a review of what I've learnt so far. For reference a better (and legitimate) alternative MOOC is Fast.AI by Jeremy Howard

Why?

As you may already know, up until today I'd been diligently working through the amazing machine learning course by Andrew Ng. My original plan was to finish the remaining 3 weeks before starting a more application-driven MOOC. However, a few days ago I chanced upon Data Lit by Siraj Raval and was immediately taken back by how it taught both the theoretical AND practical side of AI simultaneously. I've been considering the course ever since and today have finally decided to pull the plug and stop working through the old course. I'd like to take the time here to detail what I've been doing, why I'm changing and how thing's may look going forward.

Did intention arise before the awards?

After discussing whether to change courses with a teacher of mine, I had a realization, I wasn't going to buy the certificate and yet I continuously obsessed over all assignments, (no matter how irrelevant they felt). This caused me to become side-tracked, aimlessly learning, having completely forgotten my end goal of being able to:

• Create working models by myself
• Understand, interpret and contribute to others work

Although it is easy to blame the course when judging my progression with time it's clear that what I first needed is no longer what I desire. Andrew Ng's MOOC had insight and usefulness however MY lack of consistently re-evaluating what I needed to learn and how I planned to acquire knowledge blinded me to why my progress had almost haltered.

The Difference?

Data Lit still has quiz's, programming assignments and more you may say! But this time I have brutal awareness of:

• A the need to consciously counter the impulse to learn for formalities
• A clear goal to create personal projects with what I learn straight away
• A slowly forming background from reading machine-learning books

In short my awareness of my previous mistake being my flaw is what shall allow me to prosper with the new course

My Hope?

When I was looking into the Data Lit course, I found few resources, guides/tutorials, articles/review or even recommendations and so I aim to provide these.

For anyone considering this MOOC, here's a list of what I'm going to create throughout the course:

• My own solutions to any programming assignments
• Guides explaining any topics which I find excessively difficult to understand
• Extra free resources which aren't included, but I find beneficial

Here's a list of what I'm planning to judge the course on afterwards:

• What the course teaches well/not so well
• How much time's required for the course (if you're working as hard and fast as possible)
• The overall teaching style
• The ability to take you from zero to hero (where you have the technical knowledge to get a job)
• How well it balances teaching theoretical and practical knowledge
• The number of content gaps are present (difficult topics which are skipped over/remain difficult to grasp)
• Who the course is for

THANKS FOR READING!

Now that you've heard me ramble, I'd like to thank you for taking the time to read through my blog (or skipping to the end).

Cover image sourced from here