I recently realized that 1/3 th of 2021 passed away.
And I am still going consistently reading my 2nd book of the 3 books and gaining traction. But something was missing, the end Goal I think.
When the year started, few things were on mind to complete by the end of this year. First was to read those 3 books and second,
I wanted to give TensorFlow Developer Certificate exam.
“The further you get away from yourself, the more challenging it is. Not to be in your comfort zone is great fun.”
― Benedict Cumberbatch
Oh and I realized I am in my comfort zone, there was a lack of thrill. I revisited my journal to take a look what I wanted to do this year and this popped up.
Even more significant is The fun involved doing all this. Waking up every day at 4 and feeling you are getting up for purpose, makes you do all things you ever want.
So, Why am I writing this?
First, to make this post and people reading this hold accountable for my progress and Goal.
Second, If you are also someone like me, the courses I took might help.
Third, to analyze my planning and take a look back where I started.
The strategy is for my specific needs and considering my stage of learning in this journey and is inspired from Daniel's Curriculum.
I had fairly good experience in utilizing pandas and NumPy at this point of time. Missing things were Machine Learning and Deep Learning.
I was already going through more in-depth exploration of Machine Learning by reading the 2nd book of my curriculum, Hands-on Machine Learning with Sci-kit Learn, Keras and TensorFlow but for Deep Learning, I need to start from somewhere.
To begin the preparation, I need a firm grasp over Deep Learning to feel confident enough to know what I am coding. I was going to start with the Deep Learning Book anyway, but a course might help letting me connect the dots.
Ever got that "Eureka" moment. I am talking about that.
For Deep Learning, I choose Deep Learning Specialization course on Coursera by Andrew Ng, a pioneer of the domain and a great professor.
The DeepLearning.AI TensorFlow Developer Professional Certificate course on Coursera will then prepare me to fulfill rest of the requirements.
Obviously, The Deep Learning course from Andrew Ng is available for free on YouTube and might be worth considering if you don't want to take the course or don't mind coding that much. If you already have a good understanding of the the topics covered in these courses (maybe from another course or a University course you took) than a brush up might be required.
To me it matters to learn by coding it first.
Here is the link to playlists:
But the TensorFlow isn't. But a bit of ramp up from other channel might do the thing. From official channel of TensorFlow this was most helpful I found:
But if would recommend it as the course line up with with the skills requirement described in the Handbook for the exam.
One thing is important,
Certification is nice to have, not a necessity.
What matters is learning and skills.
Lastly, I will also be taking a quick look at the last year MIT Intro to Deep Learning course to finish it up.
Let's see how it goes...