Steve's Pyventures: TheRoadLessTravelled

Steve's Pyventures: TheRoadLessTravelled

How I Qualified for DataScienceNigeria 2019 Artificial Intelligence Bootcamp.

How I Qualified for DataScienceNigeria 2019 Artificial Intelligence Bootcamp.

A quick recap of a Data Science Enthusiast so far!

Milestones and an unplanned Perk.

November 11, 2019 marks a special milestone for me, actually a few milestones. So in honour of this, I'm writing my first-ever blog post. Cheers!

Good day, The biggest AI bootcamp in Nigeria is here! Will you be part of the best of the best who will make it to the all-expense paid residential Artificial Intelligence Bootcamp?...

This was a mail I received on September 24 from Data Science Nigeria. And below is a snippet of what I got on Data Science Nigeria's website today. Fresh from the oven!

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The Journey

I started my programming journey back in September, 2018 with the most highly rated course on Udemy courtesy of my mentor, Fakorede Abiola. It was fun, tense and voluminous, just like any other online bootcamp course out there (I'm shedding more light on this later). I didn't get to finish the course until May 2019.

Elated, I was planning on starting a Django bootcamp when a pen friend I met through Nairaland's programming section informed me about the ongoing InterCampus Machine Learning Competition being organized Data Science Nigeria.

Initially, I was scared to make the jump. I have this 2019 goalboard, I was planning on delving into Machine Learning (I'll be using ML from this point on) towards the end of the year.

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Buoyed by my mentor, I finally joined the competition. Turns out that's the best decision I've made this year. So far!

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But good things don't come this easy, do they?

The Hard Start

I joined the YouTube classes and oh boy! My battles started. I knew already that ML is 70% percent Maths/Statistics, 30% Computer Science. But I never realized the full implication until I started.

The classes were heavily based on calculations. I've always preferred practicals than theories.

I decided on supplementing my learning resources with Udemy courses. It was a disaster. There are lots of good courses on Udemy. And there are lots of crappy ones, too.

I got introduced to Machine Learning by Prof. Andrew Ng on Coursera. That's a good one, but heavily theoretical based. I've wasted around 4 months already, searching for the optimal course for me. Perusing through another theoretical course was not the best option for me, then.

My Escape

Finally, my lifeline arrived in the shape of Kaggle Learn. Fast, fun micro-courses with real-life practicals and applications.

Don't mind the estimated hours on their courses. The supposed 3 hours Intro to ML course took me more than 30 hours to complete.

Kaggle micro-courses are rough, tough and bumpy. But they are loads of fun.

The PreQualifying Kaggle Competition

The competition was a Staff Promotion Prediction Algorithm. 530 Data Scientists from all parts of Nigeria participated. They were only going to take the first 150, and I came 60th. My winning code solution is hosted here on Github, in case you want to have a look.

My Validation Interview

To certified the authenticity of the codes submitted by the participants, validation interviews were scheduled via Zoom. I had mine slated for October 31, but I missed it due to poor internet connectivity. I didn't get to exchange anything more than greetings with my interviewer before I lost connection.

So I had my interview rescheduled for November 2.

Reminiscing now, I think missing my initial interview was a blessing in disguise. I was so nervous and filled with tension. Supposed I'd had the interview that day, I might have flopped.

The 2nd interview went well. Uneventful, and simpler than what I'd envisaged. I think I aced it. Within 5 minutes, I was done.

What's Next?

I'm packing my bags, obviously. And I promised myself a blog post daily throughout my stay at the AI bootcamp, documenting everything I'll learn.

Okay. What's Really Next?

I'm delving into Feature Engineering, Geospatial Analysis and Deep learning. In that order. I also plan to continue my Mathematics for Machine Learning by January.

I'm writing my goals for 2020 soon. I've achieved a large share of my 2019 goals, already. In fact, I do think that I achieved more than I set out to achieve.

I'll continue sharing my journey, via these blogposts, unfiltered and regularly. Thanks to everyone who has been part of the amazing journey with me, all who believe in my potentials even when I didnt believe.

The world belongs to those who believe in the power of their dreams.

You can find me on Twitter @stevenkola6. See y'all.

#machine-learning#python#data-science
 
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