The online resources I used to improve my technical skills

About 3 weeks ago, I shared a compile document with all my notes for interview prep. You can find that post [HERE]. I honestly never thought I would get so much positive feedback.

I got colleagues who put me in contact with their hiring managers and I even had recruiters contacting me. I was impressed! From the bottom of my heart, THANK YOU.

What were the resources I use during the all process?

After that post, another insight came to head, what were the resources that helped the most? Below, I described my journey from a non-technical background to where I am at today. For the recorded: I expect to graduate from The University of Chicago August 2020.

1. Everything started in 2018

March 2018, I enrolled on the Marketing Analytics Course from Berkeley (see more here) - I was living in Sydney, Australia, and I decided to apply for university in the USA. I had been working as a marketing expert for four years. I was looking for a shift in my career, but I was honestly not sure what analytics was like. This course gave me a good taste of things. There was no coding (only excel) but it was a good starting point for statistics.

July 2018, I enrolled on the Introduction to Python course from Microsoft (see more here) - I loved it! As I was preparing to apply for university, I wanted to understand if I would enjoy coding. This course was easy and fun. I subsequently did two more.

2. Acceptance letter from The University of Chicago

November 2018, I got accepted at The University of Chicago - I reached out students to ask for resources to prepare me for school. Srihari, Brent, and Loretta gave me a lot of good insights. I went ahead and did almost all the Statistics exercises on Khan academy.

March 2019, I had my 1st R workshop & Python class at school - I was desperate. Nothing seemed to make sense, and everything was hard and fast-paced. The programming class must have been one of the most painful classes I have ever taken BUT I learned a lot. My Professor helped me A LOT. I reviewed the code from each session at the end of the week and I re-did each of my Python homeworks three times.

May 2019, I started using Dataquest to improve my python skills - Every morning, 30 minutes to one hour. This was a nonnegotiable rule on my routine for two months. Plus, all my assignments and group projects.

3. Using coding for real world problems

August 2019, I started using Python at work - This is one of the things I am the proudest of on this journey. I automated a repetitive task of sending individual emails to 30 teammates with a python script. Three hours of work per week, I went to 3 minutes! I always pitch this during my interviews.

October 2019, I started using HackerRank to improve SQL and Python - I really enjoyed the SQL part, but Python was almost impossible to get anything right. I started having my first Data Science interviews and failing bad. I built a document with the most typical questions and typical code to use for code challenges.

January 2020, I went back to all my SQL assignments and did all of them again - Most of the questions I was failing in interview were SQL. I memorized the basic questions from HERE, then went back and did my assignments and repeated the HackerRank code for SQL. I reviewed my Machine Learning assignments and start studying models online (more here).

4. Practice makes perfect

March 2020, I imposed myself to work on a Kaggle challenge every month - I only pick subjects that I really like, and I use all the tools I have from my marketing background and all the skills I learned in this program. I have honestly enjoyed working on these projects a lot, especially during COVID-19 (See more on my GitHub).

You do not need many sources and platforms, you just to be engaged in the ones you pick. I hope you found this helpful .

List of sources: Khan Academy, Dataquest, HackerRank, assignments and interviews.

Photo by Christine Sandu & Artem Sapegin & ThisisEngineering RAEng & Bonnie Kittle on Unsplash

Daniela