From writing code on an Android tablet to becoming an Outreachy intern at Ersilia and now on my way to being a 'world class' data scientist, in this post, I write about how I got into the tech space and persevered till I got a breakthrough.

The Genesis

I got into the tech space in 2020 but I felt frustrated because I didn't have an efficient laptop. I learnt Python's syntax first, then moved to HTML and CSS.

In 2021, I wanted to niche down but I had to make a choice based on the state of my laptop, which was a mini laptop. I tried front-end web development but I didn't think a mini laptop was a good tool. I ventured into data analysis but the laptop was so slow. I never thought of giving up. I only thought of new ways.

At the beginning of 2022, technical writing started popping up on my timeline on Twitter. I did my research and saw that it was a nice way to get into tech through the 'back door' so to speak.

Progress

After settling with technical writing, I began building an audience around technical writing, open source and Python programming language.

My audience was growing (still is), I carried out a lot of research on technical writing to develop myself, sent messages to experienced technical writers, joined groups, participated in Twitter spaces and applied for jobs.

Breakthrough

I applied for the Outreachy internship, Google Summer of Code and She Code Africa Contributhon and got into all three (though I had to forego GSOC and didn't pass the interview stage for She Code Africa's Contributhon). Outreachy has been a blessing, and I am forever grateful for the opportunity.

I am contributing to a project (called Ersilia) that has to do with data science, machine learning and artificial intelligence so it was easy for me to go with data science asides from technical writing.

Next steps

I started upskilling in data science in June though I already had a head start in 2021. I understand that to be a good data scientist, one has to be knowledgeable in a myriad of topics in mathematics, statistics, programming and industry. I have covered the basic concepts of data science, the required topics in statistics, SQL, basic programming with Python, data analysis and visualisation with Python.

Currently, I am practising data analysis and visualisation on data sets so I can be good at it before I move on to web scraping, mathematics and building machine learning models. Sometimes, what I need to know can be overwhelming, but data is pretty interesting so I don't mind. I'm having fun :)

My Career goals

My goal is to be a data scientist for startup companies. However, I know I need to work in a startup before I could be of help to other startup companies.

Technology and business are exciting to me and I'm grateful to be contributing my own quota in my own little way.

To keep up with my tech jouney, follow me on Twitter