I have always wanted to transition into tech and luckily for me I stormed into the Enugu state tech hub internship program, I applied, I was accepted and my data science journey started. The experience has been a roller coaster ride with lots of brain racking experience, will say it has not been a smooth ride but I scaled through as we are on the last month of the program(I pat myself on the shoulder for hanging on and not giving up even when it started getting tough *smiles)

Now, part of the internship includes a hackathon project at the end of the internship which is the purpose of today’s blog. I was paired with a group of people from different fields of tech, we were made up of Frontends, Project Managers, Product Designers, Cloud Engineers, and of course Data Scientists.

We were tasked to build an indigenous language learning platform (Igbo language to be precise), we used Figma to ideate the name of the platform, the colors, and our audience target with reasons, we came up with the name ROOTS which connotes the idea of starting at the foundation of Igbo Language, with adults being our main audience and green and purple being or color palette.

We also used click-up to assign tasks by project managers to each of us for each quest.

My First task was to write the KPI for our platform

KPI means the Key Performance Indicators and I came up with some needed for our platform which includes

• Numbers of registered users KPI: This KPI measures the total number of users who have signed up for an account on the language learning website. It is a simple metric that can help you track the growth of your user base and determine the effectiveness of your user acquisition strategies.

• User retention rate KPI: This KPI measures the percentage of users who return to the website after their initial visit.

• Lesson Completion rate KPI: This KPI measures the percentage of users who have completed a lesson on the website.

• Quiz completion rate KPI: This KPI measures the percentage of users who have completed a quiz on the website.

• Time onsite KPI: This KPI measures the amount of time that users spend on the website.

• Revenue KPI: This KPI measures subscription fees, advertising, in-app purchases and other means of generating revenue and it will depend on a variety of factors including the revenue model, target audience, competitive landscape and the platform's cost structure.

I did not find the KPI tasking and felt it was going to continue like that till the next task came.

CHATBOT

For the next task, I and my fellow data scientists were assigned to work on chatbot integration for customer interaction using python for our language learning platform. This was the most tasking and brainstorming part of my project, but we managed to pull through and learned through the process too. We imported the torch, nltk, and chatterbot library on python IDE, designed the conversation flow, trained the chatbot using PyTorch, built it, and tested and refined it but we could not deploy it to the main product.

We tried using IBM Watson and DialogFlow, it was somewhat confusing that we ended up using TileDesk and it worked for us.

In all, we are in the final stage of presenting a perfectly working website with my teammates.

This project taught me how to work with people and communicate thereby making me feel real-life work experience, it also enhanced my internet research culture (asking the right questions to get the desired answer). It was a tough ride but with teamwork, we overcame and succeeded.

Watch out for our Igbo learning platform ROOTS!