Maintained and developed new applications and application features for multiple companies under contract, using various frameworks, libraries and tech stacks.

Relevant Course Work:

Relevant Course Work:

I am working with two of my colleagues to develop a platform to encourage civic education and conversations about leaders and leadership with our main focus being Kenya. We aim to use the platform to disperse information translated into English, Swahili and native languages to encourage more conversation even amongst the uneducated. We are working to develop an AI fact-checker to track and stop misinformation on the platform. We are also working on an AI chatbot to give more details on articles written in various languages when prompted. This platform will act as an online log book for all decisions made and occurrences in leadership and attach a face to such.

This is a development of a platform to create awareness for orphanages in Kenya and other countries in the region. The aim is to increase the conversation had about orphans in the area, increase finances poured into local orphanages and encourage people to adopt more orphans in the region. With the support of the sponsors I am in conversation with, we plan on putting these orphanages in the media more so people can see them and also get the children in the orphanages more equipment and books for learning and development.

The focus of this project was to assess the use of data mining and machine learning to detect and prevent internal fraud with a focus on procurement fraud which is one of the main sources of fraud, especially in my home country, Kenya. The early stages of the project took 3 months to perform research on its feasibility, perform research on the techniques that would give the most prime results, collect sample data through data mining and develop a rudimental testing application which was done and assessed to be a successful project by my supervisors. The project's future is centred on finding and optimizing deep mining techniques to get more accurate results, working out the live storage burden for data and developing a more user-friendly application.

This was a class project with the main problem statement to use deep learning to solve common problems and document potential daily applications.

The project I did was the use of Deep Learning to identify emotion within speech. This required the use of Ravdess labelled data to perform. The project was argued to be a solution in emergency and distress handling situations such as for police officers and therapists, in a case where they do not have direct contact with the individual of concern

The project was focused on using Machine learning to determine potential Malaria hotspots within the Sub-Saharan region. The project used data provided by the world bank, and using the data of regions with a high Malaria index, the project could predict where anti-Malaria resources should be distributed. The project report an accuracy of 79%, and with further tuning, it was projected to have an accuracy of 88%

This was a hackathon where the challenge was to develop a technological solution to boost, re-establish and grow social interaction after the covid's adverse effects on social interaction.

This was a pitching challenge where we were to present feasible and student-led innovations that were within our capability. My team and I presented Lwandle, our fish farming venture, where we managed to go through all the stages and win.

We got seed funding and mentoring which were part of the reasons that enabled us to start the venture

HultPrize is an incubator that carries out mentorship and provides seed funding of 1 million US dollars over the summer for various ventures established within institutions. Through Lwandle, our fish farming venture, we managed to get through the campus levels and qualify as one of the final groups in the regionals in Nairobi, Kenya.