We are extremely happy to have selected our recipients of the month of the Omdena Scholarship Award. The selection is based on various factors including the effectiveness of the scholarship, the recipient´s story, and contribution to Omdena. It will be given for 3 months from April 2021 to June 2021 and can be spent on covering educational expenses.

For May 2021, We have allocated USD$350 that each recipient is able to spend on educational purposes, including paying for courses or buying educational materials.

This month, we have Marvin Odhiambo from Kenya and Ditiro Rampate from Botswana.

 

Who is Marvin Odhiambo?

Marvin is a research and data science specialist based in Kenya. He is passionate about technology and is a firm believer in leveraging data and artificial intelligence to build lasting solutions for businesses and uplift lives through innovation. Marvin possesses proficient knowledge in statistics, mathematics, and analytics, specializing in computer vision and natural language processing. He is self-motivated and a willing learner as that is the only way he knows how to keep growing.

Marvin joined “Kenya Red Cross Society – Assessing the Impact of Desert Locusts” challenge as a junior machine learning engineer to use multispectral data to assess the damage caused by desert locust invasions on the vegetation. And implementing supervised and unsupervised deep learning algorithms to build a land-cover type classifier.

 

 

Marvin

 

How will the Omdena scholarship help you in your career?

I am passionate about computers, software, and more recently, data science, and I have been looking for scholarship opportunities to help make my dream a reality. I always wanted to pursue a degree in Computer Science but finances have been one of the greatest hurdles that have meant this only remains to be a dream. Rather than give up on my dream, I opted for self-education with a focus on data science and my acceptance to the Omdena community has so far been the crowning moment of a long and industrious journey as it was an indicator that someone believed in my abilities despite not having a computer science degree as is often the case for many similar opportunities. I believe this scholarship will go a long way in pushing me closer to my dream of becoming a full-stack data scientist so I can be in the frontline leading the adoption of technology and leveraging its capabilities to enhance the quality of life in Africa. I am extremely grateful to Omdena for using a skill-based approach to judge an individual’s capability rather than solely relying on their educational background and I hope more companies and organizations adopt this approach to give more young people an opportunity to showcase their capabilities. This scholarship is a testament that if you keep working hard toward your goals, there will always be someone willing to help you get there as long as you remain consistent and work hard.

Thank you Omdena!

 

 

 

Who is Ditiro Rampate?

A versatile graduate of Bachelor of Science (Hons) Computer Systems Engineering from Botswana Accountancy College (in partnership with the University of Sunderland) with a special interest in full-stack development, data science cloud computing, and networks. He actively participates in open source and keep up with the latest news/trends through various articles, videos, and podcasts.

 

Ditiro

 

 

How did the Omdena experience help you in your career?

My continent Africa is composed of a young population of about 60% of which are under 25. Most countries are developing countries and have limited resources and heavily rely on the government. There are many socio-economic ills caused by overpopulation, migration, and a lack of sustainable opportunities.

My great aim is to liberate the lives of young people through the use of technology. Technology is lagging behind, and to solve our challenges, we need to adapt to what we have. TinyML is the technology in which can be used to curb these challenges. It can be used to improve food security, wildlife conservation, and healthcare. It has low latency, low power consumption, and only needs low bandwidth.

A scholarship will aid me to pay for the TinyML course as well as getting all the necessary materials to accomplish the course. For a start to get how machine learning tasks are taken at the production level, I have applied and been selected as a data wrangler on Omdena’s increasing energy access in Africa project.

I have joined Omdena as a Junior Machine Learning Engineer to work on a project with NeedEnergy. NeedEnergy is there to provide sustainable and clean energy solutions based on energy data.

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