The platform provides a great opportunity to work with industry experts and other AI professionals on a variety of innovative projects.
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This Omdena Local Chapter Challenge runs for 6 weeks and is a unique experience to try and grow your skills in a collaborative and safe environment with a diverse mix of people from all over the world.
You will work on solving a local problem, initiated by the Omdena Ethiopia Local Chapter.
Information obtained from the Ethiopian Coffee and Tea Authority revealed that coffee berry disease (CBD), CWD, and coffee leaf rust (CLR) are the three major fungal diseases of Arabica coffee, reducing coffee production and consumption in the country. The approach employed for illness surveillance is observation with the naked eye, which is time-consuming, expensive, and requires significant competence. Therefore, it is important to automatically identify the diseases without the need for experts.
We can leverage the use of deep learning, object detection, and image classification to solve this problem.
Deep learning methods have been introduced for the detection of different types of coffee plant diseases caused by pests and pathogens. These diseases can be classified by machine learning techniques like segmentation, and classification along with the estimation of the severity of stress.
Omdena Local Chapter Challenges are not a competition or hackathon but a real-world project that will grow your experience to a new level.
A unique learning experience with the potential to make an impact through the outcome of the project. You will go through an entire data science project lifecycle. This covers problem scoping, data collection, and preparation, as well as modeling for deployment.
And the best part is that you will join the global and collaborative community of Omdena with tons of benefits to accelerate your career.
Beginner-friendly, but also welcomes experts
Education-focused
Open-source
Duration: 4 to 8 weeks
The platform provides a great opportunity to work with industry experts and other AI professionals on a variety of innovative projects.
I feel Omdena is the stepping stone to discover the true potential of AI.
After all this mind-blowing experience, I feel much closer to the person I wanted to be for a very long time: a technology change maker.
I have learned so much in several domains including data mining, AI, ML, transfer learning, NLP.
Working in a collaborative project helped greatly in boosting my data science confidence.
After the Omdena project, I see that career adaptation was a necessary thing in today’s trends.
Collaboration across continents, time zones, and perspectives, especially on a social science-linked challenge was mind-opening.
Joining Omdena was an important career milestone. A unique way of learning and contributing to social good.
Collaborative AI enables robust AI solutions through sharing knowledge, perspectives, and promoting diversity and inclusion.
The community made me feel a sense of freedom and provided a non-judgmental environment where I was enabled to help others.