The Healthcare AI & Data Literacy Challenge 2025 has ended!
Empowering Africa’s healthcare professionals to move from the sidelines to the forefront of the digital health revolution.
Cash Award Winners—Students
Top 3 Overall winners
Top Reports
AIDLC Proposal Submissions: Project Overview
| Full Name | Proposal Title | Affiliation/Field | Country |
|---|---|---|---|
| Omokiti Orezimena Diane | Seeing the Unseen: Leveraging AI and Data Literacy to Redefine Disability Healthcare in Nigeria | General Practitioner | Nigeria |
| Victor Ifeanyichukwu Okeleke | DrugSight- A Medicine Price and Information Identifier | Computer Science | Nigeria |
| Peter Olamikonipekun Awoniyi | A Data-Driven Solution to Reduce Medication Stock-Outs in Rural HealthCenters | Physiology, Ladoke Akintola University of Technology, Ogbomoso | Nigeria |
| ILO DORIS IFEYINWA | The persistent and high-stakes challenge of real-time patient monitoring during anesthesia. | Anesthesia Consultant, FMC Umuahia | Nigeria |
| ZAINAB Umar Faruq | AI-Assisted Risk Prediction Tool for Birth Asphyxia in Neonates in low resources setting. | Medicine and Surgery, Umaru Musa Yar'adua University Katsina | Nigeria |
| Williams Stonard Kaphika | A Data-Driven Solution to Improve Diagnostic Accuracy from Low-Dose X-Rays in African Hospitals | Medical Physics / AI & ML in Healthcare Research | Malawi |
| Aminu Umar Ahmad | Use of Artificial Intelligence to Improve CT-scan Early Detection of Stroke type in Emergency Care | General practitioner, UHF hospital, Kano - medical officer | Nigeria |
| OLATUNJI Nurudeen | A Data-Driven Approach to Address Patient Missing Results in Startup Laboratories. | Medical Laboratory Science | Nigeria |
| Omoyajowo David Oyindamola | Predictive Genomic Surveillance for Cervical Cancer in Nigeria: An R-Powered Model for Early Risk Detection and Clinical Decision Support. | Medicine, University of Ibadan | Nigeria |
| Enobong Nkereuwem Inwang | Pharmacogenomics & Adverse Drug Reaction Risk: A Data-Driven Approach to Personalized Drug Safety | Pharmacy, University of Calabar | Nigeria |
| Akinwale Priscilla | A Data-Driven Approach to Identify Factors Affecting Patient Satisfaction and Recommend Improvements to Healthcare Delivery at Hexon Hospital. | Public health, Primary Healthcare, Lagos - Registered Nurse | Nigeria |
| Akinwale Priscilla | A Data-Driven Approach to Identify Factors Affecting PatientSatisfaction and Recommend Improvements to Healthcare Delivery at Hexon Hospital. | Public health, Primary Healthcare, Lagos - Registered Nurse | Nigeria |
| Osmond Anokwulu | A Predictive Model to Break the Cycle of Recurrent Malaria | General Medicine, Rhowil Total Care Medical Centre, Lagos - Medical Officer | Nigeria |
| Chukwuzitere Chisom Amarachi | Power Bi for Reducing Medicine Stockouts in Rural Clinics. | Medicine, Alex Ekwueme Federal University Teaching Hospital | Nigeria |
| Manjunath S | Predicting Medicine Stockouts to Save Lives in Rural Clinics | Bachelor's of Engineering, Visvesvaraya technological University | India |
| JAMIU Opeyemi Shittu | AI-Driven Knowledge Preservation System for Indigenous Medicine Knowledge Using Machine Learning, Generative AI, and Power BI Analytics | Public Health, Personal clinic, Iwo - Medical officer | Nigeria |
| Toyinbo Folorunsho | Inefficient Allocation of Blood Supply | Medicine, Federal University of Health Sciences Otukpo | Nigeria |
| SAMUEL IFEBUCHE AGADA | AI-Powered Chest X-ray Interpretation and Data-driven Workload Optimization in Radiology | Medical Radiography, Orange medical diagnostics | Nigeria |
| Aleshinloye Jameelah Bolanle | AI-Enabled Self Blood Pressure Monitoring Tool for Hypertensive Patients | Medicine, University of Ilorin | Nigeria |
| Samuel Fodop | Using Artificial Intelligence to Bridge the MentalHealth Care Gap Among African Medical Students | Catholic University of Cameroon | Cameroon |
| Talent Tondori | Early Detection Of Depression In Youth Using Digital Behavioural Data And Machine Learning Approaches In Zimbabwe | Medicine, Midlands State University | Zimbabwe |
| Shakirullah Monsuroh Ayinke | A Data-Driven System for Monitoring and Preventing Respiratory Distress in RuralCommunities | Anaesthesia Technician, Lagos State School of Anaesthetic Technician | Nigeria |
| Ogundipe Precious Adedoyin | N/A | Medicine, Ladoke Akintola University College of Health Sciences, Ogbomosho | Nigeria |
| Taiwo Gift | A Data-driven Approach To Reduce Maternal Mortality Rates in Rural Nigeria. | Medicine, University of Abuja Teaching Hospital | Nigeria |
| Divine Godwin | HealTrak: Empowering Health,One Conversation at aTime | Human Anatomy, Ahmadu Bello University, Zaria | Nigeria |
| Divine Godwin | HealTrak: Empowering Health,One Conversation at aTime | Human Anatomy, Ahmadu Bello University, Zaria | Nigeria |
| Edidiong Moses | AI-Powered Centralized Maternal Health System | Biochemistry | Nigeria |
| Kuku Zainab Oreoluwa | Tracking Blood Donors To Prevent Multiple Donations Within 3 Months | Laboratory science, Intern medical laboratory scientist, Obafemi Awolowo University Teaching Hospital | Nigeria |
| Dr Rahel Shibeshi | Predicting High-Risk Pregnancies in Resource-Limited Communities UsingClinic and Community Data | N/A | Ethiopia |
| Lois Adubea Adu-Yeboah | A Data-Driven Approach to Reducing Patient No-Shows | Midwifery, Lekma Hospital | Ghana |
| Aremu Enoch Adeyemi | Data-Driven Prediction of Ambulance Accessibility in AfricanMegacities | Medicine, Ladoke Akintola University of Technology | Nigeria |
| Tendo James Lubwama | AI Model for Predicting Preeclampsia Risk Among Expectant Mothers in EasternUgandan Hospitals. | General Medicine, Junior House Doctor, Mbale RRH, Mable | Uganda |
| Mowaninuola Olasupo | Bridging Language Gaps in Hypertension Care Among Nomadic Populations in Omupo, Kwara State | Medicine, University of Ilorin | Nigeria |
| Oluwakayode Aje | Leveraging Generative AI for Early Cancer Detection in Somalia | Physiotherapy, National Obstetric Fistula Centre, Benin City | Nigeria |
| Udeh Chioma | Development Of An AI System For Predicting Sickle Cell Crises | Medicine, Alex Ekwueme Federal University Ndufu-Alike Ikwo Ebonyi State | Nigeria |
| Esther Ogodo | Predictive Support System to Improve MedicationAdherence in Chronic Disease Patients | Pharmacy, Pharmacist intern - Ogun State Hospital Management Board | Nigeria |
| Olukolatimi Duyilemi Shalom | Predictive Modeling for Hospital Readmission | Physiotherapy, Intern physiotherapist, Federal Hospital | Nigeria |
| Tolulope Babawarun | Enhancing Data Quality and Analytical Capacity for Assessing Quality Standards in Adolescent Health Service Provision | N/A | Nigeria |
| Kaputo Jezreel | Smartphone-Based Machine Learning Tool to Reduce Maternal and Infant Mortality. | Nursing, University of Lusaka | Zambia |
| Taofeeka Abayomi | Predictive Dashboard for Zoonotic Disease Detection in Abattoirs | Master student | Nigeria |
| Adenike Adegeye | AI-assisted patient education and communication product for interpreting radiological imaging reports. | Radiology, Resident doctor, University College Hospital, Ibadan | Nigeria |
| Victor Nwaolise | A Data-Driven Decision Tool for Pharmacist Deployment | Pharmacy, Nnamdi Azikiwe University, Awka | Nigeria |
| Francis Nwabueze | A Data-driven Augumented Reality Tool for Easier Venipuncture (VeniSight) | Medicine, University of Benin | Nigeria |
| Ojo Goodluck Ayomiposi | Predicting and Preventing Lead Poisoning in African Children. | Medicine, University of medical sciences, Ondo, Ondo State. | Nigeria |
| Dr. Ruby Reason-Onya | Maternal Early Warning AI-System | Medicine, Masters in Health Inforrmatics | USA |
| Edikan Effiong Bassey | Predicting poor glycemic control in diabetic patients using routine laboratory data | Medical Laboratory Science | Nigeria |
| Aniekeme Nse Udo | How can antimicrobial resistance be more easily detected? | Alpha Pharmacy - Full time Pharmacist | Nigeria |
| John Chidozie DURUSON | PerTriStem: An AI-Powered System to Optimize Clinical Trials in Africa | Clinical Physiology, College of Medicine, University of Lagos | Nigeria |
| Oguntade Fiyinfoluwa Christianah | An Artificially Intelligent Triage System Aimed at Identifying Extent ofTraumatic Injuries. | Medicine and Surgery, Lagos State University | Nigeria |
| Chinemelum Benita Nworji | From Reactive to Proactive: AI and Data LiteracyTransforming Maternal and Child Health in Nigeria. | Medical Laboratory Science, Lagos University Teaching Hospital | Nigeria |
| Dennis Kidake | BreatheLite: A Data-Driven AI System for Early Detection ofRespiratory Diseases through Exhaled Breath Analysis | Medicine, University of Nairobi | Kenya |
| Mustaf Ali | Leveraging Generative AI for Early CancerDetection in Somalia | AgrFood | Somalia |
| Queen Keji | A Data-Driven System for Monitoring and Preventing Respiratory Distress in Rural Communities | N/A | N/A |
AIDLC2025 Webinar Schedule
| Date | Topic | Time | Presenter Link |
|---|---|---|---|
| Saturday, Oct 11 | From Idea to Impact: Framing Your AI and Data Solution for Africa | 3:00 PM WAT | Link |
| Sunday, Oct 12 | Healthcare AI in Africa: Adoption, Trends, and Real-World Case Studies | 6:00 PM WAT | Link |
| Monday, Oct 13 | Beyond the Algorithm: A Clinician's Guide to Building and Leading a Digital Health Team | 7:00 PM WAT | Link |
| Tuesday, Oct 14 | Python/R Programming AMA | 7:00 PM WAT | Link |
| Wednesday, Oct 15 | Data Science, ML, DL, AI AMA | 9:00 PM WAT | Link |
| Thursday, Oct 16 | Prompt Engineering in Healthcare | 8:30 PM WAT | Link |
| Friday, Oct 17 | Power BI, Excel, SQL AMA | 5:30 PM WAT | Link |
| Saturday, Oct 18 | Health Tech and Digital Health Careers in AI and Data | 10:00 AM WAT | Link |
What is the AI & Data Literacy Challenge?
The AIDLC 2025 is an immersive learning experience designed by Medics in Tech to equip healthcare professionals and students with the foundational AI and Data skills they need to thrive in the future of digital health. Our mission is to turn dedicated clinicians into digital health literates, adopters, advocates, and innovators.
Gain Foundational Skills
Build a strong base in healthcare data science AI by completing fundamental coding and non-coding courses.
Apply Knowledge
Brainstorm and propose an AI and data-driven solution to a real-world healthcare challenge.
Build Network
Become part of an exclusive alumni network of healthcare innovators across Africa.
Elevate Profile
Earn a Certificate of Completion and gain a full year of access to our learning platforms to continue your growth.
The AIDLC 2025 Journey
Participants learn core technical skills on the world-class DataCamp platform. They then apply that knowledge with healthcare-specific context, custom videos, and quizzes on our dedicated AIDLC Challenge Hub.
More Than Just Courses
Participants learn core technical skills on the world-class DataCamp platform. They then apply that knowledge with a healthcare-specific context, custom videos, and quizzes on our dedicated AIDLC Challenge Hub.
Don’t Miss the Next Cohort!
Recognizing Excellence
We celebrate the hard work and innovation of our participants with a range of prizes and rewards.
| Top 3 = Gold Medal | Top 10 = Ribbon | All Finishers = Certificate |
|---|---|---|
| Cash Prizes and Mentorship | Free Access to Our Courses | Certificate + 1-year DataCamp + Alumni Network |
- Top 3 Student Champions: Receive cash prizes of up to ₦500,000 plus exclusive mentorship opportunities. (Note: Cash prizes are exclusively for students enrolled in African institutions.)
- Top 10 Finalists: Get free access to all future Medics in Tech courses for an entire year.
- All Finishers: Every participant who completes the challenge receives a Certificate of Completion, one year of FULL access to DataCamp to continue their learning, and entry into our exclusive alumni network.
1. Eligibility
- General Participation: The challenge is open to healthcare professionals, students, and non-medical professionals working within the healthcare domain across Africa and beyond.
- Cash Prize Eligibility: The cash prizes (1st, 2nd, and 3rd place) are exclusively for individuals currently enrolled as students (undergraduate, masters, or graduate) in an African institution. Practicing professionals and participants from outside Africa are not eligible for cash prizes but are eligible for all other rewards.
2. Challenge Timeline
- Challenge Start Date: Monday, September 22, 2025.
- Submission Deadline: All required materials must be submitted by Tuesday, October 21, 2025. (Note: This is the official corrected date mentioned during the onboarding meeting.)
- Winners Announced: Monday, October 27, 2025.
3. Core Requirements for Completion
To successfully complete the challenge and be considered a Finisher, each participant must:
- Complete a Minimum of Three (3) Courses: Finish at least three courses from the provided list on the DataCamp platform.
- Include a Coding Course: At least one of the three completed courses must be a designated coding course.
- Submit Proof of Completion: Submit all valid course completion certificates from DataCamp via the official AI DLC Challenge Hub.
- Submit a Learning Showcase: Submit one final "Learning Showcase" project in either a written or video format.
4. The Learning Showcase Project
This project is a key component of the evaluation. It is a proposal, not a fully built product or application.
- Format: Participants must choose one of two formats:
- A 300-400-word written summary.
- A 2-minute video presentation.
- Content: The showcase should be based on what you have learned and propose a data-driven solution to a healthcare challenge in Africa. A dedicated webinar, "From Idea to Impact," will be held in Week 3 to guide participants on how to frame their proposals.
5. Scoring and Judging
Submissions will be evaluated based on a 100-point system:
- Course Performance & Initiative (40 Points): Points are awarded for course completions. This includes baseline points for meeting the minimum requirements and additional points for exceeding them (e.g., completing more courses or more challenging ones).
- Community Engagement (20 Points): Points are awarded for active and positive participation across community platforms (Discord, WhatsApp). This includes sharing your learning progress on social media, helping other participants, and asking thoughtful questions.
- Learning Showcase (40 Points): Judged on the clarity of the proposal, the connection between the identified problem and the skills learned, and the overall thoughtfulness of the solution.
- Tie-Breaker: In the event of a tie, the participant with the higher score in the "Learning Showcase" category will be ranked higher.
6. Prizes and Rewards
- Top 3 Student Champions:
- 1st Place: ₦150,000 + Mentorship.
- 2nd Place: ₦100,000 + Mentorship.
- 3rd Place: ₦50,000 + Mentorship.
- Top 10 Finalists: Free access to all future Medics in Tech courses for one year.
- All Finishers: A Certificate of Completion, one year of full access to DataCamp, and entry into the exclusive Medics in Tech alumni network.
7. Code of Conduct
Participants are expected to maintain professional and respectful conduct throughout the challenge. Plagiarism, falsifying certificates, or harassing behavior in community channels will lead to immediate disqualification.
FAQs
I am a practicing doctor in Nigeria, but not a student. Can I win the cash prize?
You are highly encouraged to participate and are eligible for all prizes except the cash prizes. The cash awards are specifically reserved for students currently enrolled in an African institution. You can still be recognized as a Top 10 Finalist or an official Finisher.
I am a student living and studying outside of Africa. Can I join the challenge?
Yes, you are welcome to join, learn, and complete the challenge. However, you will not be eligible for the cash prizes. Upon completion, you will receive all the “All Finishers” rewards.
Some materials show different end dates. Which date is correct?
The correct and official deadline for all submissions is Tuesday, October 21, 2025. The final awards ceremony will be held on Monday, October 27, 2025.
Is there a deadline to accept my DataCamp invitation?
Yes, this is critical. You must accept the DataCamp invitation within one week of receiving it. If you fail to do so, the offer will be withdrawn.
How do I find my assigned courses on DataCamp?
After you log in, click on the “Learn” tab and then navigate to the section labeled “Assignments”. All your courses for the challenge will be listed there.
Can I change the courses I was assigned?
Yes. If you were assigned a course that doesn’t fit your goals, you can get it changed by attending one of the live technical support sessions for assistance.
I can't find my DataCamp invitation email. What should I do?
Please be sure to check all of your email folders, including your primary inbox, Spam, and Promotions tabs.
Can I take more than three courses? Will it help my score?
Yes, you are encouraged to take more than three courses. Exceeding the minimum requirements will earn you additional points in the “Course Performance & Initiative” category.
Do I have to pay for the courses or DataCamp access?
No. Access to DataCamp for the challenge is provided. All participants who successfully complete the challenge will receive one full year of DataCamp access as a reward.
I already have coding experience. Do I still need to take a coding course?
Yes. To meet the challenge requirements, you must complete and submit a certificate for at least one of the listed coding courses, regardless of your prior experience.
For the Learning Showcase, do I need to build a functional app or AI model?
No. The showcase is an exercise to demonstrate your thought process, not a development contest. You do not need to code or build anything; you only need to clearly explain your idea.
How will my Community Engagement points be tracked?
The Medics in Tech team will monitor engagement on the official Discord server and WhatsApp groups. Points are earned by actively participating, asking thoughtful questions, helping peers, and sharing your learning journey on social media.
Where do I submit my certificates and Learning Showcase project?
All submissions will be made through the official AI DLC Challenge Hub (the Medics in Tech website), which you will be granted access to on Saturday, September 27, 2025.
What if I need technical help during the challenge?
For general questions, please use the official Discord Server. For technical issues, attend the live support sessions held every Monday, Wednesday, and Saturday at 12:00 PM WAT via Google Meet.
Do I need a laptop?
While the learning platforms are accessible on mobile devices, a laptop or desktop computer is highly recommended for the best learning experience, especially for the coding courses.
What is Medics in Tech?
Medics in Tech is the organization running this challenge. Our goal is to help healthcare students and professionals build the foundational knowledge to succeed at the intersection of medicine and technology.