Artificial Intelligence for disease diagnosis and precision medicine
Artificial Intelligence (AI) and Machine Learning (ML) are transforming healthcare, enabling accurate diagnoses and data-driven treatment strategies. This 100% online course teaches healthcare professionals, students, and researchers how to develop ML classifiers for high-impact diseases in Africa and how to develop AI applications for clinical use in Python programming language.
Course Content
Module 1 – Introduction and Context
- Major healthcare challenges in Africa: diabetes, malaria, tuberculosis, and HIV
- Why AI is revolutionary in diagnosis and precision medicine
- Success stories of AI in healthcare and clinical decision support
- Basic concepts: clinical signs, biomarkers, risk factors
Module 2 – Fundamentals of Python and Data Science
- Python for biomedical data: variables, functions, and control structures
- Data manipulation with Pandas and NumPy
- Data visualization: Matplotlib, Seaborn, and simple dashboards
- ML fundamentals: Random Forest, XGBoost, Logistic Regression, evaluation metrics
Module 3 – Practical Projects with Real Data
Project 1 – Diabetes Diagnosis
- Dataset: clinical and biochemical features (prepared by the instructor)
- Feature selection, preprocessing, model training and evaluation
- Development of AI applications for clinical use in Python
Project 2 – Malaria Detection (clinical data)
- Dataset: clinical signs, lab results, and demographic data
- Training ML classifiers to predict malaria positivity
- Development of AI applications for clinical use in Python
Project 3 – HIV Risk Prediction
- Dataset: clinical data of patients with HIV risk factors
- Risk prediction using Random Forest and XGBoost
- Development of AI applications for clinical use in Python
Module 4 – Ready-to-Use Clinical Tools
- Building ML pipelines for disease diagnosis
- Integration of classifiers into simple apps (Python, basic Streamlit concepts)
- Practical tips for using models in clinical environments
Module 5 – Application and Communication
- Presenting ML results to clinicians and managers
- Visualization of patterns and predictions
- Data-driven intervention strategies
Module 6 – Preparation for the International Job Market (Premium)
- Creation of competitive CVs and cover letters for international AI healthcare positions
- Optimization of professional profiles (LinkedIn, GitHub)
- Preparation for technical and behavioral interviews
- Strategies for finding opportunities in the UK, Europe, Canada, and Australia
- Informative guidance on visa types and documentation
- Strategic support for submitting up to 5 job applications
- Recommendation letter signed by Prof. Dr. Alexandre Cobre
Note: Module 6 provides strategic and consultative support only. It does not guarantee employment or visa approval. The goal is to prepare and position students competitively in the international market.
Instructor
The course is led by Prof. Dr. Alexandre de Fátima Cobre, a Mozambican scientist affiliated with The University of Manchester (UK), specialist in AI applied to drug discovery, collaborator of the WHO, and founder of MozBioMed.AI.
- Ranked among the Top 3 Pharmaceutical Scientists in Brazil (2025)
- Author of over 50 international publications
- Recognized for pioneering AI-based discoveries in COVID-19
Basic Plan – £175 (15,000 MZN)
- Complete course + practical projects + international certificate
- Discounted price (one-time payment): £165 (14,000 MZN)
- Installments: 3x £60 (total £180 / 15,000 MZN)
Premium Plan – £580 (50,000 MZN)
- Everything in the Basic Plan + full Module 6
- Strategic support for the international job market: CV, GitHub, recommendation letter, guidance on job applications and visa
- Discounted price (one-time payment): £550 (47,000 MZN)
- Installments: 5x £120 (total £600 / 50,000 MZN)
Course Highlights
- 100% online with pre-recorded lectures
- Practical projects with real clinical data
- Development of AI applications for clinical use in Python
- Completion possible in 3–6 weeks for dedicated students
- International certificate of completion
- Preparation for the global AI healthcare market
