DataBeginner
A practical introduction to how computers learn from data, from classic machine learning models to neural networks. Learn to plan, evaluate and responsibly use models for real problems in Somalia and East Africa.
3 modules · 9 lessons · 1 h 54 min
Understand what machine learning is, the main types of learning, and why data quality decides success.
Learn how models are trained and tested, meet the core classic algorithms, and measure results in a way that reflects real costs.
Understand how neural networks learn, the main deep learning architectures, and how to deploy models responsibly.
Machine learning lets computers find patterns in data and use them to make predictions, from estimating harvests to detecting fraud in mobile money. Deep learning, built on neural networks, powers today's image recognition, speech tools and chatbots. This course explains both in clear, plain language, without heavy mathematics or programming.
You will move step by step from the basic ideas, to building and measuring models, to how deep learning works and how to use it responsibly. Every lesson uses examples from Somalia and East Africa, including agriculture, health, telecom and the Somali language.
Certificate of completion
Finish every lesson, quiz and assignment to earn your SNAIC certificate.