Learn how to train an AI model using simple steps and a visual tool, making it smarter with each iteration.

Learn Unsupervised Learning, specifically Clustering with K-Means, using Python. Ideal for beginners.

Understanding how AI makes predictions using patterns learned from data.

Learn how to evaluate machine learning models using metrics like Accuracy, Precision, and Recall with Python.

Learn how to evaluate the performance of your AI models using accuracy and other metrics.

An introduction to neural networks and deep learning, inspired by the human brain.

Learn how to build your first AI project without writing a single line of code using Teachable Machine.

An overview of real-world applications and impacts of Artificial Intelligence, connecting theoretical concepts to practical scenarios.

Explains the fundamental concepts of supervised and unsupervised learning in AI, using simple analogies.

Learn the fundamentals of programming by giving AI instructions using Python.

Learn to build your first predictive model with Python and Scikit-learn, from data gathering to evaluation.

An introduction to ethical considerations in AI, focusing on bias, fairness, transparency, and accountability.