Machine Learning & Neural Learning

In this course, you'll be joining us right on campus at the University of Jordan. We’ll meet face-to-face, engaging directly in our university’s environment. It’s all about hands-on learning and real-time interaction, so you’ll get the full benefit of being right here with us.

Course Description

Step into the core of modern Artificial Intelligence. This course bridges the gap between theoretical mathematical foundations and high-impact practical applications. You will explore the vast landscape of Machine Learning, from classical regression and probabilistic models to the cutting-edge frontiers of Reinforcement Learning and Deep Neural Networks.

Designed for the problem-solvers of tomorrow, this course provides hands-on experience with real-world datasets in diverse fields like bioinformatics and speech recognition. You will learn not just how to build models, but how to optimize, evaluate, and deploy intelligent systems that can learn from data and make autonomous decisions.

Learning Objectives & Outcomes

By the end of this course, you will be able to:

• Model Architecture: Build and configure both supervised and unsupervised machine learning models.

• Neural Network Mastery: Design, train, and fine-tune Neural Networks, including CNNs for vision and RNNs for sequential data.

• Deep Optimization: Apply advanced optimization techniques to improve model accuracy and training efficiency.

• System Deployment: Evaluate model performance using rigorous metrics and prepare ML systems for real-world deployment.

Course Content & Topics

• Foundational ML: Linear and Logistic Regression, Classification, and Ensemble Methods.

• Probabilistic Modeling: Bayesian networks and reinforcement learning basics.

• Deep Learning: Architecture of CNNs (Computer Vision) and RNNs (Natural Language Processing).

• Optimization: Backpropagation, gradient descent variants, and regularization.

Assessment & Certification

• Theoretical Exam: A Written Exam covering the mathematical logic behind ML algorithms.

• Capstone Project: A comprehensive ML & Deep Learning Final Project where you will build and deploy a solution for a complex, real-world domain.