Artificial Intelligence

This course offers a comprehensive introduction to Artificial Intelligence (AI), emphasizing the characteristics, types, and functionalities of AI agents and their applications in solving real-world problems. Students will learn about machine learning techniques, including supervised learning, unsupervised learning reinforcement learning, while critically evaluating their effectiveness. To build practical expertise, the course includes hands-on training, guiding students in designing and implementing AI solutions tailored to challenges in the life sciences. Students will also learn how to measure the performance of AI systems using performance metrics. Furthermore, the course addresses ethical considerations and governance frameworks, preparing students to develop and deploy AI systems responsibly and sustainably.

• Explain the characteristics, types, and functionality of AI agents and their applicability in solving problems

• Implement and evaluate machine learning approaches including neural networks, deep learning, and reinforcement learning

• Build AI solutions to solve practical problems in life sciences

• Evaluate the performance of the AI solutions using evaluation metrics

• Recognize various ethics and governance to ensure responsible development and deployment of AI systems

• Performance (20%) Lab assignments.
• Assignment other (40%)
• Written test with closed questions (40%)

• Artificial Intelligence: A Modern Approach by Stuart Russell, Peter Norvig (3rd edition or newer)