Course overview
This course aims to provide students with advanced skills in programming for Artificial Intelligence (AI) and Machine Learning (ML). Building on foundational knowledge, this course introduces students to the practical application of key AI and ML libraries such as TensorFlow and PyTorch, and advanced concepts including transformer models. Through hands-on programming tasks and projects, students will develop a deeper understanding of how to implement, optimise, and evaluate AI and ML models, preparing them for complex problem-solving and innovative developments in the field of AI and ML.
Course learning outcomes
- Implement advanced machine learning models using TensorFlow and PyTorch, demonstrating proficiency in these libraries
- Develop and optimise neural network models, applying appropriate techniques for model training and evaluation
- Utilise transformer models for various applications, such as natural language processing, showcasing an understanding of their architecture and functionalities
- Evaluate the performance of machine learning models using appropriate metrics, and apply fine-tuning and transfer learning techniques to improve model outcomes
- Demonstrate the ability to integrate and apply advanced AI and ML programming concepts through a comprehensive capstone project, effectively solving a complex problem
Degree list
The following degrees include this course