BSc (Hons) Mathematics with Machine Learning (Placement Year)
Course Overview
Master the mathematical foundations of artificial intelligence and develop the practical skills to build and deploy advanced machine learning models. This course equips you with the theoretical knowledge and hands-on coding expertise to become a vital asset in the rapidly evolving AI landscape, preparing you for a wide range of industries.
Key Program Highlights
- Grasp the core mathematical concepts that power modern AI and machine learning algorithms
- Build and implement practical machine learning models and neural networks using Python
- Learn to apply large language models like ChatGPT and analyze real-time data from various sectors
- Prepare for high-demand careers in industries such as healthcare, finance, business, and government
- Lay a strong foundation for advanced postgraduate study in mathematics or artificial intelligence
Tuition fee
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Offer response
2 days after your application is submitted
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Course Overview
Master the mathematical foundations of artificial intelligence and develop the practical skills to build and deploy advanced machine learning models. This course equips you with the theoretical knowledge and hands-on coding expertise to become a vital asset in the rapidly evolving AI landscape, preparing you for a wide range of industries.
Key Program Highlights
- Grasp the core mathematical concepts that power modern AI and machine learning algorithms
- Build and implement practical machine learning models and neural networks using Python
- Learn to apply large language models like ChatGPT and analyze real-time data from various sectors
- Prepare for high-demand careers in industries such as healthcare, finance, business, and government
- Lay a strong foundation for advanced postgraduate study in mathematics or artificial intelligence
Requirements
The requirements may vary based on your selected study options.
Modules
- Calculus I
- Introduction to Computational Methods
- Linear Algebra
- Mathematical Foundations
- Mathematical Models
- Statistical Theory and Methods I
- Applications of Mathematics and Graduate Skills
- Calculus II
- Mathematical Methods for Machine Learning
- Algebraic Structures and Discrete Mathematics
- Introduction to Astrophysics and Cosmology
- Mathematics for Finance
- Mechanics and Dynamics
- Operational Research
- Real and Complex Analysis
- Statistical Theory and Methods II
- Advanced Machine Learning
- Statistical Learning
- Undergraduate Ambassador
- Financial Derivative Pricing
- Introduction to General Relativity and Cosmology
- Modern Astrophysics 1
- Nonlinear Dynamics
- Partial Differential Equations and their Applications
- Quantitative Supply Chain Management
- Statistics Methods in Health Research and Social Science
- Project
- Advanced Decision Modelling
- Placement Year
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Tuition fee
Apply by
Start date
Duration
Campus
Mode of study
Fees and deadlines depend on the selected options. Fees and currency conversion are approximate.
Offer response
2 days after your application is submitted
