Machine Learning in Finance
About This Course
This course prepares learners to transform their financial analysis skills with machine learning and Artificial Intelligence (AI)-driven techniques. It explores supervised, unsupervised, and deep learning methods to drive data-driven decision-making, focusing on real-world data analysis and model evaluation for financial applications. Learners will develop the skills to implement modern statistical techniques using Python or R, and gain confidence in supporting AI-enabled financial strategies. This course is ideal for financial analysts, data scientists, and machine learning engineers seeking to leverage data-driven decision-making and predictive analytics in the Financial Technology (FinTech) industry.
As this micro-credential course is only offered in the FlexiMasters in Financial Technology programme, learners are required to enrol into the programme and complete all required courses within this programme.
What You'll Learn
1. Formulate the real-life problems as machine learning problems.
2. Identify the strengths and shortcomings of different machine learning techniques.
3. Evaluate learning methods statistically and recommend the optimal method for financial applications.
4. Implement modern machine learning techniques with software such as R or Python.
Entry Requirements
Prior knowledge in programming (regardless of language) is required for this course.
Note: Shortlisting will be conducted.