Programming and Data Analysis with Python
About This Course
This Python programming course advances from elements of syntax, programme flow and control, functions and object-oriented concepts, to practical data processing and visualisation using libraries like Matplotlib and Seaborn. Learners will gain practical experience in building analytical solutions and applying machine learning workflows with Scikit-learn for classification, regression and clustering on finance-related datasets. They will develop expertise in data mining, modelling, and business data analysis to derive actionable insights and tackle real-world Financial Technology (FinTech) challenges, preparing them for roles such as software engineer, data engineer, or financial analyst in the digital finance sector.
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. Build and prototype analytical solutions using Python syntax.
2. Design and implement a programme with clear flow and control.
3. Process and visualise data using NumPy, Pandas, Matplotlib and Seaborn.
4. Perform data analysis tasks via Scikit-learn.
Entry Requirements
No pre-requisites are needed to enrol in the course; however, learners without qualifications or working experience in relevant programming/data analysis or the related fields may find the course contents challenging.
Note: Shortlisting will be conducted.