COURSE

FTEC3210

Data Analysis with Python

Society Hub / Financial Technology · 3 Credits

Students will learn how to develop Python code for cleaning and preparing data for analysis. This includes handling missing values, formatting, normalizing, and binning data. They will also learn to perform exploratory data analysis and apply analytical techniques to real-world datasets using libraries such as Pandas, Numpy, and Scipy. The course will also cover manipulating data using data frames, summarizing data, understanding data distribution, performing correlation analysis, and creating data pipelines. Additionally, students will learn how to build and evaluate regression models with the scikit-learn library for machine learning and how to use these for prediction and decision-making.