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Financial Data Science

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Financial Data Science

Overview

Fintech (the combination of finance, data, and technology) is revolutionizing financial services. Big data analytics, blockchain, machine learning, AI, cloud computing, and cryptocurrencies are all changing how business is done. This ground-breaking initiative will teach students the skills they need to work in a competitive global market for data science talent particularly in the financial services sector.

This specialization covers the fundamentals of data science and analytics with a focus on the financial industry. It combines online lectures, case studies, and hands-on projects to give students practical experience working with data.

The first course in the specialization introduces basic concepts in data science, statistics, and Python programming. The second course covers more advanced topics such as machine learning and forecasting. The third course applies these concepts to real-world data from the financial industry. Finally, students will have an opportunity to put their skills to the test in a capstone project.

What You Will Learn:

Data Wrangling: Manipulate and analyze data using common Python libraries such as pandas and numpy

Statistical Analysis: Understand basic statistical concepts and apply them to real-world data

Predictive Modeling: Create and interpret regression models to make predictions from data

Communication and Presentation: Communicate effectively about data science results using both visualizations and written reports

Programming: Write programs in Python to wrangle, analyze, and visualize data

Curriculum:

  • Quantitative Methods for Finance
  • Capital Markets & Instruments
  • Derivative Securities
  • Financial Analysis
  • Financial Econometrics
  • Financial Theory
  • Banking & Finance in the Digital Age
  • Programming for Financial Data Science
  • Financial Data Science
  • Machine Learning for Finance
  • Ethics in Financial Services

This specialization is for anyone with an interest in data science or the financial industry. No prior experience with programming or statistics is required.