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Comprehensive course materials for the Data Analytics for Finance - Master Programme, covering data manipulation, statistical analysis, visualisation, automation, and real-world case studies using industry-standard tools.

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Data Analytics for Finance - Master Programme

This repository contains the course materials for the Data Analytics for Finance - Master Programme. The programme is designed to provide a structured approach to learning data analytics with a focus on practical finance skills and industry-standard tools.

Course Modules

1. Data Manipulation

  • Cleaning and transforming datasets
  • Working with Python libraries like pandas and NumPy
  • SQL queries for data extraction and transformation

2. Statistical Analysis

  • Key concepts: distributions, hypothesis testing, regression analysis
  • Practical implementation of statistical methods
  • Application to real-world datasets

3. Visualisation

  • Creating clear and effective data visualisations
  • Tools: matplotlib, seaborn, and Tableau
  • Emphasis on storytelling with data

4. Tools and Automation

  • Automating data workflows with Python scripting
  • Advanced Excel (including macros)
  • Efficient data handling with SQL

5. Applied Case Studies

  • Real-world examples from finance, marketing, and operations
  • Simulating common industry scenarios
  • End-to-end analysis projects to reinforce concepts

This course assumes a basic understanding of programming and is aimed at learners looking to build proficiency in data analytics through practical, hands-on learning.

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Comprehensive course materials for the Data Analytics for Finance - Master Programme, covering data manipulation, statistical analysis, visualisation, automation, and real-world case studies using industry-standard tools.

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