Modelling Data

Modelling Data

Today companies have adopted big data analytics to uncover hidden patterns that can help them make more-informed business decisions. “Modelling Big Data” offers practical guidance on how to properly use and analyze Big Data. The vast proliferation of data and increasing technological advances continue to transform the way industries operate and compete. Financial companies, in particular, have adopted big data analytics to gain further insights on their environment and eventually make better investment decisions. This Online-seminar introduces common big data tools for practitioners and show them how to handle big datasets and apply big data methodologies in a range of problems from risk management to forecasting loan default with machine learning. All together, participants get empowered through practical tools that can be applied back at their desk to fit their particular needs.

Big Data Introduction

Making and Getting Big Data

  • What is Big Data
  • What is Data Science?
  • Downloading Data in R


Visualizing data with R


Big Data Management

Shrinking Big Data

  • Outliers Detection
  • Principal Component Analysis
  • Partial Correlations in Networks


Data as networks

Automatic Big Data Management

Big Data and Machine Learning

  • Big data and Machine Learning explained
  • Classification Trees
  • Logistic Regressions
  • Neural Networks

Forecasting credit data


Preditive Data Modelling
  • Model Selection
  • Mummy, I Shrank a Big VAR Model
  • Selecting Several Good Models
  • Text Mining

Forecasting your data

Seminar Details

Lecturer: Gregory Gadzinksi, PhD
Duration: 4 x 3h
Languages: English (also available in French)
Group Size: Online (max 20)

Learning Goals

Learn how to build intelligent tools and automate your complex tasks.

Target Groups
  • (Multi-) Family Offices
  • Wealth Managers
  • Private Banks
  • Regional Banks
  • Trusts
  • Finance Director
  • Financial Analyst
  • Corporate Treasurer
  • Managing Consultant
  • Performance Manager
  • Legal & tax advisor