Course Content & Structure

How is the course delivered?

This course is delivered over 5 full-day online sessions (9:30am - 4pm) between September and March, plus a compulsory online workshop that all participants must attend. This course is delivered online via live streaming only. Participants will be given access to our award winning online learning management system, Canvas, where additional resources and acticities will be made available.

In order to gain the Diploma, participants must successfully complete an assessment during and at the end of the course.


 

Course Content & Schedule

Please see below the provisional indicative content for the Diploma in Data Analytics:

 

ORIENTATION WORKSHOP: Friday 24th September 2021

  • Compulsory half-day workshop for all participants prior to the lectures starting. This is to ensure all participants are set up and time is not spent in class setting up.

SESSION 1: Friday 22nd October 2021

SUBJECT: INTRO TO DATA AND DESCRIPTIVE STATISTICS
 

  • Introduction to Data Analytics and Rstudio/Rstudio Cloud/IBM Watson Studio.
  • Intro to Tidyverse, GGplot2 and Dplyr packages in Rstudio. Data Management and Transformation for NYCFlights13 database.
  • Presenting Data, Data Visualization, Tables & Charting, Pivot Tables in Excel/RStudio, Organising Numerical Data, Frequency Distributions in Excel/RStudio, Preparing Reports using Bivariate and Univariate Data, Pivot Charts, GGplot2 environment.
  • Correlation & Covariance, Estimating the Variance Covariance Matrix, Basic Probability modelling in Excel and Rstudio. 

SESSION 2: Friday 3rd December 2021

SUBJECT: INTRO TO MODEL ESTIMATION AND EVALUATION
 

  • Introduction to Modeling Relationships.
  • The Normal Gaussian Distribution and student t distribution, Hypothesis Testing, Simple Linear Regression, Ordinary Leat Squares in Excel, VBA and Rstudio. The Black Scholes Model in Excel VBA, Python and Rstudio.
  • The Normal Gaussian Distribution and student t distribution, Hypothesis Testing, Simple Linear Regression, Ordinary Leat Squares in Excel, VBA and Rstudio. The Black Scholes Model in Excel VBA, Python and Rstudio.
  • Introduction to Datasets for Titanic Survival, HMDA Boston Mortgage Origination, Insurance Claim Data, German Loan Defaults and Wine Quality.

SESSION 3: Friday 14th January 2022

SUBJECT: MODELS OF QUALITATIVE CHOICE AND MACHINE LEARNING
 

  • Tidyverse, Exploratory Data Analysis and Model Evaluation.
  • Ordinary Least Squares, Logistic Regression, Introduction to Machine Learning.
  • More advanced modeling of Titanic Survival, HMDA Boston Mortgage Origination, Loan Default, Wine Quality and Boston House Prices datasets.
  • More advanced modeling of Insurance Purchase using Health and Retirement Survey and Ames House Price Index.

SESSION 4: Friday 18th February 2022

SUBJECT: RISK MODELS AND PREDICTIVE ANALYSIS
 

  • Value at Risk: A Really Simple Example in Excel for a Two-asset and Three-Asset portfolio. The Importance of the Variance-Covariance Matrix in statistics. Implementations in Rstudio and Excel.
  • More Advanced Portfolio modelling. More on Black Scholes (1973) in Excel VBA and Python based on the Normal Gaussian Distribution. Random number generation and Monte Carlo modeling.
  • ctree, logistic regression, Random Forest and cForest for predictive Analytics.

SESSION 5: Friday 11th March 2022

SUBJECT: EXAM REVIEW
 

  • Review of Exam and/or end of term assessment

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