Syllabus

Data Fundamentals and Preparation

Foundations of Data

  1. Basic Concepts of Data
  2. Structured, Semi-structured and Unstructured Data
  3. Data in Organizations
  4. Big Data

Data for Decision Making and Preparation

  1. Role of Data in Decision Making
  2. Data Types by Levels of Measurement
  3. Meaning and Rationale of Data Analysis
  4. Data Preparation: Cleaning, Munging, Normalization and Transformation

Exploratory and Confirmatory Data Analysis

Types of Data Analysis

  1. Descriptive Data Analysis
  2. Exploratory Data Analysis
  3. Confirmatory Data Analysis

Analysis Tools with R

  1. Univariate Data Analysis with R
  2. Bivariate Data Analysis with R
  3. Multivariate Data Analysis Tools

Predictive Analytics and Modeling Techniques

Methods I: Regression Techniques

  1. Multiple Regression
  2. Logistic Regression
  3. Mediation Analysis
  4. Moderation Analysis
  5. Implementation of Methods with R

Methods II: Multivariate Analysis

  1. Factor Analysis
  2. Cluster Analysis
  3. Implementation of Advanced Methods with R

Prescriptive Analytics and Optimization

Linear and Integer Optimization

  1. Linear Programming
  2. Integer Programming

Network Optimization and Simulation

  1. Network Optimization
  2. Simulation Modelling