Course Modules:

 

MODULE TOPIC Hours
Introduction to Data Analytics - Introduction to SPSS, Jamovi and R Studio 12
- Introduction to Data Analytics
- Concept of Primary Data and Secondary Data
- Concept of Supervised and Unsupervised learning
Data Analytics using Python - Python Basics 20
- User Inputs and Conditionals
- Lists and Loops and Functions
- Data Collections and Files
- Statistical Analysis using Python
Statistical Theory and Application in Data Analytics - Frequency Distribution 12
- Measures of Central Tendency, Dispersion, Moments, Skewness, Kurtosis
- Simple Correlation and Simple Regression
- Theory of Probability, Discrete Probability Distribution
- Binomial, Poisson, Hypergeometric
- Continuous Probability Distribution
- Sampling and Distribution - Normal Distribution; t-distribution; F-Test; Chi Squared Distribution; Jacobian of Transformation
- Testing of Hypothesis, Analysis of Variance
- Basic of Numeric Analysis
- Non-Parametric Test
Multivariate Analysis - Multiple Regression 12
- Factor Analysis
- Logistic Regression
- Discriminant Analysis
Analytical Corporate Valuation: Financial and Cost Modeling using Spreadsheets - Company Business Model Analysis 12
- Company Profitability Analysis
- Product Profitability Analysis
- Financial Statements and Projections
- Discounted Cash Flow Analysis, Comparable Company Analysis, Precedent Transactions Analysis etc.
Time Series and Forecasting using Appropriate Software - Security Analysis and Stock Selection 12
- Portfolio Analysis
- Markowitz Efficient Frontier
- Forecasting of Stock Data
Introduction to Power BI - Introducing Power BI 20
- Using Power BI Desktop
- Building a Data Model
- Power BI Reports