Data Science

Learn Data Science through real Analytics examples. Data Mining, Modeling, Tableau Visualization and much-more.

Statistics, scientific computing, scientific methods, processes, algorithms, and systems are used in the interdisciplinary academic field of data science to extract or extrapolate knowledge and insights from noisy, structured, and unstructured data.

Course Structure

• Complex Data Science project
• Create Basic Tableau Visualisations
• Perform Data Mining in Tableau
• Apply Ordinary Least Squares method to Create Linear Regressions
• Assess R-Squared for all types of models
• Assess Adjusted R-Squared for all types of models
• Create a Simple Linear Regression (SLR)
• Create a Multiple Linear Regression (MLR)
• Create Dummy Variables
• Interpret coefficients of an MLR
• Create a Logistic Regression
• Intuitively understand a Logistic Regression
• Read a Confusion Matrix
• Understand the Odds Ratio
• Install and navigate SQL Server
• Clean data and look for anomalies
• Create Conditional Splits in SSIS
• Create Scripts in SQL
• Apply SQL to Data Science projects
• Create stored procedures in SQL