Data Science A-Z™: Real-Life Data Science Exercises Included [Free Online Course] - TechCracked

Learn Data Science step by step through real Analytics examples. Data Mining, Modeling, Tableau Visualization and more!

This course includes:

• 21 hours on-demand video
• 4 articles
• Full lifetime access
• Access on mobile and TV
• Certificate of completion

What you'll learn

• Successfully perform all steps in a complex Data Science project
• Create Basic Tableau Visualisations
• Perform Data Mining in Tableau
• Understand how to apply the Chi-Squared statistical test
• Apply Ordinary Least Squares method to Create Linear Regressions
• Assess R-Squared for all types of models
• Assess the 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
• Read statistical software output for created models
• Use Backward Elimination, Forward Selection, and Bidirectional Elimination methods to create statistical models
• Create a Logistic Regression
• Intuitively understand a Logistic Regression
• Operate with False Positives and False Negatives and know the difference
• Read a Confusion Matrix
• Create a Robust Geodemographic Segmentation Model
• Transform independent variables for modelling purposes
• Derive new independent variables for modelling purposes
• Check for multicollinearity using VIF and the correlation matrix
• Understand the intuition of multicollinearity
• Apply the Cumulative Accuracy Profile (CAP) to assess models
• Build the CAP curve in Excel
• Use Training and Test data to build robust models
• Derive insights from the CAP curve
• Understand the Odds Ratio
• Derive business insights from the coefficients of a logistic regression
• Understand what model deterioration actually looks like
• Apply three levels of model maintenance to prevent model deterioration
• Install and navigate SQL Server
• Install and navigate Microsoft Visual Studio Shell
• Clean data and look for anomalies
• Use SQL Server Integration Services (SSIS) to upload data into a database
• Create Conditional Splits in SSIS
• Deal with Text Qualifier errors in RAW data
• Create Scripts in SQL
• Apply SQL to Data Science projects
• Create stored procedures in SQL
• Present Data Science projects to stakeholders

Description

Extremely Hands-On... Incredibly Practical... Unbelievably Real!

This is not one of those fluffy classes where everything works out just the way it should and your training is smooth sailing. This course throws you into the deep end.

In this course you WILL experience firsthand all of the PAIN a Data Scientist goes through on a daily basis. Corrupt data, anomalies, irregularities - you name it!

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