Data Science A-Z: Hands-On Exercises & ChatGPT Prize [2024]

Data Science A-Z: Hands-On Exercises & ChatGPT Prize [2024], available at $129.99, has an average rating of 4.58, with 235 lectures, 1 quizzes, based on 34111 reviews, and has 218932 subscribers.

You will learn about 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 This course is ideal for individuals who are Anybody with an interest in Data Science or Anybody who wants to improve their data mining skills or Anybody who wants to improve their statistical modelling skills or Anybody who wants to improve their data preparation skills or Anybody who wants to improve their Data Science presentation skills It is particularly useful for Anybody with an interest in Data Science or Anybody who wants to improve their data mining skills or Anybody who wants to improve their statistical modelling skills or Anybody who wants to improve their data preparation skills or Anybody who wants to improve their Data Science presentation skills.

Enroll now: Data Science A-Z: Hands-On Exercises & ChatGPT Prize [2024]

Summary

Title: Data Science A-Z: Hands-On Exercises & ChatGPT Prize [2024]

Price: $129.99

Average Rating: 4.58

Number of Lectures: 235

Number of Quizzes: 1

Number of Published Lectures: 217

Number of Published Quizzes: 1

Number of Curriculum Items: 236

Number of Published Curriculum Objects: 218

Original Price: $199.99

Quality Status: approved

Status: Live

What You Will 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

Who Should Attend

• Anybody with an interest in Data Science
• Anybody who wants to improve their data mining skills
• Anybody who wants to improve their statistical modelling skills
• Anybody who wants to improve their data preparation skills
• Anybody who wants to improve their Data Science presentation skills

Target Audiences

• Anybody with an interest in Data Science
• Anybody who wants to improve their data mining skills
• Anybody who wants to improve their statistical modelling skills
• Anybody who wants to improve their data preparation skills
• Anybody who wants to improve their Data Science presentation skills