[80% Off]Data Science A-Z™: Real-Life Data Science Exercises Included Coupon

Data Science A-Z™: Real-Life Data Science Exercises Included Coupon

Get 80% discount on Data Science A-Z™: Real-Life Data Science Exercises Included course from Udemy.

Data Science A-Z™: Real-Life Data Science Exercises Included Coupon

Get an exclusive 80% Udemy discount for a limited time

Course Details

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

  1. Language: English (US)
  2. Offer: 80% discount
  3. Total Ratings: 4.6
  4. Organization: Udemy
  5. Course Lenght: 21 hours on-demand video

What You will learn from this course?

  1. Successfully perform all steps in a complex Data Science project
  2. Create Basic Tableau Visualisations
  3. Perform Data Mining in Tableau
  4. Understand how to apply the Chi-Squared statistical test
  5. Apply Ordinary Least Squares method to Create Linear Regressions
  6. Assess R-Squared for all types of models
  7. Assess the Adjusted R-Squared for all types of models
  8. Create a Simple Linear Regression (SLR)
  9. Create a Multiple Linear Regression (MLR)
  10. Create Dummy Variables
  11. Interpret coefficients of an MLR
  12. Read statistical software output for created models
  13. Use Backward Elimination, Forward Selection, and Bidirectional Elimination methods to create statistical models
  14. Create a Logistic Regression
  15. Intuitively understand a Logistic Regression
  16. Operate with False Positives and False Negatives and know the difference
  17. Read a Confusion Matrix
  18. Create a Robust Geodemographic Segmentation Model
  19. Transform independent variables for modelling purposes
  20. Derive new independent variables for modelling purposes
  21. Check for multicollinearity using VIF and the correlation matrix
  22. Understand the intuition of multicollinearity
  23. Apply the Cumulative Accuracy Profile (CAP) to assess models
  24. Build the CAP curve in Excel
  25. Use Training and Test data to build robust models
  26. Derive insights from the CAP curve
  27. Understand the Odds Ratio
  28. Derive business insights from the coefficients of a logistic regression
  29. Understand what model deterioration actually looks like
  30. Apply three levels of model maintenance to prevent model deterioration
  31. Install and navigate SQL Server
  32. Install and navigate Microsoft Visual Studio Shell
  33. Clean data and look for anomalies
  34. Use SQL Server Integration Services (SSIS) to upload data into a database
  35. Create Conditional Splits in SSIS
  36. Deal with Text Qualifier errors in RAW data
  37. Create Scripts in SQL
  38. Apply SQL to Data Science projects
  39. Create stored procedures in SQL
  40. Present Data Science projects to stakeholders

About Course Instructor

Kirill Eremenko is super-psyched that you are reading this!Professionally, He come from the Data Science consulting space with experience in finance, retail, transport and other industries. He was trained by the best analytics mentors at Deloitte Australia and since starting on Udemy He has passed on knowledge to thousands of aspiring data scientists.
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