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1.1 2.13. Practical example. Descriptive statistics_lesson.xlsx.xlsx |
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1.1 3.17. Practical example. Confidence intervals_lesson.xlsx.xlsx |
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1.1 365_DataScience.png.png |
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1.1 4.10.Hypothesis-testing-section-practical-example.xlsx.xlsx |
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1.1 Arithmetic Operators - Resources.html |
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1.1 Audiobook sales.xlsx.xlsx |
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1.1 Comparison Operators - Resources.html |
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1.1 Course notes_descriptive_statistics.pdf.pdf |
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1.1 Course notes_hypothesis_testing.pdf.pdf |
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1.1 Course notes_inferential statistics.pdf.pdf |
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1.1 data_preprocessing_homework.pdf.pdf |
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1.1 Defining a Function in Python - Resources.html |
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1.1 employees_db.pdf.pdf |
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1.1 For Loops - Resources.html |
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1.1 GDP Data.xls.xls |
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1.1 Introduction to the If Statement - Resources.html |
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1.1 MySQL_Workbench_Shortcuts.pdf.pdf |
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1.1 Python Variables - Resources.html |
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1.1 Statistics Glossary.xlsx.xlsx |
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1.1 The 5 files rar.html |
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1.2 Audiobook reviews.xlsx.xlsx |
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1.2 Course notes_descriptive_statistics.pdf.pdf |
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1.2 df_preprocessed.csv.csv |
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1.2 Python Introduction - Course Notes.pdf.pdf |
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1.3 Absenteeism_data.csv.csv |
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1. A 5-minute explanation of Programming.mp4 |
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1. Applying COUNT().mp4 |
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1. Data Science Job Positions What do they Involve and What to Look out for.mp4 |
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1. Defining Stored Routines.mp4 |
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1. Duplicating a Sheet.mp4 |
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1. EXERCISE - Age vs Probability.html |
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1. Getting Started with Data, Servers, Clients, Requests, and Responses.mp4 |
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1. Getting to know the IF Statement.mp4 |
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1. How is the Content in the Next Sections Organized.html |
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1. How to Define a Function in Python.mp4 |
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1. How to Use the 'absenteeism_module' in Python - Part I.mp4 |
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1. Installing MySQL Workbench and Server.mp4 |
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1. Introduction.mp4 |
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1. Introduction to the Exercise.mp4 |
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1. Loading the 'employees' Database.mp4 |
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1. Population vs sample.mp4 |
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1. Practical Example.mp4 |
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1. Practical Example Hypothesis Testing.mp4 |
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1. Practical Example Inferential Statistics.mp4 |
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1. Programming Languages & Software Employed in Data Science - All the Tools Needed.mp4 |
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1. Python's Comparison Operators.mp4 |
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1. Solving a Business Exercise with Python, SQL, and Tableau.mp4 |
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1. SQL Subqueries with IN Embedded Inside WHERE.mp4 |
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1. The Arithmetic Operators of Python.mp4 |
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1. The SQL CASE Statement.mp4 |
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1. Traditional Data Techniques.mp4 |
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1. Types of Data.mp4 |
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1. Using For Loops.mp4 |
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1. Using SELECT - FROM.mp4 |
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1. What are Confidence Intervals.mp4 |
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1. What are JOINs.mp4 |
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1. What Does the Course Cover.mp4 |
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1. When are Traditional data, Big Data, BI, Traditional Data Science and ML applied.mp4 |
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1. Why Are There So Many Business and Data Science Buzzwords.mp4 |
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1. Why do we Need each of these Disciplines.mp4 |
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1. Why use SQL.mp4 |
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1. Why Use Tableau Make Your Data Make an Impact.mp4 |
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10.1 2.4. Numerical variables. Frequency distribution table_exercise_solution.xlsx.xlsx |
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10.1 Creating a dashboard - Tableau Public Link.html |
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10.1 Indexing Elements - Resources.html |
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10.1 Online p-value calculator.pdf.pdf |
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10.1 Subqueries SELECT FROM Solution.sql.sql |
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10.2 2.4. Numerical variables. Frequency distribution table_exercise.xlsx.xlsx |
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10.2 Audiobook reviews.xlsx.xlsx |
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10.3 Audiobook sales.xlsx.xlsx |
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10. A Deeper Look at the 'Reasons for Absence' Column.mp4 |
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10. A Deeper Look at the 'Reasons for Absence' Column.srt |
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10. Applying AVG().mp4 |
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10. Applying AVG().srt |
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10. Central Limit Theorem.html |
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10. Comparing Databases and Spreadsheets.html |
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10. Create Stored Procedures with an Output Parameter.mp4 |
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10. Creating and Formatting a Dashboard.mp4 |
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10. Creating and Formatting a Dashboard.srt |
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10. How to Index Elements.mp4 |
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10. How to Index Elements.srt |
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10. Margin of Error.mp4 |
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10. Margin of Error.srt |
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10. Numerical Variables Exercise.html |
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10. p-value.mp4 |
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10. Sending Data from Jupyter to Workbench - Part II.mp4 |
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10. Sending Data from Jupyter to Workbench - Part II.srt |
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10. SQL Subqueries Nested in SELECT and FROM - Solution 2.html |
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10. The Functionality of LEFT JOIN - Part I.mp4 |
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10. The Functionality of LEFT JOIN - Part I.srt |
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10. The Functionality of LEFT JOIN - Part I.vtt |
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10. Traditional Methods Techniques.mp4 |
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10. Traditional Methods Techniques.vtt |
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10. Understanding Jupyter's Interface.html |
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10. Using OR.mp4 |
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10. What is Software Integration and How is it Applied.html |
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11.1 2.5. The Histogram_lesson.xlsx.xlsx |
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11.1 Adding a filter - Tableau Public Link.html |
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11.1 Integration.html |
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11.1 Python Introduction - Course Notes.pdf.pdf |
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11.2 Audiobook reviews.xlsx.xlsx |
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11.3 Audiobook sales.xlsx.xlsx |
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11. Adding Interactive Filters for Improved Analysis.mp4 |
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11. Adding Interactive Filters for Improved Analysis.srt |
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11. Applying AVG() - Exercise.html |
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11. Create Stored Procedures with an Output Parameter - Exercise.html |
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11. How to Index Elements.html |
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11. Important Database Terminology.mp4 |
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11. Margin of Error.html |
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11. p-value.html |
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11. Sending Data from Jupyter to Workbench - Part III.mp4 |
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11. Splitting a Variable into Multiple Dummy Variables.mp4 |
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11. Standard error.mp4 |
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11. The Functionality of LEFT JOIN - Part II.mp4 |
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11. The Functionality of LEFT JOIN - Part II.srt |
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11. The Histogram.mp4 |
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11. Traditional Methods Techniques.html |
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11. Using OR - Exercise.html |
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12.1 3.13. Confidence intervals. Two means. Dependent samples_lesson.xlsx.xlsx |
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12.1 4.6.Test-for-the-mean.Population-variance-unknown-lesson.xlsx.xlsx |
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12.1 Structure Your Code with Indentation - Resources.html |
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12. Applying AVG() - Solution.html |
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12. Confidence intervals. Two means. Dependent samples.mp4 |
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12. Confidence intervals. Two means. Dependent samples.srt |
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12. Confidence intervals. Two means. Dependent samples.vtt |
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12. EXERCISE - Splitting a Variable into Multiple Dummy Variables.html |
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12. How to Structure Your Code with Indentation.mp4 |
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12. Important Database Terminology.html |
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12. Interactive Filters - fix.mp4 |
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12. Standard error.html |
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12. Stored Procedures with an Output Parameter - Solution.html |
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12. Test for the Mean. Population Variance Unknown.mp4 |
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12. The Functionality of LEFT JOIN - Part II - Exercise.html |
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12. The Histogram.html |
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12. Using OR - Solution.html |
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13.1 3.13. Confidence intervals. Two means. Dependent samples_exercise_solution.xlsx.xlsx |
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13.1 4.6.Test-for-the-mean.Population-variance-unknown-exercise-solution.xlsx.xlsx |
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13.2 3.13. Confidence intervals. Two means. Dependent samples_exercise.xlsx.xlsx |
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13.2 4.6. Test-for-the-mean.Population-variance-unknown-exercise.xlsx.xlsx |
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13.2 Statistics - PDF with Excel Solutions that don't visualize properly.pdf.pdf |
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13.3 2.5. The Histogram_exercise_solution.xlsx.xlsx |
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13. Confidence intervals. Two means. Dependent samples Exercise.html |
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13. Histogram Exercise.html |
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13. How to Structure Your Code with Indentation.html |
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13. Rounding Numbers with ROUND().mp4 |
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13. SOLUTION - Splitting a Variable into Multiple Dummy Variables.html |
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13. SQL Variables.mp4 |
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13. Test for the Mean. Population Variance Unknown Exercise.html |
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13. The Concept of Relational Schemas Primary Key.mp4 |
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13. The Functionality of LEFT JOIN - Part II - Solution.html |
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14.1 2.6. Cross table and scatter plot.xlsx.xlsx |
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14.1 3.14. Confidence intervals. Two means. Independent samples (Part 1)_lesson.xlsx.xlsx |
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14.1 4.7. Test for the mean. Dependent samples_lesson.xlsx.xlsx |
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14. Confidence intervals. Two means. Independent samples (Part 1).mp4 |
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14. Confidence intervals. Two means. Independent samples (Part 1).srt |
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14. Cross Table and Scatter Plot.mp4 |
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14. Estimators and Estimates.html |
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14. How to Drop a Dummy Variable from the Data Set.html |
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14. Machine Learning (ML) Techniques.html |
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14. Operator Precedence and Logical Order - Exercise.html |
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14. Rounding Numbers with ROUND() - Exercise.html |
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14. SQL Variables - Exercise.html |
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14. Test for the Mean. Dependent Samples.mp4 |
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14. The Concept of Relational Schemas Primary Key.html |
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14. The Functionality of RIGHT JOIN.mp4 |
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15.1 3.14. Confidence intervals. Two means. Independent samples (Part 1)_exercise.xlsx.xlsx |
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15.1 4.7. Test for the mean. Dependent samples_exercise_solution.xlsx.xlsx |
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15.2 3.14. Confidence intervals. Two means. Independent samples (Part 1)_exercise_solution.xlsx.xlsx |
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15.2 4.7. Test for the mean. Dependent samples_exercise.xlsx.xlsx |
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15. A Statistical Perspective on Dummy Variables.mp4 |
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15. Confidence intervals. Two means. Independent samples (Part 1) Exercise.html |
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15. Cross Tables and Scatter Plots.html |
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15. Differences between the New and the Old Join Syntax.mp4 |
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15. Machine Learning (ML) Types of Machine Learning.mp4 |
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15. Operator Precedence and Logical Order - Solution.html |
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15. Rounding Numbers with ROUND() - Solution.html |
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15. SQL Variables - Solution.html |
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15. Test for the Mean. Dependent Samples Exercise.html |
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15. The Concept of Relational Schemas Foreign Key.mp4 |
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15. The Concept of Relational Schemas Foreign Key.srt |
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16.1 2.6. Cross table and scatter plot_exercise.xlsx.xlsx |
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16.1 3.15. Confidence intervals. Two means. Independent samples (Part 2)_lesson.xlsx.xlsx |
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16. Confidence intervals. Two means. Independent samples (Part 2).mp4 |
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16. Confidence intervals. Two means. Independent samples (Part 2).vtt |
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16. Cross Tables and Scatter Plots Exercise.html |
81B |
16. Differences between the New and the Old Join Syntax - Exercise.html |
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16. Machine Learning (ML) Types of Machine Learning.html |
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16. Test for the mean. Independent samples (Part 1).mp4 |
29.96MB |
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16. The Benefit of User-Defined Functions in MySQL.mp4 |
44.90MB |
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16. The Concept of Relational Schemas Foreign Key.html |
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16. Using IN - NOT IN.mp4 |
32.12MB |
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17.1 2.7. Mean, median and mode_lesson.xlsx.xlsx |
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17.1 3.15. Confidence intervals. Two means. Independent samples (Part 2)_exercise_solution.xlsx.xlsx |
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17.1 4.8.Test-for-the-mean.Independent-samples-Part-1-exercise.xlsx.xlsx |
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17.2 3.15. Confidence intervals. Two means. Independent samples (Part 2)_exercise.xlsx.xlsx |
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17.2 4.8.Test-for-the-mean.Independent-samples-Part-1-exercise-solution.xlsx.xlsx |
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17. Concatenation in Python.mp4 |
38.74MB |
17. Concatenation in Python.srt |
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17. Confidence intervals. Two means. Independent samples (Part 2) Exercise.html |
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17. Differences between the New and the Old Join Syntax - Solution.html |
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17. Machine Learning (ML) Real-life Examples.mp4 |
36.85MB |
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17. Mean, median and mode.mp4 |
37.10MB |
17. Mean, median and mode.srt |
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17. Test for the mean. Independent samples (Part 1). Exercise.html |
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17. The Benefit of User-Defined Functions in MySQL - Exercise.html |
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17. Using IN - NOT IN - Exercise 1.html |
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18.1 2.7. Mean, median and mode_exercise.xlsx.xlsx |
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18.1 4.9. Test for the mean. Independent samples (Part 2)_lesson.xlsx.xlsx |
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18.2 2.7. Mean, median and mode_exercise_solution.xlsx.xlsx |
11.35KB |
18. Confidence intervals. Two means. Independent samples (Part 3).mp4 |
19.91MB |
18. Confidence intervals. Two means. Independent samples (Part 3).srt |
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18. Confidence intervals. Two means. Independent samples (Part 3).vtt |
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18. EXERCISE - Concatenation in Python.html |
189B |
18. Machine Learning (ML) Real-life Examples.html |
149B |
18. Mean, Median and Mode Exercise.html |
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18. Test for the mean. Independent samples (Part 2).mp4 |
36.36MB |
18. Test for the mean. Independent samples (Part 2).srt |
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18. Test for the mean. Independent samples (Part 2).vtt |
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18. The Benefit of User-Defined Functions in MySQL - Solution.html |
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18. The Concept of Relational Schemas Unique Key.html |
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18. Using IN - NOT IN - Solution 1.html |
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25.18MB |
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19.1 2.8. Skewness_lesson.xlsx.xlsx |
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19. Skewness.mp4 |
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19. SOLUTION - Concatenation in Python.html |
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2. (FreeCoursesOnline.Me) Download Udacity, Masterclass, Lynda, PHLearn, Pluralsight Free.url |
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2.1 3.2. What is a distribution_lesson.xlsx.xlsx |
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134B |
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2. Dispelling common Misconceptions.html |
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2. For Loops.html |
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2. Getting Started with Data, Servers, Clients, Requests, and Responses.html |
149B |
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2. How to Import the Data Set in Python.mp4 |
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2. How to Use the 'absenteeism_module' in Python - Part II.mp4 |
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2. Installing Visual C.html |
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2. Let's Download Tableau Public.mp4 |
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2. Loading the 'employees' Database.html |
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2. Programming Languages & Software Employed in Data Science - All the Tools Needed.html |
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2. Python's Comparison Operators.html |
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2. Python Variables.html |
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2. SQL Subqueries with IN Embedded Inside WHERE - Exercise.html |
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2. Types of data.html |
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2. Using Arithmetic Operators in Python.html |
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2. What are Confidence Intervals.html |
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2. What are JOINs - Exercise 1.html |
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2. What is a Distribution.mp4 |
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149B |
2. Why do we Need each of these Disciplines.html |
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2. Why use SQL.html |
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20.1 4.9.Test-for-the-mean.Independent-samples-Part-2-exercise-2.xlsx.xlsx |
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20.2 4.9.Test-for-the-mean.Independent-samples-Part-2-exercise-2-solution.xlsx.xlsx |
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20. Concluding Stored Routines.html |
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20. How to Reorder Columns in a DataFrame in Python.mp4 |
14.04MB |
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20. Skewness.html |
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20. Test for the mean. Independent samples (Part 2).html |
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20. Using JOIN and WHERE Together - Solution.html |
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21.1 2.8. Skewness_exercise.xlsx.xlsx |
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21.2 2.8. Skewness_exercise_solution.xlsx.xlsx |
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21. EXERCISE - How to Reorder Columns in a DataFrame in Python.html |
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21. Skewness Exercise.html |
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21. The Functionality of CROSS JOIN.mp4 |
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21. Using LIKE - NOT LIKE.mp4 |
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22.1 2.9. Variance_lesson.xlsx.xlsx |
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22. SOLUTION - How to Reorder Columns in a DataFrame in Python.html |
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22. The Functionality of CROSS JOIN - Exercise 1.html |
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22. Variance.mp4 |
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23. Using Checkpoints to Ease Your Work in Jupyter.mp4 |
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23. Variance Exercise.html |
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24.1 2.10. Standard deviation and coefficient of variation_lesson.xlsx.xlsx |
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24. EXERCISE - Using Checkpoints to Ease Your Work in Jupyter.html |
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24. Standard Deviation and Coefficient of Variation.mp4 |
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24. The Functionality of CROSS JOIN - Exercise 2.html |
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24. Using Wildcard Characters.mp4 |
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25. SOLUTION - Using Checkpoints to Ease Your Work in Jupyter.html |
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25. Standard deviation.html |
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25. The Functionality of CROSS JOIN - Solution 2.html |
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25. Using Wildcard characters - Exercise.html |
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26.1 2.10. Standard deviation and coefficient of variation_exercise.xlsx.xlsx |
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26.2 2.10. Standard deviation and coefficient of variation_exercise_solution.xlsx.xlsx |
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26. Analyzing the Date Column.mp4 |
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26. Standard Deviation and Coefficient of Variation Exercise.html |
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26. Using Wildcard characters - Solution.html |
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27.1 2.11. Covariance_lesson.xlsx.xlsx |
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27. JOIN More than Two Tables.mp4 |
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27. Retrieving the Month Value From the Date Column.mp4 |
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27. Using BETWEEN - AND.mp4 |
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27.98MB |
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28. Covariance.html |
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28. JOIN More than Two Tables - Exercise.html |
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29.1 2.11. Covariance_exercise.xlsx.xlsx |
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29.1 Dropping Columns.html |
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29.2 2.11. Covariance_exercise_solution.xlsx.xlsx |
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29. Covariance Exercise.html |
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29. JOIN More than Two Tables - Solution.html |
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3. (NulledPremium.com) Download E-Learning, E-Books, Audio-Books, Comics, Articles and more... etc.url |
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3.1 3.9. Population variance known, z-score_lesson.xlsx.xlsx |
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3.1 365_DataScience_Diagram.pdf.pdf |
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3.1 Audiobook sales.xlsx.xlsx |
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134B |
3.1 Logical and Identity Operators - Resources.html |
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3.1 Tesla sales data.xlsx.xlsx |
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3.1 The Client-Server Model.pdf.pdf |
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3.1 The Double Equality Sign - Resources.html |
134B |
3.1 Understanding Numbers and Boolean Values - Resources.html |
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3.1 While Loops and Incrementing - Resources.html |
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3. Applying COUNT() - Solution.html |
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3. Confidence Intervals; Population Variance Known; z-score.mp4 |
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3. Create Stored Procedures with MySQL Syntax.mp4 |
34.24MB |
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3. Creating Custom Fields.mp4 |
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3. Creating the 'predicted_outputs' Database in MySQL.mp4 |
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3. EXERCISE - Reasons vs Probability.html |
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3. Getting Started with Data Connectivity, APIs, and Endpoints.mp4 |
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3. Intro to Business Analytics, Data Analytics, and Data Science.mp4 |
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3. THE SQL CASE Statement - Solution 1.html |
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31. Correlation Coefficient.html |
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32. Correlation Coefficient Exercise.html |
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4. Confidence Intervals; Population Variance Known; z-score Exercise.html |
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5. Applying SUM() - Exercise.html |
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7. Categorical Variables Exercise.html |
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7. How to Import Modules in Python.mp4 |
19.92MB |
7. How to Import Modules in Python.srt |
4.82KB |
7. How to Import Modules in Python.vtt |
4.17KB |
7. How to Install Python and Jupyter.mp4 |
51.01MB |
7. How to Install Python and Jupyter.srt |
8.84KB |
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7. Inserting a Filter.mp4 |
27.62MB |
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7. MIN() and MAX().mp4 |
10.27MB |
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7. Python Dictionaries.mp4 |
25.05MB |
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3.63KB |
7. Relational Database Fundamentals.mp4 |
107.69MB |
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6.68KB |
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5.94KB |
7. SQL Subqueries Nested in SELECT and FROM.mp4 |
71.65MB |
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7. Student's T Distribution.html |
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7. The Functionality of INNER JOIN - PART II - Solution.html |
443B |
7. THE SQL CASE Statement - Solution 3.html |
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7. The Standard Normal Distribution.html |
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7. Type I Error and Type II Error.html |
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7. Using AND.mp4 |
16.73MB |
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8.1 13. Types of Joins.xlsx.xlsx |
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8.1 2.4. Numerical variables. Frequency distribution table_lesson.xlsx.xlsx |
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8.1 3.11. The t-table.xlsx.xlsx |
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8.1 3.4.Standard-normal-distribution-exercise.xlsx.xlsx |
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8.1 4.4. Test for the mean. Population variance known_lesson.xlsx.xlsx |
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8.1 Audiobook sales.xlsx.xlsx |
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8.1 Iterating over Dictionaries - Resources.html |
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8.2 3.11. Population variance unknown, t-score_lesson.xlsx.xlsx |
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8.2 3.4.Standard-normal-distribution-exercise-solution.xlsx.xlsx |
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8.2 Second chart - Tableau Public Link.html |
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8.3 Audiobook reviews.xlsx.xlsx |
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8. An Overview of our Data Science Infographic.html |
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8. Business Intelligence (BI) Techniques.html |
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8. Communication through Text Files.html |
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8. Confidence Intervals; Population Variance Unknown; t-score.mp4 |
32.18MB |
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8. Creating a Procedure in MySQL Another Way.mp4 |
32.43MB |
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8. Executing and SQL SELECT Statement from Python.mp4 |
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8. EXERCISE - Dropping Variables We Don't Need.html |
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8. Extra Info on Using Joins.mp4 |
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8. How to Add Comments.html |
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8. How to Import Modules in Python.html |
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8. How to Iterate over Dictionaries.mp4 |
16.99MB |
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8. MIN() and MAX() - Exercise.html |
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8. Numerical Variables - Frequency Distribution Table.mp4 |
25.82MB |
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8. Python Dictionaries.html |
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8. Python - Functions.html |
149B |
8. Relational Database Fundamentals.html |
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8. Second Chart.mp4 |
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8. SQL Subqueries Embedded in SELECT and FROM - Exercise 1.html |
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8. Test for the Mean. Population Variance Known.mp4 |
54.26MB |
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8. The Standard Normal Distribution Exercise.html |
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8. Understanding Jupyter’s Interface – Dashboard.mp4 |
13.79MB |
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8. Using AND - Exercise.html |
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8. Working with Joins in Tableau.mp4 |
45.13MB |
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9.1 3.11. Population variance unknown, t-score_exercise.xlsx.xlsx |
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9.1 4.4. Test for the mean. Population variance known_exercise.xlsx.xlsx |
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9.1 Audiobook sales.xlsx.xlsx |
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9.1 Line Continuation - Resources.html |
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9. Central Limit Theorem.mp4 |
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9. Confidence Intervals; Population Variance Unknown; t-score Exercise.html |
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9. MIN() and MAX() - Solution.html |
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9. Numerical variables. Using a frequency distribution table.html |
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9. Sending Data from Jupyter to Workbench - Part I.mp4 |
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9. SQL Subqueries Embedded in SELECT and FROM - Exercise 2.html |
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9. Test for the Mean. Population Variance Known Exercise.html |
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How you can help Team-FTU.txt |
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