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[FreeTutorials Us] Udemy - The Data Science Course 2018 Complete Data Science Bootcamp

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[FreeTutorials Us] Udemy - The Data Science Course 2018 Complete Data Science Bootcamp

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Name:[FreeTutorials Us] Udemy - The Data Science Course 2018 Complete Data Science Bootcamp

Infohash: 0E8AA98F18E486EBE17D7476FEEAE24FCED1625C

Total Size: 9.20 GB

Seeds: 1

Leechers: 2

Stream: Watch Full Movie @ Movie4u

Last Updated: 2024-04-12 20:32:25 (Update Now)

Torrent added: 2018-08-28 02:02:03






Torrent Files List


10. Statistics - Descriptive Statistics (Size: 9.20 GB) (Files: 1069)

 10. Statistics - Descriptive Statistics

  10.1 2.5.The-Histogram-exercise.xlsx.xlsx

15.50 KB

  10.2 2.5.The-Histogram-exercise-solution.xlsx.xlsx

17.10 KB

  10. Histogram Exercise.html

0.08 KB

  11.1 2.6. Cross table and scatter plot.xlsx.xlsx

26.12 KB

  1.1 Course notes_descriptive_statistics.pdf.pdf

482.27 KB

  11. Cross Table and Scatter Plot.mp4

39.81 MB

  11. Cross Table and Scatter Plot.srt

6.69 KB

  11. Cross Table and Scatter Plot.vtt

5.87 KB

  12.1 2.6. Cross table and scatter plot_exercise_solution.xlsx.xlsx

40.44 KB

  12.2 2.6. Cross table and scatter plot_exercise.xlsx.xlsx

16.28 KB

  12. Cross Tables and Scatter Plots Exercise.html

0.08 KB

  13.1 2.7. Mean, median and mode_lesson.xlsx.xlsx

10.49 KB

  13. Mean, median and mode.mp4

37.07 MB

  13. Mean, median and mode.srt

5.73 KB

  13. Mean, median and mode.vtt

5.00 KB

  14.1 2.7. Mean, median and mode_exercise_solution.xlsx.xlsx

11.35 KB

  14.2 2.7. Mean, median and mode_exercise.xlsx.xlsx

10.87 KB

  14. Mean, Median and Mode Exercise.html

0.08 KB

  15.1 2.8. Skewness_lesson.xlsx.xlsx

34.63 KB

  15. Skewness.mp4

19.41 MB

  15. Skewness.srt

3.65 KB

  15. Skewness.vtt

3.20 KB

  16.1 2.8. Skewness_exercise.xlsx.xlsx

9.49 KB

  16.2 2.8. Skewness_exercise_solution.xlsx.xlsx

19.78 KB

  16. Skewness Exercise.html

0.08 KB

  17.1 2.9. Variance_lesson.xlsx.xlsx

10.08 KB

  17. Variance.mp4

50.95 MB

  17. Variance.srt

7.54 KB

  17. Variance.vtt

6.64 KB

  18.1 2.9. Variance_exercise.xlsx.xlsx

10.83 KB

  18.2 2.9. Variance_exercise_solution.xlsx.xlsx

11.05 KB

  18. Variance Exercise.html

0.51 KB

  19.1 2.10. Standard deviation and coefficient of variation_lesson.xlsx.xlsx

10.97 KB

  19. Standard Deviation and Coefficient of Variation.mp4

45.13 MB

  19. Standard Deviation and Coefficient of Variation.srt

6.60 KB

  19. Standard Deviation and Coefficient of Variation.vtt

5.75 KB

  1. Types of Data.mp4

72.52 MB

  1. Types of Data.srt

5.96 KB

  1. Types of Data.vtt

5.25 KB

  20.1 2.10. Standard deviation and coefficient of variation_exercise_solution.xlsx.xlsx

12.37 KB

  20.2 2.10. Standard deviation and coefficient of variation_exercise.xlsx.xlsx

11.30 KB

  20. Standard Deviation and Coefficient of Variation Exercise.html

0.08 KB

  21.1 2.11. Covariance_lesson.xlsx.xlsx

24.92 KB

  21. Covariance.mp4

27.48 MB

  21. Covariance.srt

4.92 KB

  21. Covariance.vtt

4.30 KB

  22.1 2.11. Covariance_exercise.xlsx.xlsx

20.23 KB

  22.2 2.11. Covariance_exercise_solution.xlsx.xlsx

29.51 KB

  22. Covariance Exercise.html

0.08 KB

  23. Correlation Coefficient.mp4

29.57 MB

  23. Correlation Coefficient.srt

4.72 KB

  23. Correlation Coefficient.vtt

4.15 KB

  24.1 2.12. Correlation_exercise.xlsx.xlsx

29.30 KB

  24.2 2.12. Correlation_exercise_solution.xlsx.xlsx

29.48 KB

  24. Correlation Coefficient Exercise.html

0.08 KB

  2. Types of Data.html

0.16 KB

  3. Levels of Measurement.mp4

54.39 MB

  3. Levels of Measurement.srt

4.55 KB

  3. Levels of Measurement.vtt

4.03 KB

  4. Levels of Measurement.html

0.16 KB

  5.1 2.3.Categorical-variables.Visualization-techniques-lesson.xlsx.xlsx

30.77 KB

  5. Categorical Variables - Visualization Techniques.mp4

38.46 MB

  5. Categorical Variables - Visualization Techniques.srt

6.43 KB

  5. Categorical Variables - Visualization Techniques.vtt

5.66 KB

  6.1 2.3. Categorical variables. Visualization techniques_exercise_solution.xlsx.xlsx

41.11 KB

  6.2 2.3. Categorical variables. Visualization techniques_exercise.xlsx.xlsx

15.24 KB

  6. Categorical Variables Exercise.html

0.08 KB

  7.1 2.4. Numerical variables. Frequency distribution table_lesson.xlsx.xlsx

11.32 KB

  7. Numerical Variables - Frequency Distribution Table.mp4

25.98 MB

  7. Numerical Variables - Frequency Distribution Table.srt

4.36 KB

  7. Numerical Variables - Frequency Distribution Table.vtt

3.83 KB

  8.1 2.4. Numerical variables. Frequency distribution table_exercise_solution.xlsx.xlsx

13.15 KB

  8.2 2.4. Numerical variables. Frequency distribution table_exercise.xlsx.xlsx

11.75 KB

  8. Numerical Variables Exercise.html

0.08 KB

  9.1 2.5. The Histogram_lesson.xlsx.xlsx

18.63 KB

  9. The Histogram.mp4

13.78 MB

  9. The Histogram.srt

3.01 KB

  9. The Histogram.vtt

2.67 KB

 11. Statistics - Practical Example Descriptive Statistics

  1.1 2.13. Practical example. Descriptive statistics_lesson.xlsx.xlsx

146.51 KB

  1. Practical Example Descriptive Statistics.mp4

159.46 MB

  1. Practical Example Descriptive Statistics.srt

20.61 KB

  1. Practical Example Descriptive Statistics.vtt

17.85 KB

  2.1 2.13. Practical-example.Descriptive-statistics-exercise-solution.xlsx.xlsx

146.22 KB

  2.2 2.13.Practical-example.Descriptive-statistics-exercise.xlsx.xlsx

120.24 KB

  2. Practical Example Descriptive Statistics Exercise.html

0.08 KB

 12. Statistics - Inferential Statistics Fundamentals

  10. Standard error.mp4

22.77 MB

  10. Standard error.srt

2.03 KB

  10. Standard error.vtt

1.76 KB

  1.1 Course notes_inferential statistics.pdf.pdf

382.32 KB

  11. Estimators and Estimates.mp4

47.83 MB

  11. Estimators and Estimates.srt

3.72 KB

  11. Estimators and Estimates.vtt

3.27 KB

  12. Estimators and Estimates.html

0.16 KB

  1. Introduction.mp4

15.51 MB

  1. Introduction.srt

1.63 KB

  1. Introduction.vtt

1.44 KB

  2.1 Course notes_inferential statistics.pdf.pdf

382.32 KB

  2.2 3.2. What is a distribution_lesson.xlsx.xlsx

19.46 KB

  2. What is a Distribution.mp4

61.59 MB

  2. What is a Distribution.srt

5.86 KB

  2. What is a Distribution.vtt

5.07 KB

  3. What is a Distribution.html

0.16 KB

  4. The Normal Distribution.mp4

49.85 MB

  4. The Normal Distribution.srt

4.90 KB

  4. The Normal Distribution.vtt

4.32 KB

  5. The Normal Distribution.html

0.16 KB

  6.1 3.4. Standard normal distribution_lesson.xlsx.xlsx

10.38 KB

  6. The Standard Normal Distribution.mp4

22.51 MB

  6. The Standard Normal Distribution.srt

3.94 KB

  6. The Standard Normal Distribution.vtt

3.45 KB

  7.1 3.4. Standard normal distribution_exercise.xlsx.xlsx

11.84 KB

  7.2 3.4. Standard normal distribution_exercise_solution.xlsx.xlsx

23.73 KB

  7. The Standard Normal Distribution Exercise.html

0.08 KB

  8. Central Limit Theorem.mp4

62.88 MB

  8. Central Limit Theorem.srt

5.64 KB

  8. Central Limit Theorem.vtt

4.95 KB

  9. Central Limit Theorem.html

0.16 KB

 13. Statistics - Inferential Statistics Confidence Intervals

  10. Margin of Error.html

0.16 KB

  11.1 3.13. Confidence intervals. Two means. Dependent samples_lesson.xlsx.xlsx

10.47 KB

  11. Confidence intervals. Two means. Dependent samples.mp4

70.47 MB

  11. Confidence intervals. Two means. Dependent samples.srt

8.04 KB

  11. Confidence intervals. Two means. Dependent samples.vtt

7.10 KB

  12.1 3.13. Confidence intervals. Two means. Dependent samples_exercise_solution.xlsx.xlsx

14.24 KB

  12.2 3.13. Confidence intervals. Two means. Dependent samples_exercise.xlsx.xlsx

13.74 KB

  12. Confidence intervals. Two means. Dependent samples Exercise.html

0.08 KB

  13.1 3.14. Confidence intervals. Two means. Independent samples (Part 1)_lesson.xlsx.xlsx

9.83 KB

  13. Confidence intervals. Two means. Independent samples (Part 1).mp4

28.75 MB

  13. Confidence intervals. Two means. Independent samples (Part 1).srt

6.07 KB

  13. Confidence intervals. Two means. Independent samples (Part 1).vtt

5.33 KB

  14.1 3.14. Confidence intervals. Two means. Independent samples (Part 1)_exercise_solution.xlsx.xlsx

10.12 KB

  14.2 3.14. Confidence intervals. Two means. Independent samples (Part 1)_exercise.xlsx.xlsx

9.83 KB

  14. Confidence intervals. Two means. Independent samples (Part 1) Exercise.html

0.08 KB

  15.1 3.15. Confidence intervals. Two means. Independent samples (Part 2)_lesson.xlsx.xlsx

9.52 KB

  15. Confidence intervals. Two means. Independent samples (Part 2).mp4

26.82 MB

  15. Confidence intervals. Two means. Independent samples (Part 2).srt

4.51 KB

  15. Confidence intervals. Two means. Independent samples (Part 2).vtt

3.98 KB

  16.1 3.15. Confidence intervals. Two means. Independent samples (Part 2)_exercise_solution.xlsx.xlsx

9.79 KB

  16.2 3.15. Confidence intervals. Two means. Independent samples (Part 2)_exercise.xlsx.xlsx

9.17 KB

  16. Confidence intervals. Two means. Independent samples (Part 2) Exercise.html

0.08 KB

  17. Confidence intervals. Two means. Independent samples (Part 3).mp4

19.93 MB

  17. Confidence intervals. Two means. Independent samples (Part 3).srt

1.96 KB

  17. Confidence intervals. Two means. Independent samples (Part 3).vtt

1.72 KB

  1. What are Confidence Intervals.mp4

49.98 MB

  1. What are Confidence Intervals.srt

3.26 KB

  1. What are Confidence Intervals.vtt

2.86 KB

  2. What are Confidence Intervals.html

0.16 KB

  3.1 3.9. Population variance known, z-score_lesson.xlsx.xlsx

11.21 KB

  3.2 3.9. The z-table.xlsx.xlsx

18.48 KB

  3. Confidence Intervals; Population Variance Known; z-score.mp4

78.20 MB

  3. Confidence Intervals; Population Variance Known; z-score.srt

9.80 KB

  3. Confidence Intervals; Population Variance Known; z-score.vtt

8.65 KB

  4.1 3.9. Population variance known, z-score_exercise.xlsx.xlsx

10.83 KB

  4.2 3.9. The z-table.xlsx.xlsx

18.48 KB

  4.3 3.9. Population variance known, z-score_exercise_solution.xlsx.xlsx

11.16 KB

  4. Confidence Intervals; Population Variance Known; z-score; Exercise.html

0.08 KB

  5. Student's T Distribution.mp4

35.43 MB

  5. Student's T Distribution.srt

4.14 KB

  5. Student's T Distribution.vtt

3.68 KB

  6. Student's T Distribution.html

0.16 KB

  7.1 3.11. Population variance unknown, t-score_lesson.xlsx.xlsx

10.78 KB

  7.2 3.11. The t-table.xlsx.xlsx

15.85 KB

  7. Confidence Intervals; Population Variance Unknown; t-score.mp4

32.21 MB

  7. Confidence Intervals; Population Variance Unknown; t-score.srt

5.71 KB

  7. Confidence Intervals; Population Variance Unknown; t-score.vtt

5.00 KB

  8.1 3.11. Population variance unknown, t-score_exercise.xlsx.xlsx

10.62 KB

  8.2 3.11. Population variance unknown, t-score_exercise_solution.xlsx.xlsx

11.10 KB

  8. Confidence Intervals; Population Variance Unknown; t-score; Exercise.html

0.08 KB

  9. Margin of Error.mp4

59.09 MB

  9. Margin of Error.srt

6.21 KB

  9. Margin of Error.vtt

5.45 KB

 14. Statistics - Practical Example Inferential Statistics

  1.1 3.17. Practical example. Confidence intervals_lesson.xlsx.xlsx

1.74 MB

  1. Practical Example Inferential Statistics.mp4

102.67 MB

  1. Practical Example Inferential Statistics.srt

13.65 KB

  1. Practical Example Inferential Statistics.vtt

11.90 KB

  2.1 3.17. Practical example. Confidence intervals_exercise.xlsx.xlsx

1.73 MB

  2.2 3.17.Practical-example.Confidence-intervals-exercise-solution.xlsx.xlsx

1.74 MB

  2. Practical Example Inferential Statistics Exercise.html

0.08 KB

 15. Statistics - Hypothesis Testing

  10.1 Online p-value calculator.pdf.pdf

1.22 MB

  10. p-value.mp4

55.87 MB

  10. p-value.srt

5.04 KB

  10. p-value.vtt

4.46 KB

  1.1 Course notes_hypothesis_testing.pdf.pdf

648.60 KB

  11. p-value.html

0.16 KB

  12.1 4.6.Test-for-the-mean.Population-variance-unknown-lesson.xlsx.xlsx

14.54 KB

  12. Test for the Mean. Population Variance Unknown.mp4

40.21 MB

  12. Test for the Mean. Population Variance Unknown.srt

5.90 KB

  12. Test for the Mean. Population Variance Unknown.vtt

5.18 KB

  13.1 4.6.Test-for-the-mean.Population-variance-unknown-exercise-solution.xlsx.xlsx

11.85 KB

  13.2 4.6.Test-for-the-mean.Population-variance-unknown-exercise.xlsx.xlsx

11.34 KB

  13. Test for the Mean. Population Variance Unknown Exercise.html

0.08 KB

  14.1 4.7. Test for the mean. Dependent samples_lesson.xlsx.xlsx

9.79 KB

  14. Test for the Mean. Dependent Samples.mp4

50.39 MB

  14. Test for the Mean. Dependent Samples.srt

6.70 KB

  14. Test for the Mean. Dependent Samples.vtt

5.86 KB

  15.1 4.7. Test for the mean. Dependent samples_exercise.xlsx.xlsx

12.80 KB

  15.2 4.7. Test for the mean. Dependent samples_exercise_solution.xlsx.xlsx

14.40 KB

  15. Test for the Mean. Dependent Samples Exercise.html

0.08 KB

  16.1 4.8. Test for the mean. Independent samples (Part 1)_lesson.xlsx.xlsx

9.63 KB

  16. Test for the mean. Independent samples (Part 1).mp4

29.96 MB

  16. Test for the mean. Independent samples (Part 1).srt

5.51 KB

  16. Test for the mean. Independent samples (Part 1).vtt

4.80 KB

  17.1 4.9. Test for the mean. Independent samples (Part 2)_lesson.xlsx.xlsx

9.31 KB

  17. Test for the mean. Independent samples (Part 2).mp4

36.37 MB

  17. Test for the mean. Independent samples (Part 2).srt

5.44 KB

  17. Test for the mean. Independent samples (Part 2).vtt

4.72 KB

  18.1 4.9. Test for the mean. Independent samples (Part 2)_exercise.xlsx.xlsx

9.45 KB

  18.2 4.9. Test for the mean. Independent samples (Part 2)_exercise_solution.xlsx.xlsx

10.24 KB

  18. Test for the mean. Independent samples (Part 2) Exercise.html

0.08 KB

  1. The Null vs Alternative Hypothesis.mp4

92.12 MB

  1. The Null vs Alternative Hypothesis.srt

7.36 KB

  1. The Null vs Alternative Hypothesis.vtt

6.43 KB

  2. Further Reading on Null and Alternative Hypothesis.html

2.18 KB

  3. The Null vs Alternative Hypothesis.html

0.16 KB

  4.1 Course notes_hypothesis_testing.pdf.pdf

658.60 KB

  4. Rejection Region and Significance Level.mp4

113.16 MB

  4. Rejection Region and Significance Level.srt

8.97 KB

  4. Rejection Region and Significance Level.vtt

7.83 KB

  5. Rejection Region and Significance Level.html

0.16 KB

  6. Type I Error and Type II Error.mp4

43.93 MB

  6. Type I Error and Type II Error.srt

5.67 KB

  6. Type I Error and Type II Error.vtt

4.90 KB

  7. Type I Error and Type II Error.html

0.16 KB

  8.1 4.4. Test for the mean. Population variance known_lesson.xlsx.xlsx

10.96 KB

  8. Test for the Mean. Population Variance Known.mp4

54.22 MB

  8. Test for the Mean. Population Variance Known.srt

8.15 KB

  8. Test for the Mean. Population Variance Known.vtt

7.12 KB

  9.1 4.4. Test for the mean. Population variance known_exercise.xlsx.xlsx

11.03 KB

  9.2 4.4. Test for the mean. Population variance known_exercise_solution.xlsx.xlsx

11.22 KB

  9. Test for the Mean. Population Variance Known Exercise.html

0.08 KB

 16. Statistics - Practical Example Hypothesis Testing

  1.1 4.10.Hypothesis-testing-section-practical-example.xlsx.xlsx

51.71 KB

  1. Practical Example Hypothesis Testing.mp4

69.48 MB

  1. Practical Example Hypothesis Testing.srt

8.49 KB

  1. Practical Example Hypothesis Testing.vtt

7.43 KB

  2.1 4.10. Hypothesis testing section_practical example_exercise.xlsx.xlsx

43.38 KB

  2.2 4.10.Hypothesis-testing-section-practical-example-exercise-solution.xlsx.xlsx

44.04 KB

  2. Practical Example Hypothesis Testing Exercise.html

0.08 KB

 17. Part 3 Introduction to Python

  10. Jupyter's Interface.html

0.16 KB

  1. Introduction to Programming.mp4

58.55 MB

  1. Introduction to Programming.srt

6.91 KB

  1. Introduction to Programming.vtt

6.08 KB

  2. Introduction to Programming.html

0.16 KB

  3. Why Python.mp4

75.08 MB

  3. Why Python.srt

6.97 KB

  3. Why Python.vtt

6.11 KB

  4. Why Python.html

0.16 KB

  5. Why Jupyter.mp4

44.31 MB

  5. Why Jupyter.srt

4.64 KB

  5. Why Jupyter.vtt

4.10 KB

  6. Why Jupyter.html

0.16 KB

  7. Installing Python and Jupyter.mp4

54.41 MB

  7. Installing Python and Jupyter.srt

7.13 KB

  7. Installing Python and Jupyter.vtt

6.23 KB

  8. Understanding Jupyter's Interface - the Notebook Dashboard.mp4

13.79 MB

  8. Understanding Jupyter's Interface - the Notebook Dashboard.srt

3.74 KB

  8. Understanding Jupyter's Interface - the Notebook Dashboard.vtt

3.25 KB

  9. Prerequisites for Coding in the Jupyter Notebooks.mp4

30.58 MB

  9. Prerequisites for Coding in the Jupyter Notebooks.srt

7.79 KB

  9. Prerequisites for Coding in the Jupyter Notebooks.vtt

6.80 KB

 18. Python - Variables and Data Types

  1.1 Variables - Resources.html

0.13 KB

  1. Variables.mp4

26.61 MB

  1. Variables.srt

6.18 KB

  1. Variables.vtt

5.35 KB

  2. Variables.html

0.16 KB

  3.1 Numbers and Boolean Values - Resources.html

0.13 KB

  3. Numbers and Boolean Values in Python.mp4

17.07 MB

  3. Numbers and Boolean Values in Python.srt

3.69 KB

  3. Numbers and Boolean Values in Python.vtt

3.17 KB

  4. Numbers and Boolean Values in Python.html

0.16 KB

  5.1 Strings - Resources.html

0.13 KB

  5. Python Strings.mp4

30.76 MB

  5. Python Strings.srt

7.45 KB

  5. Python Strings.vtt

6.46 KB

  6. Python Strings.html

0.16 KB

 19. Python - Basic Python Syntax

  10.1 Indexing Elements - Resources.html

0.13 KB

  10. Indexing Elements.mp4

5.94 MB

  10. Indexing Elements.srt

1.71 KB

  10. Indexing Elements.vtt

1.47 KB

  1.1 Arithmetic Operators - Resources.html

0.13 KB

  11. Indexing Elements.html

0.16 KB

  12.1 Structure Your Code with Indentation - Resources.html

0.13 KB

  12. Structuring with Indentation.mp4

6.81 MB

  12. Structuring with Indentation.srt

2.27 KB

  12. Structuring with Indentation.vtt

1.96 KB

  13. Structuring with Indentation.html

0.16 KB

  1. Using Arithmetic Operators in Python.mp4

18.92 MB

  1. Using Arithmetic Operators in Python.srt

4.12 KB

  1. Using Arithmetic Operators in Python.vtt

3.58 KB

  2. Using Arithmetic Operators in Python.html

0.16 KB

  3.1 The Double Equality Sign - Resources.html

0.13 KB

  3. The Double Equality Sign.mp4

5.99 MB

  3. The Double Equality Sign.srt

1.83 KB

  3. The Double Equality Sign.vtt

1.59 KB

  4. The Double Equality Sign.html

0.16 KB

  5.1 Reassign Values - Resources.html

0.13 KB

  5. How to Reassign Values.mp4

4.00 MB

  5. How to Reassign Values.srt

1.30 KB

  5. How to Reassign Values.vtt

1.13 KB

  6. How to Reassign Values.html

0.16 KB

  7.1 Add Comments - Resources.html

0.13 KB

  7. Add Comments.mp4

5.01 MB

  7. Add Comments.srt

1.71 KB

  7. Add Comments.vtt

1.49 KB

  8. Add Comments.html

0.16 KB

  9.1 Line Continuation - Resources.html

0.13 KB

  9. Understanding Line Continuation.mp4

2.35 MB

  9. Understanding Line Continuation.srt

1.14 KB

  9. Understanding Line Continuation.vtt

1.00 KB

 1. Part 1 Introduction

  1. A Practical Example What You Will Learn in This Course.mp4

49.03 MB

  1. A Practical Example What You Will Learn in This Course.srt

6.37 KB

  1. A Practical Example What You Will Learn in This Course.vtt

5.62 KB

  2. What Does the Course Cover.mp4

62.25 MB

  2. What Does the Course Cover.srt

5.08 KB

  2. What Does the Course Cover.vtt

4.49 KB

 20. Python - Other Python Operators

  1.1 Comparison Operators - Resources.html

0.13 KB

  1. Comparison Operators.mp4

10.18 MB

  1. Comparison Operators.srt

2.47 KB

  1. Comparison Operators.vtt

2.14 KB

  2. Comparison Operators.html

0.16 KB

  3.1 Logical and Identity Operators - Resources.html

0.13 KB

  3. Logical and Identity Operators.mp4

30.05 MB

  3. Logical and Identity Operators.srt

5.78 KB

  3. Logical and Identity Operators.vtt

4.99 KB

  4. Logical and Identity Operators.html

0.16 KB

 21. Python - Conditional Statements

  1.1 Introduction to the If Statement - Resources.html

0.13 KB

  1. The IF Statement.mp4

13.63 MB

  1. The IF Statement.srt

3.60 KB

  1. The IF Statement.vtt

3.12 KB

  2. The IF Statement.html

0.16 KB

  3.1 Add an Else Statement - Resources.html

0.13 KB

  3. The ELSE Statement.mp4

13.58 MB

  3. The ELSE Statement.srt

2.78 KB

  3. The ELSE Statement.vtt

2.45 KB

  4.1 Else if, for Brief - Elif - Resources.html

0.13 KB

  4. The ELIF Statement.mp4

33.15 MB

  4. The ELIF Statement.srt

6.65 KB

  4. The ELIF Statement.vtt

5.75 KB

  5.1 A Note on Boolean Values - Resources.html

0.13 KB

  5. A Note on Boolean Values.mp4

11.25 MB

  5. A Note on Boolean Values.srt

2.92 KB

  5. A Note on Boolean Values.vtt

2.55 KB

  6. A Note on Boolean Values.html

0.16 KB

 22. Python - Python Functions

  1.1 Defining a Function in Python - Resources.html

0.13 KB

  1. Defining a Function in Python.mp4

7.74 MB

  1. Defining a Function in Python.srt

2.53 KB

  1. Defining a Function in Python.vtt

2.20 KB

  2.1 Creating a Function with a Parameter - Resources.html

0.13 KB

  2. How to Create a Function with a Parameter.mp4

23.87 MB

  2. How to Create a Function with a Parameter.srt

4.35 KB

  2. How to Create a Function with a Parameter.vtt

3.78 KB

  3.1 Another Way to Define a Function - Resources.html

0.13 KB

  3. Defining a Function in Python - Part II.mp4

14.78 MB

  3. Defining a Function in Python - Part II.srt

3.13 KB

  3. Defining a Function in Python - Part II.vtt

2.70 KB

  4.1 Using a Function in Another Function - Resources.html

0.13 KB

  4. How to Use a Function within a Function.mp4

8.13 MB

  4. How to Use a Function within a Function.srt

2.04 KB

  4. How to Use a Function within a Function.vtt

1.78 KB

  5.1 Combining Conditional Statements and Functions - Resources.html

0.13 KB

  5. Conditional Statements and Functions.mp4

15.69 MB

  5. Conditional Statements and Functions.srt

3.52 KB

  5. Conditional Statements and Functions.vtt

3.05 KB

  6.1 Creating Functions Containing a Few Arguments - Resources.html

0.13 KB

  6. Functions Containing a Few Arguments.mp4

7.58 MB

  6. Functions Containing a Few Arguments.srt

1.31 KB

  6. Functions Containing a Few Arguments.vtt

1.13 KB

  7.1 Notable Built-In Functions in Python - Resources.html

0.13 KB

  7. Built-in Functions in Python.mp4

22.02 MB

  7. Built-in Functions in Python.srt

4.21 KB

  7. Built-in Functions in Python.vtt

3.68 KB

  8. Python Functions.html

0.16 KB

 23. Python - Sequences

  1.1 Lists - Resources.html

0.13 KB

  1. Lists.mp4

22.00 MB

  1. Lists.srt

4.99 KB

  1. Lists.vtt

4.30 KB

  2. Lists.html

0.16 KB

  3.1 Help Yourself with Methods - Resources.html

0.13 KB

  3. Using Methods.mp4

21.95 MB

  3. Using Methods.srt

3.96 KB

  3. Using Methods.vtt

3.47 KB

  4. Using Methods.html

0.16 KB

  5.1 List Slicing - Resources.html

0.13 KB

  5. List Slicing.mp4

30.77 MB

  5. List Slicing.srt

5.55 KB

  5. List Slicing.vtt

4.83 KB

  6.1 Tuples - Resources.html

0.13 KB

  6. Tuples.mp4

16.67 MB

  6. Tuples.srt

3.39 KB

  6. Tuples.vtt

2.96 KB

  7.1 Dictionaries - Resources.html

0.13 KB

  7. Dictionaries.mp4

25.04 MB

  7. Dictionaries.srt

4.21 KB

  7. Dictionaries.vtt

3.63 KB

  8. Dictionaries.html

0.16 KB

 24. Python - Iterations

  1.1 For Loops - Resources.html

0.13 KB

  1. For Loops.mp4

11.79 MB

  1. For Loops.srt

2.80 KB

  1. For Loops.vtt

2.44 KB

  2. For Loops.html

0.16 KB

  3.1 While Loops and Incrementing - Resources.html

0.13 KB

  3. While Loops and Incrementing.mp4

15.44 MB

  3. While Loops and Incrementing.srt

2.77 KB

  3. While Loops and Incrementing.vtt

2.42 KB

  4.1 Create Lists with the range() Function - Resources.html

0.13 KB

  4. Lists with the range() Function.mp4

11.42 MB

  4. Lists with the range() Function.srt

2.79 KB

  4. Lists with the range() Function.vtt

2.45 KB

  5. Lists with the range() Function.html

0.16 KB

  6.1 Use Conditional Statements and Loops Together - Resources.html

0.13 KB

  6. Conditional Statements and Loops.mp4

16.09 MB

  6. Conditional Statements and Loops.srt

3.59 KB

  6. Conditional Statements and Loops.vtt

3.15 KB

  7.1 All In - Conditional Statements, Functions, and Loops - Resources.html

0.13 KB

  7. Conditional Statements, Functions, and Loops.mp4

9.48 MB

  7. Conditional Statements, Functions, and Loops.srt

2.41 KB

  7. Conditional Statements, Functions, and Loops.vtt

2.09 KB

  8.1 Iterating over Dictionaries - Resources.html

0.13 KB

  8. How to Iterate over Dictionaries.mp4

16.98 MB

  8. How to Iterate over Dictionaries.srt

3.88 KB

  8. How to Iterate over Dictionaries.vtt

3.34 KB

 25. Python - Advanced Python Tools

  1. Object Oriented Programming.mp4

33.59 MB

  1. Object Oriented Programming.srt

6.10 KB

  1. Object Oriented Programming.vtt

5.34 KB

  2. Object Oriented Programming.html

0.16 KB

  3. Modules and Packages.mp4

8.50 MB

  3. Modules and Packages.srt

1.26 KB

  3. Modules and Packages.vtt

1.13 KB

  4. Modules and Packages.html

0.16 KB

  5. What is the Standard Library.mp4

18.04 MB

  5. What is the Standard Library.srt

3.57 KB

  5. What is the Standard Library.vtt

3.15 KB

  6. What is the Standard Library.html

0.16 KB

  7. Importing Modules in Python.mp4

19.93 MB

  7. Importing Modules in Python.srt

4.82 KB

  7. Importing Modules in Python.vtt

4.17 KB

  8. Importing Modules in Python.html

0.16 KB

 26. Part 4 Advanced Statistical Methods in Python

  1. Introduction to Regression Analysis.mp4

17.32 MB

  1. Introduction to Regression Analysis.srt

2.21 KB

  1. Introduction to Regression Analysis.vtt

1.95 KB

  2. Introduction to Regression Analysis.html

0.16 KB

 27. Advanced Statistical Methods - Linear regression

  10. How to Interpret the Regression Table.mp4

44.64 MB

  10. How to Interpret the Regression Table.srt

6.31 KB

  10. How to Interpret the Regression Table.vtt

5.50 KB

  11. Decomposition of Variability.mp4

49.66 MB

  11. Decomposition of Variability.srt

4.17 KB

  11. Decomposition of Variability.vtt

3.67 KB

  12. Decomposition of Variability.html

0.16 KB

  13. What is the OLS.mp4

28.31 MB

  13. What is the OLS.srt

3.82 KB

  13. What is the OLS.vtt

3.33 KB

  14. R-Squared.mp4

41.03 MB

  14. R-Squared.srt

6.58 KB

  14. R-Squared.vtt

5.79 KB

  15. R-Squared.html

0.16 KB

  1. The Linear Regression Model.mp4

57.37 MB

  1. The Linear Regression Model.srt

7.06 KB

  1. The Linear Regression Model.vtt

6.14 KB

  2. The Linear Regression Model.html

0.16 KB

  3. Correlation vs Regression.mp4

14.73 MB

  3. Correlation vs Regression.srt

2.10 KB

  3. Correlation vs Regression.vtt

1.82 KB

  4. Correlation vs Regression.html

0.16 KB

  5. Geometrical Representation of the Linear Regression Model.mp4

5.12 MB

  5. Geometrical Representation of the Linear Regression Model.srt

1.64 KB

  5. Geometrical Representation of the Linear Regression Model.vtt

1.45 KB

  6. Python Packages Installation.mp4

40.59 MB

  6. Python Packages Installation.srt

5.62 KB

  6. Python Packages Installation.vtt

4.89 KB

  7.1 Simple linear regression - Lecture.html

0.13 KB

  7.2 Simple linear regression - Exercise.html

0.13 KB

  7. First Regression in Python.mp4

44.57 MB

  7. First Regression in Python.srt

7.91 KB

  7. First Regression in Python.vtt

6.91 KB

  8.1 Simple Linear Regression Exercise.html

0.13 KB

  8. First Regression in Python Exercise.html

0.07 KB

  9. Using Seaborn for Graphs.mp4

12.24 MB

  9. Using Seaborn for Graphs.srt

1.48 KB

  9. Using Seaborn for Graphs.vtt

1.30 KB

 28. Advanced Statistical Methods - Multiple Linear Regression

  10. A2 No Endogeneity.mp4

35.67 MB

  10. A2 No Endogeneity.srt

5.24 KB

  10. A2 No Endogeneity.vtt

4.58 KB

  11. A2 No Endogeneity.html

0.16 KB

  12. A3 Normality and Homoscedasticity.mp4

42.70 MB

  12. A3 Normality and Homoscedasticity.srt

6.67 KB

  12. A3 Normality and Homoscedasticity.vtt

5.81 KB

  13. A4 No Autocorrelation.mp4

31.52 MB

  13. A4 No Autocorrelation.srt

4.91 KB

  13. A4 No Autocorrelation.vtt

4.27 KB

  14. A4 No autocorrelation.html

0.16 KB

  15. A5 No Multicollinearity.mp4

28.71 MB

  15. A5 No Multicollinearity.srt

4.62 KB

  15. A5 No Multicollinearity.vtt

4.04 KB

  16. A5 No Multicollinearity.html

0.16 KB

  17.1 Dummies - Lecture.html

0.13 KB

  17. Dealing with Categorical Data - Dummy Variables.mp4

55.66 MB

  17. Dealing with Categorical Data - Dummy Variables.srt

8.15 KB

  17. Dealing with Categorical Data - Dummy Variables.vtt

7.11 KB

  18.1 Dummy variables Exercise.html

0.13 KB

  18. Dealing with Categorical Data - Dummy Variables.html

0.07 KB

  19.1 Making predictions - Lecture.html

0.13 KB

  19. Making Predictions with the Linear Regression.mp4

24.70 MB

  19. Making Predictions with the Linear Regression.srt

4.45 KB

  19. Making Predictions with the Linear Regression.vtt

3.87 KB

  1. Multiple Linear Regression.mp4

21.53 MB

  1. Multiple Linear Regression.srt

3.35 KB

  1. Multiple Linear Regression.vtt

2.93 KB

  2.1 Multiple linear regression - Lecture.html

0.13 KB

  2. Adjusted R-Squared.mp4

54.83 MB

  2. Adjusted R-Squared.srt

7.53 KB

  2. Adjusted R-Squared.vtt

6.57 KB

  3. Adjusted R-Squared.html

0.16 KB

  4.1 Multiple Linear Regression Exercise.html

0.13 KB

  4. Multiple Linear Regression Exercise.html

0.07 KB

  5. Test for Significance of the Model (F-Test).mp4

16.42 MB

  5. Test for Significance of the Model (F-Test).srt

2.56 KB

  5. Test for Significance of the Model (F-Test).vtt

2.23 KB

  6. OLS Assumptions.mp4

21.85 MB

  6. OLS Assumptions.srt

3.04 KB

  6. OLS Assumptions.vtt

2.67 KB

  7. OLS Assumptions.html

0.16 KB

  8. A1 Linearity.mp4

12.61 MB

  8. A1 Linearity.srt

2.36 KB

  8. A1 Linearity.vtt

2.07 KB

  9. A1 Linearity.html

0.16 KB

 29. Advanced Statistical Methods - Logistic Regression

  10. Underfitting and Overfitting.mp4

22.29 MB

  10. Underfitting and Overfitting.srt

4.98 KB

  10. Underfitting and Overfitting.vtt

4.37 KB

  11.1 Test dataset.html

0.13 KB

  11. Testing the Model.mp4

32.27 MB

  11. Testing the Model.srt

6.55 KB

  11. Testing the Model.vtt

5.70 KB

  1. Introduction to Logistic Regression.mp4

27.07 MB

  1. Introduction to Logistic Regression.srt

1.62 KB

  1. Introduction to Logistic Regression.vtt

1.44 KB

  2.1 Simple logistic regression example.html

0.13 KB

  2. A Simple Example in Python.mp4

34.70 MB

  2. A Simple Example in Python.srt

5.80 KB

  2. A Simple Example in Python.vtt

5.05 KB

  3. Logistic vs Logit Function.mp4

86.49 MB

  3. Logistic vs Logit Function.srt

4.88 KB

  3. Logistic vs Logit Function.vtt

4.27 KB

  4.1 Building a logistic regression.html

0.13 KB

  4. Building a Logistic Regression.mp4

17.11 MB

  4. Building a Logistic Regression.srt

3.28 KB

  4. Building a Logistic Regression.vtt

2.89 KB

  5. An Invaluable Coding Tip.mp4

23.05 MB

  5. An Invaluable Coding Tip.srt

3.21 KB

  5. An Invaluable Coding Tip.vtt

2.78 KB

  6. Understanding Logistic Regression Tables.mp4

30.55 MB

  6. Understanding Logistic Regression Tables.srt

5.56 KB

  6. Understanding Logistic Regression Tables.vtt

4.84 KB

  7. What do the Odds Actually Mean.mp4

32.29 MB

  7. What do the Odds Actually Mean.srt

4.79 KB

  7. What do the Odds Actually Mean.vtt

4.18 KB

  8.1 Binary predictors.html

0.13 KB

  8. Binary Predictors in a Logistic Regression.mp4

38.43 MB

  8. Binary Predictors in a Logistic Regression.srt

5.42 KB

  8. Binary Predictors in a Logistic Regression.vtt

4.75 KB

  9.1 Accuracy.html

0.13 KB

  9. Calculating the Accuracy of the Model.mp4

32.85 MB

  9. Calculating the Accuracy of the Model.srt

4.13 KB

  9. Calculating the Accuracy of the Model.vtt

3.63 KB

 2. The Field of Data Science - The Various Data Science Disciplines

  10. A Breakdown of our Data Science Infographic.html

0.16 KB

  1. Data Science and Business Buzzwords Why are there so many.mp4

81.41 MB

  1. Data Science and Business Buzzwords Why are there so many.srt

6.63 KB

  1. Data Science and Business Buzzwords Why are there so many.vtt

5.84 KB

  2. Data Science and Business Buzzwords Why are there so many.html

0.16 KB

  3. What is the difference between Analysis and Analytics.mp4

53.56 MB

  3. What is the difference between Analysis and Analytics.srt

5.08 KB

  3. What is the difference between Analysis and Analytics.vtt

4.42 KB

  4. What is the difference between Analysis and Analytics.html

0.16 KB

  5.1 365_DataScience_Diagram.pdf.pdf

323.08 KB

  5. Business Analytics, Data Analytics, and Data Science An Introduction.mp4

64.51 MB

  5. Business Analytics, Data Analytics, and Data Science An Introduction.srt

10.63 KB

  5. Business Analytics, Data Analytics, and Data Science An Introduction.vtt

9.26 KB

  6. Business Analytics, Data Analytics, and Data Science An Introduction.html

0.16 KB

  7.1 365_DataScience_Diagram.pdf.pdf

323.08 KB

  7.2 365_DataScience.png.png

6.92 MB

  7. Continuing with BI, ML, and AI.mp4

108.98 MB

  7. Continuing with BI, ML, and AI.srt

11.88 KB

  7. Continuing with BI, ML, and AI.vtt

10.43 KB

  8. Continuing with BI, ML, and AI.html

0.16 KB

  9.1 365_DataScience.png.png

6.93 MB

  9. A Breakdown of our Data Science Infographic.mp4

67.74 MB

  9. A Breakdown of our Data Science Infographic.srt

5.11 KB

  9. A Breakdown of our Data Science Infographic.vtt

4.45 KB

 30. Advanced Statistical Methods - Cluster Analysis

  1. Introduction to Cluster Analysis.mp4

53.42 MB

  1. Introduction to Cluster Analysis.srt

4.80 KB

  1. Introduction to Cluster Analysis.vtt

4.21 KB

  2. Some Examples of Clusters.mp4

71.54 MB

  2. Some Examples of Clusters.srt

6.24 KB

  2. Some Examples of Clusters.vtt

5.43 KB

  3. Difference between Classification and Clustering.mp4

36.16 MB

  3. Difference between Classification and Clustering.srt

3.28 KB

  3. Difference between Classification and Clustering.vtt

2.89 KB

  4. Math Prerequisites.mp4

14.55 MB

  4. Math Prerequisites.srt

4.06 KB

  4. Math Prerequisites.vtt

3.53 KB

 31. Advanced Statistical Methods - K-Means Clustering

  10. How is Clustering Useful.mp4

74.45 MB

  10. How is Clustering Useful.srt

6.40 KB

  10. How is Clustering Useful.vtt

5.65 KB

  1. K-Means Clustering.mp4

27.28 MB

  1. K-Means Clustering.srt

6.67 KB

  1. K-Means Clustering.vtt

5.76 KB

  2.1 Country clusters.html

0.13 KB

  2. A Simple Example of Clustering.mp4

51.82 MB

  2. A Simple Example of Clustering.srt

9.59 KB

  2. A Simple Example of Clustering.vtt

8.28 KB

  3.1 Clustering categorical data.html

0.13 KB

  3. Clustering Categorical Data.mp4

21.24 MB

  3. Clustering Categorical Data.srt

3.24 KB

  3. Clustering Categorical Data.vtt

2.81 KB

  4.1 Selecting the number of clusters.html

0.13 KB

  4. How to Choose the Number of Clusters.mp4

44.14 MB

  4. How to Choose the Number of Clusters.srt

7.37 KB

  4. How to Choose the Number of Clusters.vtt

6.43 KB

  5. Pros and Cons of K-Means Clustering.mp4

37.71 MB

  5. Pros and Cons of K-Means Clustering.srt

4.62 KB

  5. Pros and Cons of K-Means Clustering.vtt

4.01 KB

  6. To Standardize or to not Standardize.mp4

30.11 MB

  6. To Standardize or to not Standardize.srt

5.89 KB

  6. To Standardize or to not Standardize.vtt

5.14 KB

  7. Relationship between Clustering and Regression.mp4

9.93 MB

  7. Relationship between Clustering and Regression.srt

2.18 KB

  7. Relationship between Clustering and Regression.vtt

1.92 KB

  8.1 Market segmentation example.html

0.13 KB

  8. Market Segmentation with Cluster Analysis (Part 1).mp4

43.01 MB

  8. Market Segmentation with Cluster Analysis (Part 1).srt

7.53 KB

  8. Market Segmentation with Cluster Analysis (Part 1).vtt

6.53 KB

  9.1 Market segmentation example (Part 2).html

0.13 KB

  9. Market Segmentation with Cluster Analysis (Part 2).mp4

56.11 MB

  9. Market Segmentation with Cluster Analysis (Part 2).srt

9.19 KB

  9. Market Segmentation with Cluster Analysis (Part 2).vtt

7.96 KB

 32. Advanced Statistical Methods - Other Types of Clustering

  1. Types of Clustering.mp4

44.58 MB

  1. Types of Clustering.srt

4.66 KB

  1. Types of Clustering.vtt

4.12 KB

  2. Dendrogram.mp4

29.06 MB

  2. Dendrogram.srt

7.36 KB

  2. Dendrogram.vtt

6.41 KB

  3.1 Heatmaps.html

0.13 KB

  3. Heatmaps.mp4

29.62 MB

  3. Heatmaps.srt

6.35 KB

  3. Heatmaps.vtt

5.47 KB

 33. Part 5 Mathematics

  10.1 Addition and Subtraction of Matrices Python Notebook.html

0.17 KB

  10. Addition and Subtraction of Matrices.mp4

32.62 MB

  10. Addition and Subtraction of Matrices.srt

4.05 KB

  10. Addition and Subtraction of Matrices.vtt

3.48 KB

  11. Addition and Subtraction of Matrices.html

0.16 KB

  12.1 Errors when Adding Matrices Python Notebook.html

0.21 KB

  12. Errors when Adding Matrices.mp4

11.18 MB

  12. Errors when Adding Matrices.srt

2.58 KB

  12. Errors when Adding Matrices.vtt

2.27 KB

  13.1 Transpose of a Matrix Python Notebook.html

0.16 KB

  13. Transpose of a Matrix.mp4

38.07 MB

  13. Transpose of a Matrix.srt

5.37 KB

  13. Transpose of a Matrix.vtt

4.69 KB

  14.1 Dot Product Python Notebook.html

0.15 KB

  14. Dot Product.mp4

24.00 MB

  14. Dot Product.srt

4.27 KB

  14. Dot Product.vtt

3.68 KB

  15.1 Dot Product of Matrices Python Notebook.html

0.17 KB

  15. Dot Product of Matrices.mp4

49.43 MB

  15. Dot Product of Matrices.srt

9.52 KB

  15. Dot Product of Matrices.vtt

8.22 KB

  16. Why is Linear Algebra Useful.mp4

144.34 MB

  16. Why is Linear Algebra Useful.srt

11.79 KB

  16. Why is Linear Algebra Useful.vtt

10.31 KB

  1. What is a matrix.mp4

33.59 MB

  1. What is a matrix.srt

4.35 KB

  1. What is a matrix.vtt

3.80 KB

  2. What is a Matrix.html

0.16 KB

  3. Scalars and Vectors.mp4

33.85 MB

  3. Scalars and Vectors.srt

3.78 KB

  3. Scalars and Vectors.vtt

3.30 KB

  4. Scalars and Vectors.html

0.16 KB

  5. Linear Algebra and Geometry.mp4

49.79 MB

  5. Linear Algebra and Geometry.srt

4.10 KB

  5. Linear Algebra and Geometry.vtt

3.54 KB

  6. Linear Algebra and Geometry.html

0.16 KB

  7.1 Arrays in Python Notebook.html

0.18 KB

  7. Arrays in Python - A Convenient Way To Represent Matrices.mp4

26.12 MB

  7. Arrays in Python - A Convenient Way To Represent Matrices.srt

5.94 KB

  7. Arrays in Python - A Convenient Way To Represent Matrices.vtt

5.14 KB

  8.1 Tensors Notebook.html

0.14 KB

  8. What is a Tensor.mp4

22.53 MB

  8. What is a Tensor.srt

3.61 KB

  8. What is a Tensor.vtt

3.17 KB

  9. What is a Tensor.html

0.16 KB

 34. Part 6 Deep Learning

  1. What to Expect from this Part.mp4

31.10 MB

  1. What to Expect from this Part.srt

4.63 KB

  1. What to Expect from this Part.vtt

4.05 KB

  2. What is Machine Learning.html

0.16 KB

 35. Deep Learning - Introduction to Neural Networks

  10. The Linear Model with Multiple Inputs.html

0.16 KB

  1.1 Course Notes - Section 2.pdf.pdf

927.67 KB

  11. The Linear model with Multiple Inputs and Multiple Outputs.mp4

38.31 MB

  11. The Linear model with Multiple Inputs and Multiple Outputs.srt

5.47 KB

  11. The Linear model with Multiple Inputs and Multiple Outputs.vtt

4.79 KB

  12. The Linear model with Multiple Inputs and Multiple Outputs.html

0.16 KB

  13. Graphical Representation of Simple Neural Networks.mp4

22.64 MB

  13. Graphical Representation of Simple Neural Networks.srt

2.69 KB

  13. Graphical Representation of Simple Neural Networks.vtt

2.34 KB

  14. Graphical Representation of Simple Neural Networks.html

0.16 KB

  15. What is the Objective Function.mp4

17.91 MB

  15. What is the Objective Function.srt

2.12 KB

  15. What is the Objective Function.vtt

1.87 KB

  16. What is the Objective Function.html

0.16 KB

  17. Common Objective Functions L2-norm Loss.mp4

23.28 MB

  17. Common Objective Functions L2-norm Loss.srt

2.77 KB

  17. Common Objective Functions L2-norm Loss.vtt

2.44 KB

  18. Common Objective Functions L2-norm Loss.html

0.16 KB

  19. Common Objective Functions Cross-Entropy Loss.mp4

37.24 MB

  19. Common Objective Functions Cross-Entropy Loss.srt

5.26 KB

  19. Common Objective Functions Cross-Entropy Loss.vtt

4.57 KB

  1. Introduction to Neural Networks.mp4

42.92 MB

  1. Introduction to Neural Networks.srt

5.90 KB

  1. Introduction to Neural Networks.vtt

5.18 KB

  20. Common Objective Functions Cross-Entropy Loss.html

0.16 KB

  21.1 GD-function-example.xlsx.xlsx

42.18 KB

  21. Optimization Algorithm 1-Parameter Gradient Descent.mp4

55.62 MB

  21. Optimization Algorithm 1-Parameter Gradient Descent.srt

8.47 KB

  21. Optimization Algorithm 1-Parameter Gradient Descent.vtt

7.43 KB

  22. Optimization Algorithm 1-Parameter Gradient Descent.html

0.16 KB

  23. Optimization Algorithm n-Parameter Gradient Descent.mp4

39.42 MB

  23. Optimization Algorithm n-Parameter Gradient Descent.srt

7.53 KB

  23. Optimization Algorithm n-Parameter Gradient Descent.vtt

6.62 KB

  24. Optimization Algorithm n-Parameter Gradient Descent.html

0.16 KB

  2. Introduction to Neural Networks.html

0.16 KB

  3.1 Course Notes - Section 2.pdf.pdf

927.67 KB

  3. Training the Model.mp4

28.71 MB

  3. Training the Model.srt

4.28 KB

  3. Training the Model.vtt

3.79 KB

  4. Training the Model.html

0.16 KB

  5. Types of Machine Learning.mp4

45.11 MB

  5. Types of Machine Learning.srt

5.24 KB

  5. Types of Machine Learning.vtt

4.62 KB

  6. Types of Machine Learning.html

0.16 KB

  7. The Linear Model (Linear Algebraic Version).mp4

28.44 MB

  7. The Linear Model (Linear Algebraic Version).srt

3.88 KB

  7. The Linear Model (Linear Algebraic Version).vtt

3.43 KB

  8. The Linear Model.html

0.16 KB

  9. The Linear Model with Multiple Inputs.mp4

25.11 MB

  9. The Linear Model with Multiple Inputs.srt

3.10 KB

  9. The Linear Model with Multiple Inputs.vtt

2.74 KB

 36. Deep Learning - How to Build a Neural Network from Scratch with NumPy

  1.1 Shortcuts-for-Jupyter.pdf.pdf

619.17 KB

  1.2 Bais NN Example Part 1.html

0.13 KB

  1. Basic NN Example (Part 1).mp4

20.60 MB

  1. Basic NN Example (Part 1).srt

4.47 KB

  1. Basic NN Example (Part 1).vtt

3.91 KB

  2.1 Basic NN Example (Part 2).html

0.13 KB

  2. Basic NN Example (Part 2).mp4

34.94 MB

  2. Basic NN Example (Part 2).srt

6.79 KB

  2. Basic NN Example (Part 2).vtt

5.88 KB

  3.1 Basic NN Example (Part 3).html

0.13 KB

  3. Basic NN Example (Part 3).mp4

24.40 MB

  3. Basic NN Example (Part 3).srt

4.46 KB

  3. Basic NN Example (Part 3).vtt

3.88 KB

  4.1 Basic NN Example (Part 4).html

0.14 KB

  4. Basic NN Example (Part 4).mp4

61.14 MB

  4. Basic NN Example (Part 4).srt

10.87 KB

  4. Basic NN Example (Part 4).vtt

9.46 KB

  5.10 Basic NN Example Exercise 6 Solution.html

0.15 KB

  5.1 Basic NN Example Exercise 5 Solution.html

0.15 KB

  5.2 Basic NN Example (All Exercises).html

0.14 KB

  5.3 Basic NN Example Exercise 4 Solution.html

0.15 KB

  5.4 Basic NN Example Exercise 1 Solution.html

0.15 KB

  5.5 Basic NN Example Exercise 2 Solution.html

0.15 KB

  5.6 Basic NN Example Exercise 3d Solution.html

0.15 KB

  5.7 Basic NN Example Exercise 3b Solution.html

0.15 KB

  5.8 Basic NN Example Exercise 3c Solution.html

0.15 KB

  5.9 Basic NN Example Exercise 3a Solution.html

0.15 KB

  5. Basic NN Example Exercises.html

1.37 KB

 37. Deep Learning - TensorFlow Introduction

  1.1 Shortcuts-for-Jupyter.pdf.pdf

619.17 KB

  1. How to Install TensorFlow.mp4

14.56 MB

  1. How to Install TensorFlow.srt

3.22 KB

  1. How to Install TensorFlow.vtt

2.84 KB

  2. A Note on Installation of Packages in Anaconda.html

0.61 KB

  3. TensorFlow Outline and Logic.mp4

47.69 MB

  3. TensorFlow Outline and Logic.srt

5.21 KB

  3. TensorFlow Outline and Logic.vtt

4.59 KB

  4.1 Shortcuts-for-Jupyter.pdf.pdf

619.17 KB

  4. Actual Introduction to TensorFlow.mp4

17.41 MB

  4. Actual Introduction to TensorFlow.srt

2.18 KB

  4. Actual Introduction to TensorFlow.vtt

1.92 KB

  5.1 Basic NN Example with TensorFlow (Part 1).html

0.15 KB

  5. Types of File Formats, supporting Tensors.mp4

20.34 MB

  5. Types of File Formats, supporting Tensors.srt

3.45 KB

  5. Types of File Formats, supporting Tensors.vtt

3.00 KB

  6.1 Basic NN Example with TensorFlow (Part 2).html

0.15 KB

  6. Basic NN Example with TF Inputs, Outputs, Targets, Weights, Biases.mp4

38.49 MB

  6. Basic NN Example with TF Inputs, Outputs, Targets, Weights, Biases.srt

7.36 KB

  6. Basic NN Example with TF Inputs, Outputs, Targets, Weights, Biases.vtt

6.47 KB

  7.1 Basic NN Example with TensorFlow (Part 3).html

0.15 KB

  7. Basic NN Example with TF Loss Function and Gradient Descent.mp4

32.51 MB

  7. Basic NN Example with TF Loss Function and Gradient Descent.srt

4.83 KB

  7. Basic NN Example with TF Loss Function and Gradient Descent.vtt

4.21 KB

  8.1 Basic NN Example with TensorFlow (Complete).html

0.15 KB

  8. Basic NN Example with TF Model Output.mp4

37.39 MB

  8. Basic NN Example with TF Model Output.srt

7.93 KB

  8. Basic NN Example with TF Model Output.vtt

6.87 KB

  9.1 Basic NN Example with TensorFlow Exercise 2.4 Solution.html

0.16 KB

  9.2 Basic NN Example with TensorFlow Exercise 2.1 Solution.html

0.16 KB

  9.3 Basic NN Example with TensorFlow (All Exercises).html

0.15 KB

  9.4 Basic NN Example with TensorFlow Exercise 3 Solution.html

0.16 KB

  9.5 Basic NN Example with TensorFlow Exercise 2.2 Solution.html

0.16 KB

  9.6 Basic NN Example with TensorFlow Exercise 4 Solution.html

0.16 KB

  9.7 Basic NN Example with TensorFlow Exercise 1 Solution.html

0.16 KB

  9.8 Basic NN Example with TensorFlow Exercise 2.3 Solution.html

0.16 KB

  9. Basic NN Example with TF Exercises.html

1.59 KB

 38. Deep Learning - Digging Deeper into NNs Introducing Deep Neural Networks

  1.1 Course Notes - Section 6.pdf.pdf

936.42 KB

  1. What is a Layer.mp4

12.50 MB

  1. What is a Layer.srt

2.39 KB

  1. What is a Layer.vtt

2.13 KB

  2.1 Course Notes - Section 6.pdf.pdf

936.42 KB

  2. What is a Deep Net.mp4

29.53 MB

  2. What is a Deep Net.srt

3.25 KB

  2. What is a Deep Net.vtt

2.84 KB

  3. Digging into a Deep Net.mp4

59.36 MB

  3. Digging into a Deep Net.srt

6.70 KB

  3. Digging into a Deep Net.vtt

5.84 KB

  4. Non-Linearities and their Purpose.mp4

27.68 MB

  4. Non-Linearities and their Purpose.srt

3.89 KB

  4. Non-Linearities and their Purpose.vtt

3.38 KB

  5. Activation Functions.mp4

25.10 MB

  5. Activation Functions.srt

5.26 KB

  5. Activation Functions.vtt

4.58 KB

  6. Activation Functions Softmax Activation.mp4

25.92 MB

  6. Activation Functions Softmax Activation.srt

4.46 KB

  6. Activation Functions Softmax Activation.vtt

3.89 KB

  7. Backpropagation.mp4

34.95 MB

  7. Backpropagation.srt

4.47 KB

  7. Backpropagation.vtt

3.91 KB

  8. Backpropagation picture.mp4

19.51 MB

  8. Backpropagation picture.srt

3.98 KB

  8. Backpropagation picture.vtt

3.44 KB

  9.1 Backpropagation-a-peek-into-the-Mathematics-of-Optimization.pdf.pdf

182.36 KB

  9. Backpropagation - A Peek into the Mathematics of Optimization.html

0.53 KB

 39. Deep Learning - Overfitting

  1. What is Overfitting.mp4

31.08 MB

  1. What is Overfitting.srt

5.58 KB

  1. What is Overfitting.vtt

4.93 KB

  2. Underfitting and Overfitting for Classification.mp4

25.07 MB

  2. Underfitting and Overfitting for Classification.srt

2.63 KB

  2. Underfitting and Overfitting for Classification.vtt

2.31 KB

  3. What is Validation.mp4

32.71 MB

  3. What is Validation.srt

4.90 KB

  3. What is Validation.vtt

4.27 KB

  4. Training, Validation, and Test Datasets.mp4

25.20 MB

  4. Training, Validation, and Test Datasets.srt

3.60 KB

  4. Training, Validation, and Test Datasets.vtt

3.11 KB

  5. N-Fold Cross Validation.mp4

20.70 MB

  5. N-Fold Cross Validation.srt

4.18 KB

  5. N-Fold Cross Validation.vtt

3.67 KB

  6. Early Stopping or When to Stop Training.mp4

24.17 MB

  6. Early Stopping or When to Stop Training.srt

6.86 KB

  6. Early Stopping or When to Stop Training.vtt

6.01 KB

 3. The Field of Data Science - Connecting the Data Science Disciplines

  1. Applying Traditional Data, Big Data, BI, Traditional Data Science and ML.mp4

126.87 MB

  1. Applying Traditional Data, Big Data, BI, Traditional Data Science and ML.srt

8.99 KB

  1. Applying Traditional Data, Big Data, BI, Traditional Data Science and ML.vtt

7.90 KB

  2. Applying Traditional Data, Big Data, BI, Traditional Data Science and ML.html

0.16 KB

 40. Deep Learning - Initialization

  1. What is Initialization.mp4

21.76 MB

  1. What is Initialization.srt

3.51 KB

  1. What is Initialization.vtt

3.09 KB

  2. Types of Simple Initializations.mp4

14.31 MB

  2. Types of Simple Initializations.srt

3.68 KB

  2. Types of Simple Initializations.vtt

3.23 KB

  3. State-of-the-Art Method - (Xavier) Glorot Initialization.mp4

17.14 MB

  3. State-of-the-Art Method - (Xavier) Glorot Initialization.srt

3.71 KB

  3. State-of-the-Art Method - (Xavier) Glorot Initialization.vtt

3.24 KB

 41. Deep Learning - Digging into Gradient Descent and Learning Rate Schedules

  1. Stochastic Gradient Descent.mp4

28.68 MB

  1. Stochastic Gradient Descent.srt

4.82 KB

  1. Stochastic Gradient Descent.vtt

4.18 KB

  2. Problems with Gradient Descent.mp4

11.02 MB

  2. Problems with Gradient Descent.srt

2.83 KB

  2. Problems with Gradient Descent.vtt

2.50 KB

  3. Momentum.mp4

16.44 MB

  3. Momentum.srt

3.45 KB

  3. Momentum.vtt

3.04 KB

  4. Learning Rate Schedules, or How to Choose the Optimal Learning Rate.mp4

29.09 MB

  4. Learning Rate Schedules, or How to Choose the Optimal Learning Rate.srt

5.94 KB

  4. Learning Rate Schedules, or How to Choose the Optimal Learning Rate.vtt

5.22 KB

  5. Learning Rate Schedules Visualized.mp4

9.11 MB

  5. Learning Rate Schedules Visualized.srt

2.17 KB

  5. Learning Rate Schedules Visualized.vtt

1.90 KB

  6. Adaptive Learning Rate Schedules ( AdaGrad and RMSprop ).mp4

26.35 MB

  6. Adaptive Learning Rate Schedules ( AdaGrad and RMSprop ).srt

5.21 KB

  6. Adaptive Learning Rate Schedules ( AdaGrad and RMSprop ).vtt

4.57 KB

  7. Adam (Adaptive Moment Estimation).mp4

22.36 MB

  7. Adam (Adaptive Moment Estimation).srt

3.33 KB

  7. Adam (Adaptive Moment Estimation).vtt

2.92 KB

 42. Deep Learning - Preprocessing

  1. Preprocessing Introduction.mp4

27.78 MB

  1. Preprocessing Introduction.srt

3.87 KB

  1. Preprocessing Introduction.vtt

3.39 KB

  2. Types of Basic Preprocessing.mp4

11.84 MB

  2. Types of Basic Preprocessing.srt

1.64 KB

  2. Types of Basic Preprocessing.vtt

1.46 KB

  3. Standardization.mp4

50.98 MB

  3. Standardization.srt

5.98 KB

  3. Standardization.vtt

5.29 KB

  4. Preprocessing Categorical Data.mp4

18.60 MB

  4. Preprocessing Categorical Data.srt

2.77 KB

  4. Preprocessing Categorical Data.vtt

2.42 KB

  5. Binary and One-Hot Encoding.mp4

28.95 MB

  5. Binary and One-Hot Encoding.srt

4.81 KB

  5. Binary and One-Hot Encoding.vtt

4.18 KB

 43. Deep Learning - Classifying on the MNIST Dataset

  10.1 TensorFlow MNIST All Exercises.html

0.14 KB

  10. MNIST Exercises.html

2.13 KB

  11.10 TensorFlow MNIST '5. Activation Functions (Part 2)' Solution.html

0.17 KB

  11.11 TensorFlow MNIST 'Around 98% Accuracy' Solution.html

0.15 KB

  11.1 TensorFlow MNIST 'Time' Solution.html

0.16 KB

  11.2 TensorFlow MNIST '1. Width' Solution.html

0.15 KB

  11.3 TensorFlow MNIST '3. Width and Depth' Solution.html

0.16 KB

  11.4 TensorFlow MNIST '2. Depth' Solution.html

0.15 KB

  11.5 TensorFlow MNIST '8. Learning Rate (Part 1)' Solution.html

0.16 KB

  11.6 TensorFlow MNIST '9. Learning Rate (Part 2)' Solution.html

0.16 KB

  11.7 TensorFlow MNIST '7. Batch size (Part 2)' Solution.html

0.16 KB

  11.8 TensorFlow MNIST '4. Activation Functions (Part 1)' Solution.html

0.17 KB

  11.9 TensorFlow MNIST '6. Batch size (Part 1)' Solution.html

0.16 KB

  11. MNIST Solutions.html

2.19 KB

  1. MNIST What is the MNIST Dataset.mp4

17.82 MB

  1. MNIST What is the MNIST Dataset.srt

3.50 KB

  1. MNIST What is the MNIST Dataset.vtt

3.07 KB

  2. MNIST How to Tackle the MNIST.mp4

22.59 MB

  2. MNIST How to Tackle the MNIST.srt

3.62 KB

  2. MNIST How to Tackle the MNIST.vtt

3.17 KB

  3.1 TensorFlow MNIST Part 1 with Comments.html

0.16 KB

  3. MNIST Relevant Packages.mp4

18.91 MB

  3. MNIST Relevant Packages.srt

2.12 KB

  3. MNIST Relevant Packages.vtt

1.89 KB

  4.1 TensorFlow MNIST Part 2 with Comments.html

0.16 KB

  4. MNIST Model Outline.mp4

56.38 MB

  4. MNIST Model Outline.srt

9.07 KB

  4. MNIST Model Outline.vtt

7.91 KB

  5.1 TensorFlow MNIST Part 3 with Comments.html

0.16 KB

  5. MNIST Loss and Optimization Algorithm.mp4

25.86 MB

  5. MNIST Loss and Optimization Algorithm.srt

3.54 KB

  5. MNIST Loss and Optimization Algorithm.vtt

3.09 KB

  6.1 TensorFlow MNIST Part 4 with Comments.html

0.16 KB

  6. Calculating the Accuracy of the Model.mp4

43.90 MB

  6. Calculating the Accuracy of the Model.srt

5.19 KB

  6. Calculating the Accuracy of the Model.vtt

4.51 KB

  7.1 TensorFlow MNIST Part 5 with Comments.html

0.16 KB

  7. MNIST Batching and Early Stopping.mp4

12.85 MB

  7. MNIST Batching and Early Stopping.srt

2.93 KB

  7. MNIST Batching and Early Stopping.vtt

2.56 KB

  8.1 TensorFlow MNIST Part 6 with Comments.html

0.16 KB

  8. MNIST Learning.mp4

46.69 MB

  8. MNIST Learning.srt

10.20 KB

  8. MNIST Learning.vtt

8.89 KB

  9.1 TensorFlow MNIST Complete Code with Comments.html

0.15 KB

  9. MNIST Results and Testing.mp4

62.77 MB

  9. MNIST Results and Testing.srt

8.17 KB

  9. MNIST Results and Testing.vtt

7.15 KB

 44. Deep Learning - Business Case Example

  10. Business Case Testing the Model.mp4

11.20 MB

  10. Business Case Testing the Model.srt

2.71 KB

  10. Business Case Testing the Model.vtt

2.36 KB

  11.1 TensorFlow Business Case Homework.html

0.13 KB

  1.1 Audiobooks_data.csv.csv

710.77 KB

  11. Business Case A Comment on the Homework.mp4

36.38 MB

  11. Business Case A Comment on the Homework.srt

5.30 KB

  11. Business Case A Comment on the Homework.vtt

4.65 KB

  12.1 TensorFlow Business Case Homework.html

0.13 KB

  12. Business Case Final Exercise.html

0.43 KB

  1. Business Case Getting acquainted with the dataset.mp4

87.66 MB

  1. Business Case Getting acquainted with the dataset.srt

10.79 KB

  1. Business Case Getting acquainted with the dataset.vtt

9.37 KB

  2. Business Case Outlining the Solution.mp4

12.22 MB

  2. Business Case Outlining the Solution.srt

2.52 KB

  2. Business Case Outlining the Solution.vtt

2.19 KB

  3. The Importance of Working with a Balanced Dataset.mp4

39.41 MB

  3. The Importance of Working with a Balanced Dataset.srt

4.48 KB

  3. The Importance of Working with a Balanced Dataset.vtt

3.91 KB

  4.1 Audiobooks Preprocessing.html

0.13 KB

  4. Business Case Preprocessing.mp4

103.41 MB

  4. Business Case Preprocessing.srt

13.46 KB

  4. Business Case Preprocessing.vtt

11.71 KB

  5.1 Preprocessing Exercise.html

0.13 KB

  5. Business Case Preprocessing Exercise.html

0.37 KB

  6.1 Creating a Data Provider (Class).html

0.13 KB

  6. Creating a Data Provider.mp4

76.34 MB

  6. Creating a Data Provider.srt

7.75 KB

  6. Creating a Data Provider.vtt

6.80 KB

  7.1 TensorFlow Business Case Model Outline.html

0.13 KB

  7. Business Case Model Outline.mp4

53.13 MB

  7. Business Case Model Outline.srt

6.94 KB

  7. Business Case Model Outline.vtt

6.07 KB

  8.1 TensorFlow Business Case Optimization.html

0.13 KB

  8. Business Case Optimization.mp4

41.52 MB

  8. Business Case Optimization.srt

6.60 KB

  8. Business Case Optimization.vtt

5.76 KB

  9.1 TensorFlow Business Case Interpretation.html

0.13 KB

  9. Business Case Interpretation.mp4

25.74 MB

  9. Business Case Interpretation.srt

2.94 KB

  9. Business Case Interpretation.vtt

2.60 KB

 45. Deep Learning - Conclusion

  1. Summary of What You Learned.mp4

39.76 MB

  1. Summary of What You Learned.srt

5.22 KB

  1. Summary of What You Learned.vtt

4.61 KB

  2. What's Further out there in terms of Machine Learning.mp4

20.13 MB

  2. What's Further out there in terms of Machine Learning.srt

2.55 KB

  2. What's Further out there in terms of Machine Learning.vtt

2.27 KB

  3. An overview of CNNs.mp4

58.79 MB

  3. An overview of CNNs.srt

6.44 KB

  3. An overview of CNNs.vtt

5.66 KB

  4. DeepMind and Deep Learning.html

1.05 KB

  5. An Overview of RNNs.mp4

25.27 MB

  5. An Overview of RNNs.srt

3.71 KB

  5. An Overview of RNNs.vtt

3.30 KB

  6. An Overview of non-NN Approaches.mp4

44.77 MB

  6. An Overview of non-NN Approaches.srt

5.12 KB

  6. An Overview of non-NN Approaches.vtt

4.56 KB

 4. The Field of Data Science - The Benefits of Each Discipline

  1. The Reason behind these Disciplines.mp4

81.19 MB

  1. The Reason behind these Disciplines.srt

6.50 KB

  1. The Reason behind these Disciplines.vtt

5.69 KB

  2. The Reason behind these Disciplines.html

0.16 KB

 5. The Field of Data Science - Popular Data Science Techniques

  10. Techniques for Working with Traditional Methods.mp4

123.51 MB

  10. Techniques for Working with Traditional Methods.srt

11.08 KB

  10. Techniques for Working with Traditional Methods.vtt

9.66 KB

  11. Techniques for Working with Traditional Methods.html

0.16 KB

  12. Real Life Examples of Traditional Methods.mp4

42.78 MB

  12. Real Life Examples of Traditional Methods.srt

3.59 KB

  12. Real Life Examples of Traditional Methods.vtt

3.14 KB

  13. Machine Learning (ML) Techniques.mp4

99.32 MB

  13. Machine Learning (ML) Techniques.srt

8.74 KB

  13. Machine Learning (ML) Techniques.vtt

7.67 KB

  14. Machine Learning (ML) Techniques.html

0.16 KB

  15. Types of Machine Learning.mp4

125.15 MB

  15. Types of Machine Learning.srt

10.52 KB

  15. Types of Machine Learning.vtt

9.23 KB

  16. Types of Machine Learning.html

0.16 KB

  17. Real Life Examples of Machine Learning (ML).mp4

36.81 MB

  17. Real Life Examples of Machine Learning (ML).srt

2.91 KB

  17. Real Life Examples of Machine Learning (ML).vtt

2.57 KB

  18. Real Life Examples of Machine Learning (ML).html

0.16 KB

  1. Techniques for Working with Traditional Data.mp4

138.30 MB

  1. Techniques for Working with Traditional Data.srt

10.63 KB

  1. Techniques for Working with Traditional Data.vtt

9.30 KB

  2. Techniques for Working with Traditional Data.html

0.16 KB

  3. Real Life Examples of Traditional Data.mp4

29.94 MB

  3. Real Life Examples of Traditional Data.srt

2.25 KB

  3. Real Life Examples of Traditional Data.vtt

1.97 KB

  4. Techniques for Working with Big Data.mp4

75.51 MB

  4. Techniques for Working with Big Data.srt

5.67 KB

  4. Techniques for Working with Big Data.vtt

4.96 KB

  5. Techniques for Working with Big Data.html

0.16 KB

  6. Real Life Examples of Big Data.mp4

22.03 MB

  6. Real Life Examples of Big Data.srt

1.88 KB

  6. Real Life Examples of Big Data.vtt

1.64 KB

  7. Business Intelligence (BI) Techniques.mp4

89.94 MB

  7. Business Intelligence (BI) Techniques.srt

8.63 KB

  7. Business Intelligence (BI) Techniques.vtt

7.57 KB

  8. Business Intelligence (BI) Techniques.html

0.16 KB

  9. Real Life Examples of Business Intelligence (BI).mp4

29.54 MB

  9. Real Life Examples of Business Intelligence (BI).srt

2.13 KB

  9. Real Life Examples of Business Intelligence (BI).vtt

1.89 KB

 6. The Field of Data Science - Popular Data Science Tools

  1. Necessary Programming Languages and Software Used in Data Science.mp4

103.52 MB

  1. Necessary Programming Languages and Software Used in Data Science.srt

7.30 KB

  1. Necessary Programming Languages and Software Used in Data Science.vtt

6.42 KB

  2. Necessary Programming Languages and Software Used in Data Science.html

0.16 KB

 7. The Field of Data Science - Careers in Data Science

  1. Finding the Job - What to Expect and What to Look for.mp4

54.38 MB

  1. Finding the Job - What to Expect and What to Look for.srt

4.50 KB

  1. Finding the Job - What to Expect and What to Look for.vtt

3.94 KB

  2. Finding the Job - What to Expect and What to Look for.html

0.16 KB

 8. The Field of Data Science - Debunking Common Misconceptions

  1. Debunking Common Misconceptions.mp4

72.85 MB

  1. Debunking Common Misconceptions.srt

5.30 KB

  1. Debunking Common Misconceptions.vtt

4.69 KB

  2. Debunking Common Misconceptions.html

0.16 KB

 9. Part 2 Statistics

  1.1 Glossary.xlsx.xlsx

19.97 KB

  1.2 Course notes_descriptive_statistics.pdf.pdf

482.27 KB

  1. Population and Sample.mp4

58.11 MB

  1. Population and Sample.srt

5.47 KB

  1. Population and Sample.vtt

4.81 KB

  2. Population and Sample.html

0.16 KB
 

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