[GigaCourse.Com] Udemy - Data Science with Python Complete Course

Creation Time	May 4, 2026, 8:16 a.m.
Last Access Time	May 4, 2026, 7:07 p.m.
File Size	8.1 GB
Keywords	Complete Data with Science - Udemy Python GigaCourse Course Com
Total Requests	6
Total Files	172
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5. Let's dig deeper/2. EDA on Mc'donalds Data Set.mp4 689.8 MB
4. Advance Python/2. Advance Programming in Python Part 2.mp4 599.9 MB
5. Let's dig deeper/3. Exploratory Data Analysis.mp4 438.8 MB
4. Advance Python/1. Advance Programming in Python.mp4 359.6 MB
4. Advance Python/5. Multivariate Plotting.mp4 336.5 MB
7. Module Seven/2. How to use Linear Regression.mp4 303.6 MB
3. Python for Data Science/15. Control Flow in Python.mp4 273.5 MB
4. Advance Python/3. Data Visualisations.mp4 263.6 MB
3. Python for Data Science/17. Types of Functions in Python.mp4 228.9 MB
3. Python for Data Science/9. Data Types & Related Stuffs in Python.mp4 203.3 MB
2. Basic Maths Required for Data Science/8. Probability.mp4 179.8 MB
7. Module Seven/3. Logistic Regression.mp4 156.3 MB
7. Module Seven/1. Linear Regression.mp4 150.1 MB
2. Basic Maths Required for Data Science/4. Measures of Spread.mp4 148.9 MB
4. Advance Python/4. Bivariate Plotting.mp4 148.8 MB
7. Module Seven/4. Logistic Regression on Titanic Data Set.mp4 141.0 MB
10. Project Telecom Churn Production/3. Project Part 3.mp4 129.4 MB
2. Basic Maths Required for Data Science/1. Let's Start with Statistics.mp4 128.9 MB
3. Python for Data Science/14. Operators in Python.mp4 120.7 MB
10. Project Telecom Churn Production/5. Project Let's Finalise it.mp4 119.4 MB
3. Python for Data Science/16. Functions in Python.mp4 117.2 MB
10. Project Telecom Churn Production/4. Project part 4.mp4 113.9 MB
10. Project Telecom Churn Production/1. Project Part 1 Let's get our system ready.mp4 112.6 MB
2. Basic Maths Required for Data Science/11. Normal Probability Distribution.mp4 104.2 MB
2. Basic Maths Required for Data Science/3. Types of Statistics.mp4 91.6 MB
7. Module Seven/24. Model Evaluation recall Curve.mp4 90.3 MB
3. Python for Data Science/18. Argument in a Function.mp4 88.3 MB
2. Basic Maths Required for Data Science/6. Plots Visualisation.mp4 87.5 MB
7. Module Seven/6. Algorithms used in Decision Treee.mp4 86.7 MB
7. Module Seven/10. Working on Titanic Data Set.mp4 84.7 MB
9. Featured Topics in Java/1. Big Data.mp4 84.6 MB
2. Basic Maths Required for Data Science/13. Hypothesis Testing for Decision Making.mp4 83.9 MB
6. Let's Explore in to Machine Learning/1. Introduction Machine Learning.mp4 81.4 MB
3. Python for Data Science/19. Recursive Functions in Python.mp4 78.2 MB
7. Module Seven/18. Linear Regression.mp4 76.2 MB
3. Python for Data Science/12. Output Formatting.mp4 75.6 MB
7. Module Seven/15. Random Forest Implementation on Titanic Data Set.mp4 73.6 MB
1. Introduction/1. Getting Started with Data Science.mp4 71.8 MB
2. Basic Maths Required for Data Science/2. Data Quality Issues.mp4 62.7 MB
8. Module Eight/3. All about R Language.mp4 58.2 MB
9. Featured Topics in Java/2. Intro to Hadoop.mp4 58.0 MB
2. Basic Maths Required for Data Science/5. Measures of Shapes.mp4 57.6 MB
10. Project Telecom Churn Production/2. Project part 2.mp4 57.6 MB
2. Basic Maths Required for Data Science/10. Random Variables.mp4 57.2 MB
9. Featured Topics in Java/3. Intro to Tableu.mp4 57.0 MB
3. Python for Data Science/10. Conversion of Data Types in Python.mp4 54.2 MB
9. Featured Topics in Java/4. Intro to Business Analytics.mp4 53.9 MB
3. Python for Data Science/1. Python for Data Science.mp4 52.2 MB
2. Basic Maths Required for Data Science/12. Central Limit Theorem.mp4 49.4 MB
3. Python for Data Science/20. Lambda or Anonymous Functions in Python.mp4 47.0 MB
2. Basic Maths Required for Data Science/7. Inferential Statistics.mp4 46.0 MB
3. Python for Data Science/8. Variables in Python.mp4 43.6 MB
6. Let's Explore in to Machine Learning/3. Reinforement Learning.mp4 43.1 MB
3. Python for Data Science/5. Comments in Python.mp4 42.4 MB
7. Module Seven/7. Gini Index.mp4 39.1 MB
3. Python for Data Science/6. Python Indentation.mp4 38.3 MB
7. Module Seven/20. Confusion Matrix.mp4 37.2 MB
7. Module Seven/8. Issues with Decision Tree.mp4 36.7 MB
7. Module Seven/23. AUC ROC curve.mp4 36.5 MB
7. Module Seven/22. FB score.mp4 36.2 MB
3. Python for Data Science/2. Python Installation - Google Collab.mp4 36.0 MB
3. Python for Data Science/4. Identifiers in Python.mp4 35.6 MB
3. Python for Data Science/13. User Input in Python.mp4 32.5 MB
7. Module Seven/16. Model Evaluation Technique.mp4 31.1 MB
6. Let's Explore in to Machine Learning/2. Unsupervised Learning.mp4 29.3 MB
5. Let's dig deeper/1. EDA.mp4 27.4 MB
7. Module Seven/5. Decision Tree.mp4 27.0 MB
7. Module Seven/17. Concept of R-Squared.mp4 26.8 MB
2. Basic Maths Required for Data Science/9. Conditional Probability.mp4 26.5 MB
7. Module Seven/11. Random Forest.mp4 26.1 MB
7. Module Seven/21. Recall Sensitivity True Rate of Positive.mp4 22.9 MB
8. Module Eight/2. Data Analysis using R part 2.mp4 22.7 MB
7. Module Seven/19. Classification.mp4 21.7 MB
3. Python for Data Science/3. Python Basics.mp4 20.1 MB
8. Module Eight/1. Data Analysis using R.mp4 19.8 MB
7. Module Seven/14. Application of Random Forest.mp4 18.0 MB
3. Python for Data Science/7. Python Statements.mp4 17.8 MB
3. Python for Data Science/11. Python IO functions.mp4 14.2 MB
7. Module Seven/9. Applications of Decision Tree.mp4 13.1 MB
7. Module Seven/13. Why Random Forest.mp4 9.5 MB
7. Module Seven/12. Types of Random Forest.mp4 3.8 MB
4. Advance Python/2. Advance Programming in Python Part 2.srt 121.5 KB
5. Let's dig deeper/2. EDA on Mc'donalds Data Set.srt 112.0 KB
5. Let's dig deeper/3. Exploratory Data Analysis.srt 78.0 KB
4. Advance Python/1. Advance Programming in Python.srt 72.9 KB
4. Advance Python/5. Multivariate Plotting.srt 61.5 KB
7. Module Seven/2. How to use Linear Regression.srt 56.8 KB
3. Python for Data Science/15. Control Flow in Python.srt 54.5 KB
4. Advance Python/3. Data Visualisations.srt 45.4 KB
7. Module Seven/3. Logistic Regression.srt 40.0 KB
7. Module Seven/1. Linear Regression.srt 37.2 KB
4. Advance Python/4. Bivariate Plotting.srt 37.0 KB
3. Python for Data Science/17. Types of Functions in Python.srt 33.4 KB
3. Python for Data Science/9. Data Types & Related Stuffs in Python.srt 32.7 KB
10. Project Telecom Churn Production/3. Project Part 3.srt 24.1 KB
7. Module Seven/6. Algorithms used in Decision Treee.srt 24.1 KB
3. Python for Data Science/14. Operators in Python.srt 22.7 KB
7. Module Seven/4. Logistic Regression on Titanic Data Set.srt 22.3 KB
10. Project Telecom Churn Production/4. Project part 4.srt 21.7 KB
10. Project Telecom Churn Production/5. Project Let's Finalise it.srt 21.6 KB
3. Python for Data Science/16. Functions in Python.srt 20.3 KB
6. Let's Explore in to Machine Learning/1. Introduction Machine Learning.srt 19.6 KB
10. Project Telecom Churn Production/1. Project Part 1 Let's get our system ready.srt 18.4 KB
7. Module Seven/24. Model Evaluation recall Curve.srt 15.2 KB
9. Featured Topics in Java/1. Big Data.srt 14.6 KB
1. Introduction/1. Getting Started with Data Science.srt 13.9 KB
7. Module Seven/10. Working on Titanic Data Set.srt 13.7 KB
2. Basic Maths Required for Data Science/8. Probability.srt 13.5 KB
2. Basic Maths Required for Data Science/1. Let's Start with Statistics.srt 13.2 KB
9. Featured Topics in Java/3. Intro to Tableu.srt 12.5 KB
7. Module Seven/15. Random Forest Implementation on Titanic Data Set.srt 12.3 KB
3. Python for Data Science/19. Recursive Functions in Python.srt 12.1 KB
2. Basic Maths Required for Data Science/4. Measures of Spread.srt 12.1 KB
3. Python for Data Science/18. Argument in a Function.srt 12.0 KB
9. Featured Topics in Java/4. Intro to Business Analytics.srt 12.0 KB
7. Module Seven/7. Gini Index.srt 11.8 KB
8. Module Eight/3. All about R Language.srt 11.8 KB
7. Module Seven/18. Linear Regression.srt 11.5 KB
2. Basic Maths Required for Data Science/11. Normal Probability Distribution.srt 11.3 KB
7. Module Seven/22. FB score.srt 11.1 KB
9. Featured Topics in Java/2. Intro to Hadoop.srt 10.5 KB
10. Project Telecom Churn Production/2. Project part 2.srt 10.4 KB
5. Let's dig deeper/1. EDA.srt 9.8 KB
2. Basic Maths Required for Data Science/6. Plots Visualisation.srt 9.6 KB
2. Basic Maths Required for Data Science/3. Types of Statistics.srt 9.4 KB
6. Let's Explore in to Machine Learning/3. Reinforement Learning.srt 9.0 KB
2. Basic Maths Required for Data Science/13. Hypothesis Testing for Decision Making.srt 8.9 KB
7. Module Seven/20. Confusion Matrix.srt 8.6 KB
7. Module Seven/8. Issues with Decision Tree.srt 8.5 KB
7. Module Seven/23. AUC ROC curve.srt 8.5 KB
7. Module Seven/16. Model Evaluation Technique.srt 7.9 KB
3. Python for Data Science/2. Python Installation - Google Collab.srt 7.8 KB
3. Python for Data Science/10. Conversion of Data Types in Python.srt 7.4 KB
7. Module Seven/5. Decision Tree.srt 7.0 KB
3. Python for Data Science/20. Lambda or Anonymous Functions in Python.srt 6.8 KB
6. Let's Explore in to Machine Learning/2. Unsupervised Learning.srt 6.7 KB
2. Basic Maths Required for Data Science/5. Measures of Shapes.srt 6.7 KB
3. Python for Data Science/8. Variables in Python.srt 6.4 KB
3. Python for Data Science/5. Comments in Python.srt 6.3 KB
3. Python for Data Science/12. Output Formatting.srt 6.3 KB
3. Python for Data Science/6. Python Indentation.srt 6.3 KB
2. Basic Maths Required for Data Science/10. Random Variables.srt 6.0 KB
2. Basic Maths Required for Data Science/2. Data Quality Issues.srt 6.0 KB
7. Module Seven/11. Random Forest.srt 5.9 KB
7. Module Seven/19. Classification.srt 5.8 KB
7. Module Seven/17. Concept of R-Squared.srt 5.7 KB
2. Basic Maths Required for Data Science/7. Inferential Statistics.srt 5.3 KB
7. Module Seven/21. Recall Sensitivity True Rate of Positive.srt 5.2 KB
3. Python for Data Science/1. Python for Data Science.srt 5.0 KB
8. Module Eight/2. Data Analysis using R part 2.srt 4.8 KB
2. Basic Maths Required for Data Science/12. Central Limit Theorem.srt 4.7 KB
8. Module Eight/1. Data Analysis using R.srt 4.3 KB
3. Python for Data Science/4. Identifiers in Python.srt 4.3 KB
3. Python for Data Science/7. Python Statements.srt 4.1 KB
3. Python for Data Science/3. Python Basics.srt 3.4 KB
7. Module Seven/14. Application of Random Forest.srt 3.3 KB
2. Basic Maths Required for Data Science/9. Conditional Probability.srt 3.0 KB
7. Module Seven/9. Applications of Decision Tree.srt 2.9 KB
3. Python for Data Science/13. User Input in Python.srt 2.5 KB
7. Module Seven/13. Why Random Forest.srt 2.5 KB
3. Python for Data Science/11. Python IO functions.srt 1.7 KB
7. Module Seven/12. Types of Random Forest.srt 1.4 KB
0. Websites you may like/[CourseClub.ME].url 122 bytes
10. Project Telecom Churn Production/[CourseClub.Me].url 122 bytes
3. Python for Data Science/[CourseClub.Me].url 122 bytes
6. Let's Explore in to Machine Learning/[CourseClub.Me].url 122 bytes
[CourseClub.Me].url 122 bytes
0. Websites you may like/[GigaCourse.Com].url 49 bytes
10. Project Telecom Churn Production/[GigaCourse.Com].url 49 bytes
3. Python for Data Science/[GigaCourse.Com].url 49 bytes
6. Let's Explore in to Machine Learning/[GigaCourse.Com].url 49 bytes
[GigaCourse.Com].url 49 bytes

[GigaCourse.Com] Udemy - Data Science with Python Complete Course

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