[FreeCourseSite.com] Udemy - Data Science and Machine Learning Bootcamp with R

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Last Access Time	March 13, 2025, 4:37 a.m.
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4. Mac OS Installation Set-Up/1. Mac OS Installation Procedure.mp4 71.5 MB
18. Capstone Data Project/2. Capstone Project Solutions Walkthrough.mp4 63.3 MB
19. Introduction to Machine Learning with R/2. Introduction to Machine Learning.mp4 59.7 MB
21. Machine Learning Project - Linear Regression/2. ML - Linear Regression Project - Solutions Part 1.mp4 59.5 MB
14. Data Manipulation with R/8. Guide to Using Tidyr.mp4 57.7 MB
15. Data Visualization with R/2. Histograms.mp4 57.0 MB
23. Machine Learning Project - Logistic Regression/2. Logistic Regression Project Solutions - Part 1.mp4 56.3 MB
20. Machine Learning with R - Linear Regression/2. Linear Regression with R - Part 1.mp4 55.6 MB
33. Machine Learning with R - Neural Nets/2. Neural Nets with R.mp4 54.8 MB
20. Machine Learning with R - Linear Regression/3. Linear Regression with R - Part 2.mp4 54.0 MB
22. Machine Learning with R - Logistic Regression/3. Logistic Regression with R - Part 2.mp4 47.6 MB
24. Machine Learning with R - K Nearest Neighbors/2. K Nearest Neighbors with R.mp4 46.7 MB
21. Machine Learning Project - Linear Regression/1. Introduction to Linear Regression Project.mp4 46.5 MB
22. Machine Learning with R - Logistic Regression/2. Logistic Regression with R - Part 1.mp4 46.3 MB
1. Course Introduction/4.1 R-Course-HTML-Notes.zip 45.6 MB
6. Development Environment Overview/2.1 R-Course-HTML-Notes.zip 45.6 MB
18. Capstone Data Project/1. Introduction to Capstone Project.mp4 45.5 MB
15. Data Visualization with R/3. Scatterplots.mp4 45.2 MB
12. R Programming Basics/10. Functions Training Exercise - Solutions.mp4 43.4 MB
32. Machine Learning with R - Natural Language Processing/3. Natural Language Processing with R - Part 2.mp4 42.8 MB
17. Interactive Visualizations with Plotly/1. Overview of Plotly and Interactive Visualizations.mp4 42.5 MB
16. Data Visualization Project/2. Data Visualization Project - Solutions Walkthrough - Part 1.mp4 42.0 MB
16. Data Visualization Project/3. Data Visualization Project Solutions Walkthrough - Part 2.mp4 41.5 MB
12. R Programming Basics/8. Functions.mp4 40.6 MB
28. Machine Learning with R - Support Vector Machines/2. Support Vector Machines with R.mp4 39.6 MB
9. R Data Frames/5. Overview of Data Frame Operations - Part 2.mp4 38.9 MB
27. Machine Learning Project - Decision Trees and Random Forests/2. Tree Methods Project Solutions - Part 1.mp4 38.9 MB
23. Machine Learning Project - Logistic Regression/3. Logistic Regression Project Solutions - Part 2.mp4 38.6 MB
31. Machine Learning Project - K-means Clustering/2. K Means Clustering Project - Solutions Walkthrough.mp4 38.2 MB
23. Machine Learning Project - Logistic Regression/4. Logistic Regression Project - Solutions Part 3.mp4 37.6 MB
6. Development Environment Overview/3. Guide to RStudio.mp4 35.1 MB
9. R Data Frames/4. Overview of Data Frame Operations - Part 1.mp4 34.6 MB
26. Machine Learning with R - Decision Trees and Random Forests/2. Decision Trees and Random Forests with R.mp4 34.4 MB
9. R Data Frames/7. Data Frame Training Exercises - Solutions Walkthrough.mp4 34.1 MB
11. Data Input and Output with R/5. SQL with R.mp4 33.4 MB
21. Machine Learning Project - Linear Regression/3. ML - Linear Regression Project - Solutions Part 2.mp4 32.7 MB
13. Advanced R Programming/3. Apply.mp4 31.4 MB
6. Development Environment Overview/2. Course Notes.mp4 31.1 MB
15. Data Visualization with R/10. ggplot2 Exercise Solutions.mp4 30.5 MB
25. Machine Learning Project - K Nearest Neighbors/2. K Nearest Neighbors Project Solutions.mp4 30.4 MB
14. Data Manipulation with R/2. Guide to Using Dplyr.mp4 29.4 MB
12. R Programming Basics/3. if, else, and else if Statements.mp4 29.2 MB
29. Machine Learning Project - Support Vector Machines/2. Support Vector Machines Project - Solutions Part 1.mp4 28.5 MB
8. R Matrices/8. Matrix Training Exercises - Solutions Walkthrough.mp4 28.1 MB
15. Data Visualization with R/7. Coordinates and Faceting.mp4 28.0 MB
13. Advanced R Programming/6. Dates and Timestamps.mp4 27.8 MB
11. Data Input and Output with R/4. Excel Files with R.mp4 27.7 MB
12. R Programming Basics/7. For Loops.mp4 26.6 MB
20. Machine Learning with R - Linear Regression/4. Linear Regression with R - Part 3.mp4 26.3 MB
34. Machine Learning Project - Neural Nets/2. Neural Nets Project - Solutions.mp4 25.5 MB
15. Data Visualization with R/6. 2 Variable Plotting.mp4 24.7 MB
3. Windows Installation Set-Up/1. Windows Installation Procedure.mp4 24.5 MB
29. Machine Learning Project - Support Vector Machines/3. Support Vector Machines Project - Solutions Part 2.mp4 24.3 MB
12. R Programming Basics/5. Conditional Statements Training Exercise - Solutions Walkthrough.mp4 24.2 MB
14. Data Manipulation with R/3. Guide to Using Dplyr - Part 2.mp4 24.1 MB
11. Data Input and Output with R/6. Web Scraping with R.mp4 22.8 MB
30. Machine Learning with R - K-means Clustering/2. K Means Clustering with R.mp4 22.5 MB
22. Machine Learning with R - Logistic Regression/1. Introduction to Logistic Regression.mp4 21.9 MB
10. R Lists/1. List Basics.mp4 21.9 MB
9. R Data Frames/2. Data Frame Basics.mp4 21.5 MB
8. R Matrices/2. Creating a Matrix.mp4 21.2 MB
13. Advanced R Programming/2. Built-in R Features.mp4 20.4 MB
15. Data Visualization with R/4. Barplots.mp4 20.0 MB
9. R Data Frames/3. Data Frame Indexing and Selection.mp4 19.0 MB
7. Introduction to R Basics/8. Vector Indexing and Slicing.mp4 17.9 MB
1. Course Introduction/1. Introduction to Course.mp4 17.4 MB
8. R Matrices/6. Factor and Categorical Matrices.mp4 17.0 MB
15. Data Visualization with R/5. Boxplots.mp4 16.7 MB
14. Data Manipulation with R/4. Pipe Operator.mp4 16.6 MB
12. R Programming Basics/2. Logical Operators.mp4 16.2 MB
14. Data Manipulation with R/7. Dplyr Training Exercise - Solutions Walkthrough.mp4 15.6 MB
7. Introduction to R Basics/5. Vector Basics.mp4 15.3 MB
16. Data Visualization Project/1. Data Visualization Project.mp4 15.2 MB
7. Introduction to R Basics/11. R Basics Training Exercise - Solutions Walkthrough.mp4 14.7 MB
25. Machine Learning Project - K Nearest Neighbors/1. Introduction K Nearest Neighbors Project.mp4 14.7 MB
11. Data Input and Output with R/2. CSV Files with R.mp4 14.1 MB
12. R Programming Basics/6. While Loops.mp4 13.5 MB
23. Machine Learning Project - Logistic Regression/1. Introduction to Logistic Regression Project.mp4 13.4 MB
15. Data Visualization with R/8. Themes.mp4 13.4 MB
15. Data Visualization with R/1. Overview of ggplot2.mp4 13.3 MB
8. R Matrices/5. Matrix Selection and Indexing.mp4 13.3 MB
13. Advanced R Programming/4. Math Functions with R.mp4 13.0 MB
8. R Matrices/4. Matrix Operations.mp4 12.8 MB
33. Machine Learning with R - Neural Nets/1. Introduction to Neural Nets.mp4 12.7 MB
32. Machine Learning with R - Natural Language Processing/2. Natural Language Processing with R - Part 1.mp4 12.6 MB
26. Machine Learning with R - Decision Trees and Random Forests/1. Introduction to Tree Methods.mp4 12.5 MB
7. Introduction to R Basics/7. Comparison Operators.mp4 11.9 MB
20. Machine Learning with R - Linear Regression/1. Introduction to Linear Regression.mp4 11.6 MB
29. Machine Learning Project - Support Vector Machines/1. Introduction to SVM Project.mp4 11.5 MB
34. Machine Learning Project - Neural Nets/1. Introduction to Neural Nets Project.mp4 11.1 MB
13. Advanced R Programming/5. Regular Expressions.mp4 11.0 MB
27. Machine Learning Project - Decision Trees and Random Forests/3. Tree Methods Project Solutions - Part 2.mp4 10.5 MB
27. Machine Learning Project - Decision Trees and Random Forests/1. Introduction to Decision Trees and Random Forests Project.mp4 10.2 MB
7. Introduction to R Basics/4. R Basic Data Types.mp4 9.9 MB
7. Introduction to R Basics/3. Variables.mp4 9.9 MB
30. Machine Learning with R - K-means Clustering/1. Introduction to K-Means Clustering.mp4 9.6 MB
24. Machine Learning with R - K Nearest Neighbors/1. Introduction to K Nearest Neighbors.mp4 9.3 MB
28. Machine Learning with R - Support Vector Machines/1. Introduction to Support Vector Machines.mp4 9.0 MB
8. R Matrices/3. Matrix Arithmetic.mp4 8.9 MB
31. Machine Learning Project - K-means Clustering/1. Introduction to K Means Clustering Project.mp4 8.8 MB
12. R Programming Basics/9. Functions Training Exercise.mp4 8.6 MB
7. Introduction to R Basics/2. Arithmetic in R.mp4 8.5 MB
7. Introduction to R Basics/6. Vector Operations.mp4 8.4 MB
15. Data Visualization with R/9. ggplot2 Exercises.mp4 8.3 MB
32. Machine Learning with R - Natural Language Processing/1. Introduction to Natural Language Processing.mp4 8.3 MB
1. Course Introduction/3. What is Data Science.mp4 7.8 MB
7. Introduction to R Basics/9. Getting Help with R and RStudio.mp4 6.8 MB
1. Course Introduction/2. Course Curriculum.mp4 6.7 MB
7. Introduction to R Basics/10. R Basics Training Exercise.mp4 6.5 MB
7. Introduction to R Basics/1. Introduction to R Basics.mp4 6.4 MB
9. R Data Frames/6. Data Frame Training Exercise.mp4 5.0 MB
12. R Programming Basics/4. Conditional Statements Training Exercise.mp4 4.4 MB
8. R Matrices/7. Matrix Training Exercise.mp4 3.8 MB
14. Data Manipulation with R/6. Dplyr Training Exercise.mp4 3.1 MB
19. Introduction to Machine Learning with R/2.1 Machine Learning Slides.zip 2.9 MB
12. R Programming Basics/1. Introduction to Programming Basics.mp4 1.9 MB
13. Advanced R Programming/1. Introduction to Advanced R Programming.mp4 1.8 MB
8. R Matrices/1. Introduction to R Matrices.mp4 1.6 MB
9. R Data Frames/1. Introduction to R Data Frames.mp4 1.5 MB
14. Data Manipulation with R/1. Data Manipulation Overview.mp4 1.3 MB
6. Development Environment Overview/1. Development Environment Overview.mp4 1.1 MB
11. Data Input and Output with R/1. Introduction to Data Input and Output with R.mp4 1.0 MB
33. Machine Learning with R - Neural Nets/2. Neural Nets with R.srt 31.4 KB
20. Machine Learning with R - Linear Regression/3. Linear Regression with R - Part 2.srt 29.8 KB
18. Capstone Data Project/2. Capstone Project Solutions Walkthrough.srt 29.6 KB
21. Machine Learning Project - Linear Regression/2. ML - Linear Regression Project - Solutions Part 1.srt 29.3 KB
12. R Programming Basics/10. Functions Training Exercise - Solutions.srt 28.6 KB
20. Machine Learning with R - Linear Regression/2. Linear Regression with R - Part 1.srt 28.2 KB
22. Machine Learning with R - Logistic Regression/2. Logistic Regression with R - Part 1.srt 28.0 KB
15. Data Visualization with R/2. Histograms.srt 27.9 KB
14. Data Manipulation with R/8. Guide to Using Tidyr.srt 27.8 KB
23. Machine Learning Project - Logistic Regression/2. Logistic Regression Project Solutions - Part 1.srt 27.8 KB
19. Introduction to Machine Learning with R/2. Introduction to Machine Learning.srt 27.1 KB
9. R Data Frames/5. Overview of Data Frame Operations - Part 2.srt 26.8 KB
12. R Programming Basics/8. Functions.srt 26.1 KB
24. Machine Learning with R - K Nearest Neighbors/2. K Nearest Neighbors with R.srt 25.3 KB
22. Machine Learning with R - Logistic Regression/3. Logistic Regression with R - Part 2.srt 24.9 KB
9. R Data Frames/4. Overview of Data Frame Operations - Part 1.srt 24.4 KB
15. Data Visualization with R/3. Scatterplots.srt 23.8 KB
31. Machine Learning Project - K-means Clustering/2. K Means Clustering Project - Solutions Walkthrough.srt 23.3 KB
27. Machine Learning Project - Decision Trees and Random Forests/2. Tree Methods Project Solutions - Part 1.srt 22.7 KB
23. Machine Learning Project - Logistic Regression/3. Logistic Regression Project Solutions - Part 2.srt 21.8 KB
28. Machine Learning with R - Support Vector Machines/2. Support Vector Machines with R.srt 20.7 KB
9. R Data Frames/7. Data Frame Training Exercises - Solutions Walkthrough.srt 20.7 KB
32. Machine Learning with R - Natural Language Processing/3. Natural Language Processing with R - Part 2.srt 20.2 KB
13. Advanced R Programming/3. Apply.srt 20.1 KB
12. R Programming Basics/3. if, else, and else if Statements.srt 19.9 KB
15. Data Visualization with R/10. ggplot2 Exercise Solutions.srt 19.2 KB
23. Machine Learning Project - Logistic Regression/4. Logistic Regression Project - Solutions Part 3.srt 19.2 KB
8. R Matrices/8. Matrix Training Exercises - Solutions Walkthrough.srt 19.2 KB
6. Development Environment Overview/3. Guide to RStudio.srt 19.0 KB
12. R Programming Basics/7. For Loops.srt 18.0 KB
14. Data Manipulation with R/2. Guide to Using Dplyr.srt 17.9 KB
11. Data Input and Output with R/4. Excel Files with R.srt 17.6 KB
12. R Programming Basics/5. Conditional Statements Training Exercise - Solutions Walkthrough.srt 17.4 KB
26. Machine Learning with R - Decision Trees and Random Forests/2. Decision Trees and Random Forests with R.srt 17.1 KB
22. Machine Learning with R - Logistic Regression/1. Introduction to Logistic Regression.srt 17.0 KB
13. Advanced R Programming/6. Dates and Timestamps.srt 16.5 KB
16. Data Visualization Project/2. Data Visualization Project - Solutions Walkthrough - Part 1.srt 16.5 KB
16. Data Visualization Project/3. Data Visualization Project Solutions Walkthrough - Part 2.srt 16.3 KB
11. Data Input and Output with R/5. SQL with R.srt 16.0 KB
20. Machine Learning with R - Linear Regression/4. Linear Regression with R - Part 3.srt 15.6 KB
29. Machine Learning Project - Support Vector Machines/2. Support Vector Machines Project - Solutions Part 1.srt 15.3 KB
21. Machine Learning Project - Linear Regression/3. ML - Linear Regression Project - Solutions Part 2.srt 15.1 KB
6. Development Environment Overview/2. Course Notes.srt 14.7 KB
8. R Matrices/2. Creating a Matrix.srt 14.6 KB
29. Machine Learning Project - Support Vector Machines/3. Support Vector Machines Project - Solutions Part 2.srt 14.3 KB
14. Data Manipulation with R/3. Guide to Using Dplyr - Part 2.srt 14.1 KB
30. Machine Learning with R - K-means Clustering/2. K Means Clustering with R.srt 14.1 KB
7. Introduction to R Basics/8. Vector Indexing and Slicing.srt 14.1 KB
15. Data Visualization with R/7. Coordinates and Faceting.srt 14.0 KB
21. Machine Learning Project - Linear Regression/1. Introduction to Linear Regression Project.srt 13.9 KB
25. Machine Learning Project - K Nearest Neighbors/2. K Nearest Neighbors Project Solutions.srt 13.5 KB
17. Interactive Visualizations with Plotly/1. Overview of Plotly and Interactive Visualizations.srt 13.1 KB
9. R Data Frames/3. Data Frame Indexing and Selection.srt 12.8 KB
10. R Lists/1. List Basics.srt 12.8 KB
18. Capstone Data Project/1. Introduction to Capstone Project.srt 12.7 KB
13. Advanced R Programming/2. Built-in R Features.srt 12.5 KB
34. Machine Learning Project - Neural Nets/2. Neural Nets Project - Solutions.srt 12.2 KB
9. R Data Frames/2. Data Frame Basics.srt 11.9 KB
15. Data Visualization with R/4. Barplots.srt 11.5 KB
8. R Matrices/6. Factor and Categorical Matrices.srt 11.4 KB
12. R Programming Basics/2. Logical Operators.srt 11.3 KB
15. Data Visualization with R/5. Boxplots.srt 10.7 KB
11. Data Input and Output with R/6. Web Scraping with R.srt 10.4 KB
12. R Programming Basics/6. While Loops.srt 10.4 KB
15. Data Visualization with R/6. 2 Variable Plotting.srt 10.3 KB
7. Introduction to R Basics/11. R Basics Training Exercise - Solutions Walkthrough.srt 10.2 KB
15. Data Visualization with R/1. Overview of ggplot2.srt 10.2 KB
3. Windows Installation Set-Up/1. Windows Installation Procedure.srt 10.1 KB
7. Introduction to R Basics/5. Vector Basics.srt 10.0 KB
14. Data Manipulation with R/7. Dplyr Training Exercise - Solutions Walkthrough.srt 9.9 KB
8. R Matrices/5. Matrix Selection and Indexing.srt 9.6 KB
7. Introduction to R Basics/7. Comparison Operators.srt 9.6 KB
14. Data Manipulation with R/4. Pipe Operator.srt 9.3 KB
11. Data Input and Output with R/2. CSV Files with R.srt 9.3 KB
33. Machine Learning with R - Neural Nets/1. Introduction to Neural Nets.srt 9.3 KB
26. Machine Learning with R - Decision Trees and Random Forests/1. Introduction to Tree Methods.srt 9.3 KB
4. Mac OS Installation Set-Up/1. Mac OS Installation Procedure.srt 8.7 KB
20. Machine Learning with R - Linear Regression/1. Introduction to Linear Regression.srt 8.1 KB
15. Data Visualization with R/8. Themes.srt 7.7 KB
32. Machine Learning with R - Natural Language Processing/2. Natural Language Processing with R - Part 1.srt 7.6 KB
7. Introduction to R Basics/4. R Basic Data Types.srt 7.6 KB
8. R Matrices/4. Matrix Operations.srt 7.6 KB
7. Introduction to R Basics/3. Variables.srt 7.4 KB
27. Machine Learning Project - Decision Trees and Random Forests/3. Tree Methods Project Solutions - Part 2.srt 7.2 KB
24. Machine Learning with R - K Nearest Neighbors/1. Introduction to K Nearest Neighbors.srt 7.2 KB
30. Machine Learning with R - K-means Clustering/1. Introduction to K-Means Clustering.srt 7.0 KB
13. Advanced R Programming/5. Regular Expressions.srt 6.9 KB
7. Introduction to R Basics/2. Arithmetic in R.srt 6.5 KB
8. R Matrices/3. Matrix Arithmetic.srt 6.5 KB
7. Introduction to R Basics/6. Vector Operations.srt 6.4 KB
32. Machine Learning with R - Natural Language Processing/1. Introduction to Natural Language Processing.srt 6.2 KB
28. Machine Learning with R - Support Vector Machines/1. Introduction to Support Vector Machines.srt 6.1 KB
1. Course Introduction/3. What is Data Science.srt 5.8 KB
25. Machine Learning Project - K Nearest Neighbors/1. Introduction K Nearest Neighbors Project.srt 5.3 KB
13. Advanced R Programming/4. Math Functions with R.srt 4.9 KB
16. Data Visualization Project/1. Data Visualization Project.srt 4.7 KB
15. Data Visualization with R/9. ggplot2 Exercises.srt 4.5 KB
7. Introduction to R Basics/1. Introduction to R Basics.srt 4.1 KB
12. R Programming Basics/9. Functions Training Exercise.srt 3.9 KB
1. Course Introduction/1. Introduction to Course.srt 3.9 KB
29. Machine Learning Project - Support Vector Machines/1. Introduction to SVM Project.srt 3.9 KB
34. Machine Learning Project - Neural Nets/1. Introduction to Neural Nets Project.srt 3.5 KB
7. Introduction to R Basics/10. R Basics Training Exercise.srt 3.5 KB
31. Machine Learning Project - K-means Clustering/1. Introduction to K Means Clustering Project.srt 3.5 KB
1. Course Introduction/2. Course Curriculum.srt 3.4 KB
7. Introduction to R Basics/9. Getting Help with R and RStudio.srt 3.3 KB
23. Machine Learning Project - Logistic Regression/1. Introduction to Logistic Regression Project.srt 2.8 KB
27. Machine Learning Project - Decision Trees and Random Forests/1. Introduction to Decision Trees and Random Forests Project.srt 2.8 KB
12. R Programming Basics/4. Conditional Statements Training Exercise.srt 2.5 KB
2. Course Best Practices/1. How to Get Help in the Course!.html 2.0 KB
14. Data Manipulation with R/6. Dplyr Training Exercise.srt 2.0 KB
11. Data Input and Output with R/3. Note on R with Excel Download.html 1.9 KB
9. R Data Frames/6. Data Frame Training Exercise.srt 1.7 KB
12. R Programming Basics/1. Introduction to Programming Basics.srt 1.6 KB
8. R Matrices/7. Matrix Training Exercise.srt 1.5 KB
13. Advanced R Programming/1. Introduction to Advanced R Programming.srt 1.5 KB
5. Linux Installation/1. LinuxUnbuntu Installation Procedure.html 1.5 KB
1. Course Introduction/4. Course FAQ.html 1.3 KB
8. R Matrices/1. Introduction to R Matrices.srt 1.2 KB
9. R Data Frames/1. Introduction to R Data Frames.srt 1.1 KB
14. Data Manipulation with R/1. Data Manipulation Overview.srt 1.0 KB
17. Interactive Visualizations with Plotly/2. Resources for Plotly and ggplot2.html 962 bytes
35. Bonus Section/1. Bonus Lecture.html 532 bytes
11. Data Input and Output with R/1. Introduction to Data Input and Output with R.srt 494 bytes
6. Development Environment Overview/1. Development Environment Overview.srt 483 bytes
19. Introduction to Machine Learning with R/1. ISLR PDF.html 393 bytes
2. Course Best Practices/3. Installation and Set-Up.html 335 bytes
14. Data Manipulation with R/5. Quick note on Dpylr exercise.html 309 bytes
2. Course Best Practices/2. Welcome to the Course..html 159 bytes
0. Websites you may like/[FCS Forum].url 133 bytes
0. Websites you may like/[FreeCourseSite.com].url 127 bytes
0. Websites you may like/[CourseClub.ME].url 122 bytes
8. R Matrices/4.1 Reference of Built-in Functions.html 117 bytes

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