Tutorialsplanet NET Udemy - R Programming Hands-on Specialization for Data Science Lv1

1. 1. Introduction/1. Warm Welcome!.mp45.34MB
2. 1. Introduction/2. Why you should learn R.mp422.92MB
3. 1. Introduction/3. What you will learn in this course.mp414.88MB
4. 2. R Fundamentals/1. Installing R (console) and RStudio (IDE).mp413.61MB
5. 2. R Fundamentals/2. Getting to know R - Setting Context.mp43.59MB
6. 2. R Fundamentals/3. R Basics - Working Directory, Environment Variables and more!.mp427.52MB
7. 2. R Fundamentals/4. R Basics - Loading and Executing R scripts from local file system.mp411.75MB
8. 3. R Data Types/1. R Atomic Data Types Intro - What you must know about Numeric and Integers in R.mp417.76MB
9. 3. R Data Types/2. Complex and Character Data Types (Atomic).mp49.61MB
10. 3. R Data Types/3. Character Data Type (Atomic) + Important Data Transformation Functions (1).mp48.49MB
11. 3. R Data Types/4. Character Data Type (Atomic) + Important Data Transformation Functions (2).mp46.86MB
12. 3. R Data Types/5. Character Data Type (Atomic) + Important Data Transformation Functions (3).mp413.82MB
13. 3. R Data Types/6. Logical Data Type (Atomic) and Its known Implications.mp48.29MB
14. 3. R Data Types/7. Atomic Data Types and Nuances in Coercioning (ExplicitImplicit).mp416.12MB
15. 4. R Data Structure - Vectors/1. Vectors - Creation, Homogeneity, Coercion Implications and Important Functions!.mp423.46MB
16. 4. R Data Structure - Vectors/2. Vectors - Comparing different ways to create vectors in R!.mp411.23MB
17. 4. R Data Structure - Vectors/3. Vectors - Understanding Indexing like never before!.mp419.7MB
18. 4. R Data Structure - Vectors/4. Vectors - Indexing (Out of Bound scenarios) and How Pros use it!.mp419.26MB
19. 4. R Data Structure - Vectors/5. Vectors - Flatness property and its critical implications in Indexing!.mp410.78MB
20. 4. R Data Structure - Vectors/6. Vectors - Labels and their Advanced Usage in Indexing.mp416.64MB
21. 4. R Data Structure - Vectors/7. Vectors - Assigning Attributes and its use-case as Metadata.mp410.62MB
22. 5. R Data Structure - Matrices/1. Matrices - Getting Acquainted, Creation and its operational functions!.mp417.6MB
23. 5. R Data Structure - Matrices/2. Matrices - Creation and Implications related to its Dimensions.mp411.72MB
24. 5. R Data Structure - Matrices/3. Matrices - Creation from Vectors + Naming Dimensions (Explicit, Implicit).mp424.1MB
25. 5. R Data Structure - Matrices/4. Matrices - Dimensions (Advanced) and Intro to Indexing.mp47.62MB
26. 5. R Data Structure - Matrices/5. Matrices - Indexing Continued.mp46.54MB
27. 5. R Data Structure - Matrices/6. Matrices - Advanced Indexing using DimensionNames.mp47.87MB
28. 5. R Data Structure - Matrices/7. Matrices - Even more Advanced Indexing!.mp413.88MB
29. 5. R Data Structure - Matrices/8. Matrices - Operations!.mp411.34MB
30. 6. R Data Structure - Lists/1. Lists - Getting Introduced to one of the most powerful data structures in R.mp411.45MB
31. 6. R Data Structure - Lists/2. Lists - Comparing with Vectors w.r.t Heterogeneity and Introducing Indexing.mp48.74MB
32. 6. R Data Structure - Lists/3. Lists - Comprehending their Recursive Nature in comparison with Vectors.mp46.67MB
33. 6. R Data Structure - Lists/4. Lists - Converting to and from Vectors and implications (coercion, flatness).mp48.44MB
34. 6. R Data Structure - Lists/5. Lists - Nuances in Determining Length in the context of Recursiveness.mp48.02MB
35. 6. R Data Structure - Lists/6. Lists - Nuances in Determining Length and Class of Elements.mp411.32MB
36. 6. R Data Structure - Lists/7. List - Advanced Indexing also using Labels.mp415.84MB
37. 6. R Data Structure - Lists/8. List - Comparison of Indexing ways and Implications.mp49.86MB
38. 7. R Data Structure - Data Frames/1. Data Frames - Introducing The holy grail of processing Structured Data.mp418.73MB
39. 7. R Data Structure - Data Frames/2. Data Frames - Creation and important functions for Basic Exploratory Analysis.mp425.2MB
40. 7. R Data Structure - Data Frames/3. Data Frames - More Important Functions for Basic Exploratory Analysis.mp417.15MB
41. 7. R Data Structure - Data Frames/4. Data Frames - Creation from Lists.mp43.78MB
42. 7. R Data Structure - Data Frames/5. Data Frames - Creation from Lists, Matrices and Vectors.mp45.98MB
43. 7. R Data Structure - Data Frames/6. Data Frames - Everything you need to know about Subsetting.mp429.56MB
44. 7. R Data Structure - Data Frames/7. Data Frames - Handling Missing Values like Pros!.mp420.4MB
45. 7. R Data Structure - Data Frames/8. Data Frames - Imputing Missing Values like Pros!.mp428.35MB
46. 7. R Data Structure - Data Frames/9. Data Frames - Advanced Subsetting Techniques for robust analytics.mp425.75MB
47. 8. R Control Structures/1. While Loops in R.mp410.06MB
48. 8. R Control Structures/2. For Loops in R - Intro and Practical Use-Cases.mp422MB
49. 8. R Control Structures/3. If Else Structures in R.mp48.41MB
50. 8. R Control Structures/4. If Else Structures in R (2).mp418.19MB
51. 8. R Control Structures/5. If Else Structures in R (3).mp46.22MB
52. 9. Data Science Application in R - Automated Web Scraping Bot/1. Web Scraping - Setting Context + Highlighting Use-Cases.mp424MB
53. 9. Data Science Application in R - Automated Web Scraping Bot/11. Web Scraping on Steroids - XPath in R!.mp417.6MB
54. 9. Data Science Application in R - Automated Web Scraping Bot/12. Web Scraping on Steroids - XPath in R (2).mp42.26MB
55. 9. Data Science Application in R - Automated Web Scraping Bot/15. Automating Web Scraping - RSelenium!.mp48.65MB
56. 9. Data Science Application in R - Automated Web Scraping Bot/17. Automated Web Scraping - installing RSelenium in R.mp49.07MB
57. 9. Data Science Application in R - Automated Web Scraping Bot/18. Automated Web Scraping - Initialising RSelenium Server.mp410.72MB
58. 9. Data Science Application in R - Automated Web Scraping Bot/2. Web Scraping - One Simple yet Powerful Way to do so!.mp433.73MB
59. 9. Data Science Application in R - Automated Web Scraping Bot/21. Web Scraping Use Case Context Setting.mp410.56MB
60. 9. Data Science Application in R - Automated Web Scraping Bot/22. Web Scraping Pipeline - Deep dive of workflow pattern.mp413.77MB
61. 9. Data Science Application in R - Automated Web Scraping Bot/23. Systematic analysis of website for efficient Scraping.mp422.1MB
62. 9. Data Science Application in R - Automated Web Scraping Bot/24. Installing and Loading RSelenium.mp49.52MB
63. 9. Data Science Application in R - Automated Web Scraping Bot/25. Starting Selenium Server - The right way!.mp412.98MB
64. 9. Data Science Application in R - Automated Web Scraping Bot/26. Handling RSelenium's Driver Issues.mp43.64MB
65. 9. Data Science Application in R - Automated Web Scraping Bot/3. Web Scraping - Use Case Custom Churn Analysis.mp424.97MB
66. 9. Data Science Application in R - Automated Web Scraping Bot/33. Advanced Data Munging - Discretizing Continuous Values.mp425.62MB
67. 9. Data Science Application in R - Automated Web Scraping Bot/34. Advanced Data Frames Manipulation.mp433.71MB
68. 9. Data Science Application in R - Automated Web Scraping Bot/35. Orchestrating Automation of Web Scraping Routine.mp421.4MB
69. 9. Data Science Application in R - Automated Web Scraping Bot/6. Use Case Custom Churn - Performing Data Cleansing.mp423.76MB
70. 9. Data Science Application in R - Automated Web Scraping Bot/7. Web Scraping - Contextual understanding of HTML.mp410.46MB
71. 9. Data Science Application in R - Automated Web Scraping Bot/8. Web Scraping - Contextual Understanding of HTML Tags.mp420.88MB