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Torrent Details For "Udemy - R Programming Advanced Analytics In R For Data Science"

Udemy - R Programming Advanced Analytics In R For Data Science

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Seeds: 19
Leechers: 3
Completed: 338
Last Checked: 23-08-2019 00:38:06

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Name:	Udemy - R Programming Advanced Analytics In R For Data Science
Description: Ready to take your R Programming skills to the next level? Want to truly become proficient at Data Science and Analytics with R? This course is for you! Professional R Video training, unique datasets designed with years of industry experience in mind, engaging exercises that are both fun and also give you a taste for Analytics of the REAL WORLD.
YouTube Video:
Category:	Tutorials
Language:	English
Total Size:	1.26 GB
Info Hash:	FCBCEA701D9A9953BCD05112CDC1353C86B6EC3E
Added By:	fclab16
Date Added:	2019-01-17 19:05:59
Torrent Status:	Torrent Verified

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File List:

File	Size
1. Welcome To The Course/1. Welcome to the Advanced R Programming Course!.mp4	29.07 MB
1. Welcome To The Course/1. Welcome to the Advanced R Programming Course!.vtt	7.97 kB
1. Welcome To The Course/2. Some Additional Resources!!.html	620.00 B
2. Data Preparation/1. Welcome to this section. This is what you will learn!.mp4	26.74 MB
2. Data Preparation/1. Welcome to this section. This is what you will learn!.vtt	3.73 kB
2. Data Preparation/10. What is an NA.mp4	13.99 MB
2. Data Preparation/10. What is an NA.vtt	7.57 kB
2. Data Preparation/11. An Elegant Way To Locate Missing Data.mp4	48.42 MB
2. Data Preparation/11. An Elegant Way To Locate Missing Data.vtt	13.85 kB
2. Data Preparation/12. Data Filters which() for Non-Missing Data.mp4	30.00 MB
2. Data Preparation/12. Data Filters which() for Non-Missing Data.vtt	12.46 kB
2. Data Preparation/13. Data Filters is.na() for Missing Data.mp4	21.48 MB
2. Data Preparation/13. Data Filters is.na() for Missing Data.vtt	7.38 kB
2. Data Preparation/14. Removing records with missing data.mp4	26.31 MB
2. Data Preparation/14. Removing records with missing data.vtt	6.40 kB
2. Data Preparation/15. Reseting the dataframe index.mp4	39.17 MB
2. Data Preparation/15. Reseting the dataframe index.vtt	6.67 kB
2. Data Preparation/16. Replacing Missing Data Factual Analysis Method.mp4	24.05 MB
2. Data Preparation/16. Replacing Missing Data Factual Analysis Method.vtt	9.44 kB
2. Data Preparation/17. Replacing Missing Data Median Imputation Method (Part 1).mp4	48.97 MB
2. Data Preparation/17. Replacing Missing Data Median Imputation Method (Part 1).vtt	18.03 kB
2. Data Preparation/18. Replacing Missing Data Median Imputation Method (Part 2).mp4	15.61 MB
2. Data Preparation/18. Replacing Missing Data Median Imputation Method (Part 2).vtt	6.29 kB
2. Data Preparation/19. Replacing Missing Data Median Imputation Method (Part 3).mp4	19.06 MB
2. Data Preparation/19. Replacing Missing Data Median Imputation Method (Part 3).vtt	8.62 kB
2. Data Preparation/2. Project Brief Financial Review.mp4	6.82 MB
2. Data Preparation/2. Project Brief Financial Review.vtt	4.14 kB
2. Data Preparation/20. Replacing Missing Data Deriving Values Method.mp4	18.45 MB
2. Data Preparation/20. Replacing Missing Data Deriving Values Method.vtt	5.88 kB
2. Data Preparation/21. Visualizing results.mp4	31.87 MB
2. Data Preparation/21. Visualizing results.vtt	14.97 kB
2. Data Preparation/22. Section Recap.mp4	10.92 MB
2. Data Preparation/22. Section Recap.vtt	7.83 kB
2. Data Preparation/23. Data Preparation.html	117.00 B
2. Data Preparation/3. Updates on Udemy Reviews.mp4	58.33 MB
2. Data Preparation/3. Updates on Udemy Reviews.vtt	3.82 kB
2. Data Preparation/4. Import Data into R.mp4	19.31 MB
2. Data Preparation/4. Import Data into R.vtt	7.19 kB
2. Data Preparation/5. What are Factors (Refresher).mp4	29.24 MB
2. Data Preparation/5. What are Factors (Refresher).vtt	10.37 kB
2. Data Preparation/6. The Factor Variable Trap.mp4	24.53 MB
2. Data Preparation/6. The Factor Variable Trap.vtt	13.94 kB
2. Data Preparation/7. FVT Example.mp4	22.53 MB
2. Data Preparation/7. FVT Example.vtt	9.28 kB
2. Data Preparation/8. gsub() and sub().mp4	33.14 MB
2. Data Preparation/8. gsub() and sub().vtt	13.12 kB
2. Data Preparation/9. Dealing with Missing Data.mp4	42.59 MB
2. Data Preparation/9. Dealing with Missing Data.vtt	12.57 kB
3. Lists in R/1. Welcome to this section. This is what you will learn!.mp4	17.77 MB
3. Lists in R/1. Welcome to this section. This is what you will learn!.vtt	2.29 kB
3. Lists in R/10. Creating A Timeseries Plot.mp4	38.28 MB
3. Lists in R/10. Creating A Timeseries Plot.vtt	11.74 kB
3. Lists in R/11. Section Recap.mp4	6.59 MB
3. Lists in R/11. Section Recap.vtt	4.57 kB
3. Lists in R/12. Lists in R.html	117.00 B
3. Lists in R/2. Project Brief Machine Utilization.mp4	53.14 MB
3. Lists in R/2. Project Brief Machine Utilization.vtt	24.99 kB
3. Lists in R/3. Import Data Into R.mp4	15.41 MB
3. Lists in R/3. Import Data Into R.vtt	7.87 kB
3. Lists in R/4. Handling Date-Times in R.mp4	38.59 MB
3. Lists in R/4. Handling Date-Times in R.vtt	13.59 kB
3. Lists in R/5. What is a List.mp4	35.97 MB
3. Lists in R/5. What is a List.vtt	14.82 kB
3. Lists in R/6. Naming components of a list.mp4	11.67 MB
3. Lists in R/6. Naming components of a list.vtt	5.99 kB
3. Lists in R/7. Extracting components lists [] vs [[]] vs $.mp4	16.75 MB
3. Lists in R/7. Extracting components lists [] vs [[]] vs $.vtt	16.76 MB
3. Lists in R/8. Adding and deleting components.mp4	32.55 MB
3. Lists in R/8. Adding and deleting components.vtt	12.53 kB
3. Lists in R/9. Subsetting a list.mp4	24.26 MB
3. Lists in R/9. Subsetting a list.vtt	10.94 kB
4. Apply Family of Functions/1. Welcome to this section. This is what you will learn!.mp4	27.71 MB
4. Apply Family of Functions/1. Welcome to this section. This is what you will learn!.vtt	3.51 kB
4. Apply Family of Functions/10. Using sapply().mp4	34.94 MB
4. Apply Family of Functions/10. Using sapply().vtt	14.63 kB
4. Apply Family of Functions/11. Nesting apply() functions.mp4	24.88 MB
4. Apply Family of Functions/11. Nesting apply() functions.vtt	10.71 kB
4. Apply Family of Functions/12. which.max() and which.min() (advanced topic).mp4	32.42 MB
4. Apply Family of Functions/12. which.max() and which.min() (advanced topic).vtt	14.83 kB
4. Apply Family of Functions/13. Section Recap.mp4	9.81 MB
4. Apply Family of Functions/13. Section Recap.vtt	7.09 kB
4. Apply Family of Functions/14. Apply Family of Functions.html	117.00 B
4. Apply Family of Functions/2. Project Brief Weather Patterns.mp4	25.31 MB
4. Apply Family of Functions/2. Project Brief Weather Patterns.vtt	12.80 kB
4. Apply Family of Functions/3. Import Data into R.mp4	28.07 MB
4. Apply Family of Functions/3. Import Data into R.vtt	13.57 kB
4. Apply Family of Functions/4. What is the Apply family.mp4	17.23 MB
4. Apply Family of Functions/4. What is the Apply family.vtt	10.72 kB
4. Apply Family of Functions/5. Using apply().mp4	25.69 MB
4. Apply Family of Functions/5. Using apply().vtt	11.73 kB
4. Apply Family of Functions/6. Recreating the apply function with loops (advanced topic).mp4	19.76 MB
4. Apply Family of Functions/6. Recreating the apply function with loops (advanced topic).vtt	10.20 kB
4. Apply Family of Functions/7. Using lapply().mp4	38.72 MB
4. Apply Family of Functions/7. Using lapply().vtt	14.58 kB
4. Apply Family of Functions/8. Combining lapply() with [].mp4	24.81 MB
4. Apply Family of Functions/8. Combining lapply() with [].vtt	9.87 kB
4. Apply Family of Functions/9. Adding your own functions.mp4	28.02 MB
4. Apply Family of Functions/9. Adding your own functions.vtt	12.34 kB
5. Bonus Lectures/1. YOUR SPECIAL BONUS.html	3.35 kB
[FreeCourseLab.com].url	126.00 B

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Udemy - R Programming Advanced Analytics In R For Data Science