R for Data Analysis: Students and Professionals

سرفصل های دوره

Most Honest Crash Course to Become a Data Analyst using R by Solving Real-World Data Problems

1. Welcome to the Course

1. 0 1. Lecture Part A - Course Intro

2. 0 2. Lecture Part B - Overview of R and R Studio

3. 0 3. Lecture Part C - Install R and Launching R Studio

4. 0 4. Lecture Part D - Intro to R Packages and Installation

5.1 CoursePack R for Data Analysts.zip

5. DOWNLOAD COURSE PACK Datasets, Coding Exercises, Course Outline and Cheatsheet.html

6. 0 5. Demo Overview of Course Folder Structure

7. 0 6. Demo Part A - How to Download R and R Studio

8. 0 7. Demo Part B - How to Install R

9. 0 8. Demo Part C - How to Install R Studio

10. 0 9. Demo Part D - Navigate R and R Studio

2. Load and Write Data in R

1. What You Will Learn Module 1.html

2. 1 1. Lecture Part A - Summary of Data Objects and Structures

3. 1 2. Lecture Part B - Define Path and Load Data

4. 1 3. Lecture Part C - Write Data

5. 1 4. Welcome to Lab 1 Overview

6. 1 5. Problem 1 Install R Packages

7. 1 6. Problem 2 Define Folder Paths and Setup Directories

8. 1 7. Problem 3 Load Data into R Workspace

9. 1 8. Problem 4 Write Data into R Workspace

10. 1 9. Extra Problem Capture a Snapshot Date from Filenames

3. Data Types and Formatting

1. What You Will Learn Moudle 2.html

2. 2 1. Lecture Data Types and Data Type Conversion in R

3. 2 2. Lecture Check Column Names and Rename Columns

4. 2 3. Lecture Date Formatting - Year, Month, etc.

5. 2 4. Lecture Character Formatting - Add Leading Zeros

6. 2 5. Welcome to Lab 2 Overview

7. 2 6. Problem 1 Check Data Types

8. 2 7. Problem 2 Rename Columns

9. 2 8. Problem 3 Date Formatting

10. 2 9. Problem 4 Add Leading Zeros

4. Data Manipulation

1. What You Will Learn Module 3.html

2. 3 1. Lecture Clean Data (drop columns, remove duplicates)

3. 3 2. Lecture Clean Data (recode and replace values)

4. 3 3. Lecture Sort and Order Data

5. 3 4. Lecture Subset Data (Columns, List, Conditions)

6. 3 5. Welcome to Lab 3 Overview

7. 3 6. Problem 1 Cleaning Data

8. 3 7. Problem 2 Recode Data

9. 3 8. Problem 3 Replace Data

10. 3 9. Problem 4 Arrange Data

11. 3 10. Problem 5 Sort Data

12. 3 11. Problem 6 Subset Data

5. Join Data Operations

1. What You Will Learn Module 4.html

2. 4 1. Lecture What is Join and Types of Join

3. 4 2. Lecture Perform Joins with dplyr

4. 4 3. Lecture Perform Joins with sqldf

5. 4 4. Lecture Advanced Join Problem - Temporal

6. 4 5. Lecture Advanced Join Problem - Subquery with Max()

7. 4 7. Weclome to Lab 4 Overview

8. 4 8. Problem 1 Perform Joins with dplyr

9. 4 9. Problem 2 Perform Joins with sqldf

10. 4 10. Problem 3 Perform Joins on Multiple Tables

11. 4 11. Problem 4 Advanced Join Temporal

12. 4 12. Problem 5 Advanced Subquery Max()

13. 4 13. Extra Problem Identify Changes in Account Information

6. Data Aggregation and Feature Engineering

1. What You Will Learn Module 5.html

2. 5 1. Lecture Summarize Data (count(), sum(), etc.)

3. 5 2. Lecture Filtering and Slicing Data

4. 5 3. Lecture Convert a Summary Table Format

5. 5 4. Lecture Feature Engineering using mutate()

6. 5 5. Welcome to Lab 5 Overview

7. 5 6. Problem 1 Summarize Data with dplyr using summarize()

8. 5 7. Problem 2 Filter Data with dplyr

9. 5 8. Problem 2 Slice Data with dplyr

10. 5 9. Problem 3 Sort Data with dplyr

11. 5 10. Problem 4 Convert a Summary Table Format

12. 5 11. Problem 5 Feature Engineering

7. Time Intelligence

1. What You Will Learn Module 6.html

2. 6 1. Lecture Calculate Time Features using Date Manipulation

3. 6 2. Lecture Calculate Event Sequence Analysis

4. 6 3. Lecture Calculate Number of Business Days

5. 6 4. Lecture Calculate KPIs with Different Frequencies

6. 6 5. Welcome to Lab 6 Overview

7. 6 6. Problem 1 Date Manipulation - Time Dimension

8. 6 7. Problem 1 Date Manipulation - Durations

9. 6 8. Problem 2 Calculate Event Sequence Analysis

10. 6 9. Problem 3 Calculate Business Days using bizdays Package

11. 6 10. Problem 4 Calculate a Measure at Daily Snapshot

12. 6 11. Extra Problem Calculate a Measure at Monthly Snapshot

8. Data Visualization with ggplot2

1. What You Will Learn Module 7.html

2. 7 1. Lecture Intro to Exploratory Data Analysis

3. 7 2. Lecture Uni-Variate Bar Chart

4. 7 3. Lecture Uni-Variate Pie Chart

5. 7 4. Lecture Uni-Variate Line Chart

6. 7 5. Lecture Uni-Variate Histogram

7. 7 6. Lecture Uni-Variate Density

8. 7 7. Lecture Bi-Variate Box Plot

9. 7 8. Lecture Bi-Variate Scatter Plot

10. 7 9. Lecture Bi-Variate Correlation Matrix

11. 7 10. Lecture Bi-Variate Cross Tabulation

12. 7 11. Welcome to Lab 7 Overview

13. 7 12. Problem 1 Uni-Variate Categorical Bar Chart

14. 7 13. Problem 1 Uni-Variate Categorical Pie Chart

15. 7 14. Problem 2 Uni-Variate Numerical Line Chart

16. 7 15. Problem 2 Uni-Variate Numerical Histogram and Density Plot

17. 7 16. Problem 3 Bi-Variate Categorical Charts Cross Tab

18. 7 17. Problem 4 Bi-Variate Numerical Charts Box Plot

19. 7 18. Problem 4 Bi-Variate Numerical Charts Scatter Plot

20. 7 19. Problem 4 Bi-Variate Numerical Charts Correlation Matrix

9. Capstone Projects

1. Capstone Project 1 - OpenAirBnB

2. 8 1. Capstone Project 1 - Solution Part A

3. 8 2. Capstone Project 1 - Solution Part B

4. 8 3. Capstone Project 1 - Solution Part C

5. 8 4. Capstone Project 1 - Solution Part D

6. Capstone Project 2 - Hotel Bookings (Extra).html

7. 8 5. Capstone Project 2 - Solution (Text Reminder).html

10. CONGRATULATIONS!!!

1. Course Wrap Up.html

2. Congratulations!!!

3. Bonus Lecture.html

“طراحی Layot های Responsive بوسیله CSS Grid, Flexbox” به سبد خرید شما اضافه شد. مشاهده سبد خرید

179,000 تومان

افزودن به سبد خرید

خرید دانلودی فوری

در این روش نیاز به افزودن محصول به سبد خرید و تکمیل اطلاعات نیست و شما پس از وارد کردن ایمیل خود و طی کردن مراحل پرداخت لینک های دریافت محصولات را در ایمیل خود دریافت خواهید کرد.

تولید کننده: Udemy