Enroll Now

Price With GST: ₹17700/-

Subject: Data Science Level: Expert**01: History and Overview of R**
- What is R?
- What is S?
- The S Philosophy
- Back to R
- Basic Features of R
- Free Software
- Design of the R System
- Limitations of R
- R Resources

**02: Getting Started with R**
- Installation
- Getting started with the R interface

**03: R Nuts and Bolts**
- Entering Input
- Evaluation
- R Objects
- Numbers
- Attributes
- Creating Vectors
- Mixing Objects
- Explicit Coercion
- Matrices
- Lists
- Factors
- Missing Values
- Data Frames
- Names
- Summary

**03: Getting Data In and Out of R**
- Reading and Writing Data
- Reading Data Files with readtable()
- Reading in Larger Datasets with readtable
- Calculating Memory Requirements for R Objects

**04: Using the readr Package**

**05: Using Textual and Binary Formats for Storing Data**
- Using dput() and dump()
- Binary Formats

**06: Interfaces to the Outside World**
- File Connections
- Reading Lines of a Text File
- Reading From a URL Connection

**07: Subsetting R Objects**
- Subsetting a Vector
- Subsetting a Matrix
- Subsetting Lists
- Subsetting Nested Elements of a List
- Extracting Multiple Elements of a List
- Partial Matching
- Removing NA Values

**08: Vectorized Operations**
- Vectorized Matrix Operations

**09: Dates and Times**
- Dates in R
- Times in R
- Operations on Dates and Times
- Summary

**10: Managing Data Frames with the dplyr package**
- Data Frames
- The dplyr Package
- dplyr Grammar
- Installing the dplyr package
- select()
- filter()
- arrange()
- rename()
- mutate()

**11: Control Structures**
- if-else
- for Loops
- Nested for loops
- while Loops
- repeat Loops
- next, break
- Summary

**12: Functions**
- Functions in R
- Your First Function
- Argument Matching
- Lazy Evaluation
- The Argument
- Arguments Coming After the Argument
- Summary

**13: Scoping Rules of R**
- A Diversion on Binding Values to Symbol
- Scoping Rules
- Lexical Scoping: Why Does It Matter?
- Lexical vs Dynamic Scoping
- Application: Optimization
- Plotting the Likelihood
- Summary

**14: Coding Standards for R**

**15: Loop Functions**
- Looping on the Command Line
- lapply()
- sapply()
- split()
- Splitting a Data Frame
- tapply
- apply()
- Col/Row Sums and Means
- Other Ways to Apply
- mapply()
- Vectorizing a Function
- Summary

**16: Debugging**
- Something’s Wrong!
- Figuring Out What’s Wrong
- Debugging Tools in R
- Using traceback()
- Using debug()
- Using recover()
- Summary

**17: Profiling R Code**
- Using systemtime()
- Timing Longer Expressions
- The R Profiler
- Using summaryRprof()
- Summary

**18: Simulation**
- Generating Random Numbers
- Setting the random number seed
- Simulating a Linear Model
- Random Sampling
- Summary

**19: Data Analysis Case Study**

Hit The Ground Running
4 videos

- Welcome to the R Programming Course!
- Installing R and R Studio (MAC & Windows)
- Exercise - Get Excited!
- BONUS: Using R in The Real World

Core Programming Principles
11 videos

- Welcome to this section. This is what you will learn!
- Types of variables
- Using Variables
- Logical Variables and Operators
- The "While" Loop
- Using the console
- The "For" Loop
- The "If" statement
- Section Recap
- HOMEWORK: Law of Large Numbers
- Core Programming Principles

Fundamentals Of R
11 videos

- Welcome to this section. This is what you will learn!
- What is a Vector?
- Let's create some vectors
- Using the [] brackets
- Vectorized operations
- The power of vectorized operations
- Functions in R
- Packages in R
- Section Recap
- HOMEWORK: Financial Statement Analysis
- Fundamentals of R

Matrices
15 videos

- Welcome to this section. This is what you will learn!
- Project Brief: Basketball Trends
- Matrices
- Building Your First Matrix
- Naming Dimensions
- Colnames() and Rownames()
- Matrix Operations
- Visualizing With Matplot()
- Subsetting
- Visualizing Subsets
- Creating Your First Function
- Basketball Insights
- Section Recap
- HOMEWORK: Basketball Free Throws
- Matrices

Data Frames
15 videos

- Welcome to this section. This is what you will learn!
- Project Brief: Demographic Analysis
- Importing data into R
- Exploring your dataset
- Using the $ sign
- Basic operations with a Data Frame
- Filtering a Data Frame
- Introduction to qplot
- Visualizing With Qplot: Part I
- Building Dataframes
- Merging Data Frames
- Visualizing With Qplot: Part II
- Section Recap
- HOMEWORK: World Trends
- Data Frames

Advanced Visualization With GGPlot2
17 videos

- Welcome to this section. This is what you will learn!
- Project Brief: Movie Ratings
- Grammar Of Graphics - GGPlot2
- What is a Factor?
- Aesthetics
- Plotting With Layers
- Overriding Aesthetics
- Mapping vs Setting
- Histograms and Density Charts
- Starting Layer Tips
- Statistical Transformations
- Using Facets
- Coordinates
- Perfecting By Adding Themes
- Section Recap
- HOMEWORK: Movie Domestic % Gross
- Advanced Visualization With GGPlot2

Homework Solutions
6 videos

- Homework Solution Section 2: Law Of Large Numbers
- Homework Solution Section 3: Financial Statement Analysis
- Homework Solution Section 4: Basketball Free Throws
- Homework Solution Section 5: World Trends
- Homework Solution Section 6: Movie Domestic % Gross (Part 1)
- Homework Solution Section 6: Movie Domestic % Gross (Part 2)

Bonus Tutorials
2 videos

- BoxPlots
- **YOUR SPECIAL BONUS**