Data Science and Machine Learning with R and Python

Data Science with R:

Types of operators used in R,IF statements,IF then else statement,nested IF, ifelse() function,switch statement,FOR loop,While loop,repeat,break,next statement

Data types in R-Vector,Scalar,Matrix,accessing a matrix by dimensions,creating matrices from vectors

Importing the data set. Setting up the working directory,creating a duplicate file,Data Exploratory functions in R such as str, summary for descriptive statistics of data,names,head,tail,sd(standard deviation),var(variance),mean,minimum,level,dim,unique,duplicate,range,tolower,toupper.

Functions in R such as apply,lapply,sapply,tapply,mapply

Data manipulation in R-Dply,Filter,multiple filter,mutate,arrange,summarize.

Functions in R such as apply,lapply,sapply,tapply,mapply

Data manipulation in R-Dply,Filter,multiple filter,mutate,arrange,summarize.

Data visualization in R-Bar graphs,Stacked bar,grouped bar graph

Data Visualization in R

Data Visualization in R-Line chart for time series data,Box plot to calculate mean, median, min ,max ,3rd quartile and 1st quartile values

Logistic Regression using Cancer remission data set.

Clustering using Kmeans 

Association Analysis in R using Market Basket analysis

Machine Learning using R

Data Science with Python:

Basics of Python,importing sys library,platform,checking the platform,run a code,checking data type,performing calculations,concatenating of strings,conversion of values,working on tuples,

Working with tuple continued,list,tuple,dictionaries(key value pair),set,In keyword,define a function,sorting using sorted function.

Data mapping and indexing using enumerate,creating dictionaries using enumerate,sorting without order,reversing the list,append the list.

Zip function,Iterate the value of tuple,If statement,else if statement,for loop,while,exception handling

Mathematical on Array using Numpy,decalring the 2D array,3D array,dtype,numpy operations,boolean array.

Shape manipulation on Arrays,flatten the data set,reshape the data set,resize the array,split array,stacking of arrays,broadcasting,scalar on arrays,transpose function,inverse function on arrays using linalg function,sum of diagonal elements using trace.

Pandas,series containing data and label,list,series from a scalar,creating series from dictionary,access the element in series according to location using iloc()

Vector operation with data alignment,creating data frame out of dictionary of equal length list,create Data frame by combining two series,create Data frame from array.

Vector operation with data alignment,creating data frame out of dictionary of equal length list,create Data frame by combining two series,create Data frame from array

Grouping by variable,Sorting of Data,standardization of data,apply standardized function to data frame

Linear regression in python

Clustering using Kmeans

Data Visualization using matplotlib

Machine learning using Python

Quizzes and practice tests included for knowledge test