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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
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