Get yourself trained on Data Science and with this Online Training Data Science and Machine Learning with R and Python.
Online Training 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 KmeansAssociation Analysis in R using Market Basket analysis Machine Learning using RData 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 handlingMathematical 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 arrayGrouping by variable,Sorting of Data,standardization of data,apply standardized function to data frameLinear regression in pythonClustering using KmeansData Visualization using matplotlibMachine learning using PythonQuizzes and practice tests included for knowledge test
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As a society, we spend hundreds of billions of dollars measuring the return on our financial assets. Yet, at the same time, we still haven’t found convincing ways of measuring the return on our investments in developing people.
And I get it: If my bank account pays me 1% a year, I can measure it to the penny. We’ve been collectively trained to expect neat and precise ROI calculations on everything, so when it’s applied to something as seemingly squishy as how effectively people are learning in the workplace, the natural inclination is to throw up our hands and say it can’t be done. But we need to figure this out. In a world where skills beat capital, the winners and losers of the next 30 years will be determined by their ability to attract and develop great talent.
Fortunately, corporate learning & development (L&D), like most business functions, is evolving quickly. We can embrace some level of ambiguity and have rigor when measuring the ROI of learning. It just might look a little different than an M.B.A. would expect to see in an Excel model.