1  R installation [for Windows]   (6m39s,2010)        https://www.youtube.com/watch?v=ZoPJGmpYJzw
2  R installation [on a Mac]      (5m59s,2014)        https://www.youtube.com/watch?v=Ywj6yNfc5nM
3  How to install Anaconda on Windows(v12k,s,t4:29)   https://www.youtube.com/watch?v=GEYK1dlDqgU
4  How to install Python on Mac OS(v169k,s254k,t7:39) https://www.youtube.com/watch?v=TgA4ObrowRg&t=2s
5  Install Anaconda Python On Mac (v30k,s191,t3:43)   https://www.youtube.com/watch?v=V6ZAv7hBH6Y
6  install Python 3.9.1 Windows (v108k,s9k,t3:54)     https://www.youtube.com/watch?v=IDo_Gsv3KVk
7  What are Python modules?      (t6:35)              https://www.youtube.com/watch?v=XcfxkHrHTVE
8  Modules in Python Explained    (t15:03)            https://www.youtube.com/watch?v=1oFneicTaII
9  For loops in Python are easy    (t5:05)            https://www.youtube.com/watch?v=KWgYha0clzw
10  Learn Matplotlib in 6 minutes   (t6:42)            https://www.youtube.com/watch?v=nzKy9GY12yo
11  How to search for code in GitHub(v6k,s656,t2:06)   https://www.youtube.com/watch?v=K4FatbcgPIU
12  What is Machine Learning in Finance (t1:59)        https://www.youtube.com/watch?v=A5_6fY9JNc4
13  PCA main ideas in only 5 minutes!!!  (t6:04)       https://www.youtube.com/watch?v=HMOI_lkzW08
14  K-means clustering   (t8:30,v1.4m,s34k)            https://www.youtube.com/watch?v=4b5d3muPQmA
15  Supervised vs. Unsupervised Learning  (t7:07)      https://www.youtube.com/watch?v=W01tIRP_Rqs
16  Reinforcement Learning from scratch   (t8:24)      https://www.youtube.com/watch?v=vXtfdGphr3c
17  Neural Network In 5 Minutes   (t5:44)              https://www.youtube.com/watch?v=bfmFfD2RIcg
x<-readLines("http://datayyy.com/fmr/starter/watchVideos.txt")
x2<-x[grep("http",x)]
x3<-sub("^.*http","http",x2)

generate RData for a list for datasets
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a<-data()
write(unlist(a),file="c://temp/t.txt")
x<-readLines('c://temp/t.txt')
n<-length(x)
x2<-x[2:(n-2)]

k<-grep("C:/Program",x2)

n3<-length(k) # [1] 104

x3<-x2[-k]
x4<-matrix(x3,n3,3)
df<-data.frame(x4[,1],x4[,3])
colnames(df)<-c("Package","Name")
save(df,file="c://temp/datasets.RData")
/////////////////////////////////