Road map of data science
Data scientists collect, analyze, process raw data to get insights from it. There is a
increase of 62 % in demand in current year. Average salary is 10,00,000. And in coming
future this job will do fantastic. Data scientist will become an advantage for more earning.
There are some personal tips and tricks which I have used. Statistics is the ultimate
resource for this , from where to learn statistics ? The 1st you should know is Statistics.
Then you have to learn real meaning of dy/dx. After this, you should learn about
distribution and Optimisation. I 'll give you a target of 3 months and you'll learn within 3
months. You 'll get to know optimisation and normal distribution from Hines.
Optimisation and gradient descent of dy/dx, geometric meaning of this I have told in my
playlist. Then you have to learn about Numpy and Pandas. Matplotlib and Seaborn are a
library.
Matplotlib and Seaborn are very good for data visualization. For data visualization, start
with Matplot lib , and then keep it as an option. In excel, if you want to plot x and y, then
you do n't have to use this. As a data scientist it will be very useful to you when you will
use different type of algorithms. You should know database. What is this database ? You
can learn mySQL. If you already know about NoSQL database, than any one database you
should know. And you can know how to connect this database to python. There is
pymongo to connect with mongo db. If your machines are powerful, than your biggest
data can be handled here only. There is Tableau and Hadoop. So its optional. Feel free if
you want to ignore. But I am telling that when you start solving problems of data science.
At that time you can go with this. That does'nt mean you have to learn this , but atleast
you can give it a try.
Machine learning is not a big thing as people think How I will do in so less time. You do
n't have to research in machine learning You can do it you just need to learn this much
That you can work on data What company want if you can give insights , If you can solve
problem then they do not care what you know in what depth. I have made a video for
Linux learn Linux in one video. In which I have shown you basic Linux which you need
So you can watch that in less time more Linux. After this , Other things you need to learn
as Linux and git. In this video I have only teach to run VMs and all Learn to do SSH in
machine that 's it I have taught' There are no more learning resources if you think there
are many things to learn then no This much is it. Statistics, programming, ML , ML , DL
Not much just shown that much If you are able to see external tools of data visualisation
then do see else learn to work in excel. Excel is compulsory to learn graph Sum and the
function of concatenation and everything you learn. Linux and git , see one video of each
of them in external courses.
your link of GitHub trending repository Where you will find all the trending repositories
of GitHub. You can see and can download the code to execute. Once you learn Python this
will be more easy for you Python and LINUX , Linux is not much useful It works on
Windows machine too but GitHub trending repositories Execute them by downloading
Then there is a website named paperswithcode the latest research Is given with code
means source code in GitHub link. A person of IIT, NIT, and tier 3 then people tend to
look once to IIT person. But listen to the whole point I have n't finished It does n't mean
Data scientists collect, analyze, process raw data to get insights from it. There is a
increase of 62 % in demand in current year. Average salary is 10,00,000. And in coming
future this job will do fantastic. Data scientist will become an advantage for more earning.
There are some personal tips and tricks which I have used. Statistics is the ultimate
resource for this , from where to learn statistics ? The 1st you should know is Statistics.
Then you have to learn real meaning of dy/dx. After this, you should learn about
distribution and Optimisation. I 'll give you a target of 3 months and you'll learn within 3
months. You 'll get to know optimisation and normal distribution from Hines.
Optimisation and gradient descent of dy/dx, geometric meaning of this I have told in my
playlist. Then you have to learn about Numpy and Pandas. Matplotlib and Seaborn are a
library.
Matplotlib and Seaborn are very good for data visualization. For data visualization, start
with Matplot lib , and then keep it as an option. In excel, if you want to plot x and y, then
you do n't have to use this. As a data scientist it will be very useful to you when you will
use different type of algorithms. You should know database. What is this database ? You
can learn mySQL. If you already know about NoSQL database, than any one database you
should know. And you can know how to connect this database to python. There is
pymongo to connect with mongo db. If your machines are powerful, than your biggest
data can be handled here only. There is Tableau and Hadoop. So its optional. Feel free if
you want to ignore. But I am telling that when you start solving problems of data science.
At that time you can go with this. That does'nt mean you have to learn this , but atleast
you can give it a try.
Machine learning is not a big thing as people think How I will do in so less time. You do
n't have to research in machine learning You can do it you just need to learn this much
That you can work on data What company want if you can give insights , If you can solve
problem then they do not care what you know in what depth. I have made a video for
Linux learn Linux in one video. In which I have shown you basic Linux which you need
So you can watch that in less time more Linux. After this , Other things you need to learn
as Linux and git. In this video I have only teach to run VMs and all Learn to do SSH in
machine that 's it I have taught' There are no more learning resources if you think there
are many things to learn then no This much is it. Statistics, programming, ML , ML , DL
Not much just shown that much If you are able to see external tools of data visualisation
then do see else learn to work in excel. Excel is compulsory to learn graph Sum and the
function of concatenation and everything you learn. Linux and git , see one video of each
of them in external courses.
your link of GitHub trending repository Where you will find all the trending repositories
of GitHub. You can see and can download the code to execute. Once you learn Python this
will be more easy for you Python and LINUX , Linux is not much useful It works on
Windows machine too but GitHub trending repositories Execute them by downloading
Then there is a website named paperswithcode the latest research Is given with code
means source code in GitHub link. A person of IIT, NIT, and tier 3 then people tend to
look once to IIT person. But listen to the whole point I have n't finished It does n't mean
