IS it TOUGH to be a DATA SCIENTIST? NO , it is not
Data Science is Not Rocket Science. But once a data scientist you have to keep learning every day.
Master R and Python basics along with statistics basics.
Then learn Machine Learning.
- Text Mining Basic and Topic Modeling.
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Time Series.
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Then learn Deep Learning, ANN, CNN, RNN , LSTM.
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Computer Vision.
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Speech Recognition.
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Chatbots.
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Blockchain.
you can learn this from internet for free. Dont get confused or insecure to pay lacs of rupees or thousands of dollars to institutes that give you certificates that are not recognized by corporations
Intro to R https://lnkd.in/e65KfmX
Intro to Python https://lnkd.in/eJ-F3c7
Intro to Machine Learning https://lnkd.in/eeHdi_t
Here is one more free “kernel”, but in colab format: https://github.com/noahgift/functional_intro_to_python#safari-online-training–essential-machine-learning-and-exploratory-data-analysis-with-python-and-jupyter-notebook
Is KAGGLE a website only for super human data scientists? NO NO NO
You can be a kaggler very easily-
1) Understand how kernels function especially input file and output submission- The best is to use Notebook method not script method of using code
2) Have basic knowledge of EDA and Data Viz in either R or Python ( if you dont know that EDA means exploratory data analysis you can start learning – from Kaggle KERNELS itself
3) Have basic knowledge of Machine Learning Algorithms (and how to apply ) and how to compare Area under Curve (AUC)
4) Deep Learning is advanced and for Python preferably
5) Practice one hour a day. Kaggle is like a gym for the brain if you do this for a year, see where your career zooms.
And one more thing- cross port your code on Github
I am sure there are better kernels, but you can find them out yourself, and best of all they are free. tip- Number of votes often points out to a better more popular kernel
R Basics Here https://www.statmethods.net/ and https://www.datacamp.com/courses/free-introduction-to-r
basic statistics https://www.slideshare.net/ajayohri/statistics-for-data-scientists
and free SAS learning from SAS itself https://www.sas.com/en_us/learn/academic-programs/resources/free-how-to-videos.html
Interview Questions https://www.edureka.co/blog/interview-questions/top-data-science-interview-questions-for-budding-data-scientists/
Python basics here https://cognitiveclass.ai/courses/python-for-data-science/ and http://www.statisticsviews.com/details/feature/8868901/A-Tutorial-on-Python.html
(Free )Kaggle kernel + IBM Cognitive + edx + Kaggle contest + hackathon > certificate from paid private company ???
40 hours to gain a certificate for X dollars versus 40 hours on Kaggle for free. Which will give you better skills. What will get you a job – skills or certificates.
When we interview data scientist freshers we always have a coding round as the first step. Certificates from private institutes dont matter regardless of how long or how expensive they are
I have been asked why I write these articles on free resources on data science, what is my agenda and why not let things be.
Well, short answer, if you charge thousands of dollars for content which can be free, and force young people in debt and indulge in predatory pricing, then someone needs to expose these merchants of data science certificates
Someone asked why I charge for my 3 data science books. I write books, publisher sells them and gives me 13% of royalty. The books are 1/10th of price of a course.
Most importantly I write books for academic credentials and because I love writing (as seen by my extensive blogging on https://decisionstats.com/decisionstats-org/ (writing books is a great way to share knowledge in my opinion but takes a long time so writing a blog tutorial or kaggle kernel or github code is faster
I still do guest lectures- but in all cases I am not responsible for students paying too much and I balance this by my evangelizing free resources that would be students are completely unaware of.
These free resources are often updated more than the curriculum of courses by institutes and they are often easy to understand
As the man said- Money for nothing and my MTV
http://www.youtube.com/watch?v=lAD6Obi7Cag
