This topic contains 3 replies, has 4 voices, and was last updated by ravali 1 year, 2 months ago.
- 12/20/2016 at 12:00 am #5754ananthMember
The fact that you are doing a CS course in Engineering is already a good start for a career in data analytics.
Data Analytics is a highly competitive field currently and to make your mark there, I would suggest you to do a masters in Data Analytics from a good University. You still have two more years to complete your CS degree, so I would suggest you to look into online Data Analytics related courses in the meanwhile(There are some really good online courses for free from coursera and edx that you can take a look at).
Further, Data Analytics is a broad field, once you figure out the overview of the field, you would need to find out which part of Data Analytics you are interested in and what you would like to specialize in. In the next two years, you may also need to prepare for GATE if you are planning on doing the masters in IIT or you can prepare for GRE if you want to do the master abroad.
- 12/20/2016 at 12:00 am #978Darshil ShahMember
I want to develop career in data analytics, can you please suggest me some ways through which I can start the career in data analytics from scratch.
P.S.- I am currently in 2nd year of CS Engineering
- 12/21/2016 at 12:00 am #5772Shraddha GoelMember
The first and foremost is understanding if you have problem solving skills using data.Second set of skills necessary are domain or business understanding. Since mainly you will be solving business problems you need to understand the driver of that business or industry well and the important metrics in that business or domain. Third set of skills would be the numerical and technical ones. You need o be decent at math and stats, the applied kind and not the theory part only.These are skills that can be learnt through short online courses at various institutes some of them being
Books which could be helpful are:, , etc.
1. Statistics for Management by Richard Levin and David Rubin
2. SAS Programming by Example by Ron Cody
3. Data Mining Techniques by Michael Berry and Gordon Linoff
4. Data Mining Cookbook by Olivia Parr Rud
5. Predictive Data mining by Sholom Weiss
Since you are young and have time, start with these basic learnings and then move forward. All the best 🙂
- 07/18/2019 at 3:49 pm #1500578ravali
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