jannat
Active member
Published 08/2022MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 ChGenre: eLearning | Language: English + srt | Duration: 6 lectures (2h 27m) | Size: 2.86 GB
Get Expert Advice On How to start a career in Data Science
Know the right path to become a Data Scientist
Know the right Skill to master to become a Data Scientist
Know the right industry for your background
Get to know which resources to use
Get to know what mistakes to avoid
Get to know how to crack your Data Science Interviews
This is a bner level course and does not require any prerequisite
Data Science is with no doubt the no.
1 job in the whole world but starting a career in Data Science or becoming a Data Scientist that companies will like to pay huge salary is difficult.
Having the right guidance and advice can be a saver.
In this course, we talked to experts to share their own experience as well as advice on how a fresher, intermediate as well as a someone who wants to transition from one career to Data Science can do it the right way.
Experts in the course includes
1) Dr Chiranjiv Roy, PhD (One of India's Top 10 Data Scientists)
2) Ranjeev Dhumal(Data Scientist at Fractal Analytics)
3) Saniya Jaswani (Machine Learning Eeer @ IBM)
4) Kanav Anand (Data Scientist @ American Express)
5) Sajan Kedia (Data Scientist @ Myntra)
6) Suraj Shukla (Data Scientist @ Deloitte, CIMB Lab)
Learning from the experience and advice from these experts will save you tons of months and years of wasting figuring out the right path.
You will get to know
The right path to become a Data Scientist
Know the right Skill to master to become a Data Scientist
The right industry for your background
Which resources to use
What mistakes to avoid
How to crack your Data Science Interviews
etc.
Enroll now to start your Data Science career the right way
Any student who is interested in to become a Data Scientist
Anyone interested in becoming a Data Scientist but does not know how to start and where to start from
Anyone looking for career transition into the field of Data Sciecne
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