Data Science
Aayushi Verma | Data Scientist | EdGE Networks Pvt LtdWhat is Data Science?
A Career in Data Science is very intriguing. One should first understand What a Career in Data Science entails before investing time and effort to figure out How to start a Career in Data Science. It is best to learn about Data Science from a real professional, this is akin to getting it from the horse's mouth.
Data Scientist Aayushi Verma invested 5 years in Data Science. Data Scientist Aayushi Verma describes Data Science as:
Data science is a multidisciplinary blend of data inference, algorithmm development, and technology in order to solve analytically complex problems. At the core is data. Troves of raw information keep streaming in and stored in enterprise data warehouses as there is much to learn by mining it.
How Data Scientist Aayushi Verma got into Data Science?
After completing my M Tech in Data Analytics, I joined a start-up in Delhi as a Data Scientist. After that I have worked for few companies as a Data Scientist, in 2018, I joined EdGE Networks Pvt Ltd as Data Scientist. I have also published few Research Papers in Journals like IEEE & Springer.
Data Scientist Aayushi Verma's Talk on Data Science |
|
Starts with what is: | |
1) | Data Science |
Next, it covers Education. We all know that only 10% of what is taught in Data Science is actually used in real life. The Education section of the Talk clearly explained what is the 10% needed in Data Science. It defines Education in terms of following items for Data Science: | |
2) | Mathematics |
3) | Programming Languages |
4) | Domain Knowledge |
Then, the Talk focuses on the most important component that is Skills. 90% success in Data Science depends on Skills. It is crucial to understand these. It defines Skills in terms of following items for Data Science: | |
5) | Reading |
6) | Analytical & Logical Thinking |
7) | Data Exploration |
Data Science has an interesting list of Positives. The Talk goes through this list of Positives of Data Science: | |
8) | High Paying Profession |
9) | Huge Demand |
10) | Positive Social Impact |
11) | Interesting Job |
It is important that one develops a fair understanding of the Challenges of Data Science: | |
12) | Lack of High Quality Data |
13) | High Expectations |
14) | Interpretability Issues |
In the final section of the Talk, Aayushi Verma talks about How a day goes in a Career in: | |
15) | Data Science |
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How to get into
Data Science?
If you are want to get into Data Science, start by investing in a Career Plan.
The 14 hour process, guided by a LifePage Career Advisor, will help you introspect and check whether your interest in Data Science is merely an infatuation or is it truly something you wish to do for the rest of your life.
Next, your Career Advisor will help you document how you can get into Data Science, what education and skills you need to succeed in Data Science, and what positives and challenges you will face in Data Science.
Finally, you will get a Career Plan stating which Courses, Certifications, Trainings and other Items you need to do in the next 7 years to become world’s best in Data Science.
LifePage Career Plan
14 hour personalized guidance program
Your LifePage Career Advisor facilitates your guided introspection so that you systematically explore various Career options to arrive at a well thought out Career choice.
Next: your Advisor helps you figure out how you will get into your chosen Career and how will you develop the skills needed for success in your Chosen Career.
LifePage Plan will not stop at saying "to become an Architect study Architecture". It will guide you on which Certifications, Trainings and Other items you need to do along with your Architecture education to become the world's best Architect.
Links for this Talk
LifePage Career Talk on Data Science
[Career]
https://www.lifepage.in/careers/data-science-1
[Full Talk]
https://lifepage.app.link/20181130-0008
[Trailer]
https://www.youtube.com/watch?v=rdNZoyFLgI4
(Aayushi Verma, Data Scientist, Edge Networks, Data Science, Natural Language Processing, NLP, Artificial Intelligence, Data Analytics)
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