I am a great fan of Quora.com. I spend sometime, everyday to check out what’s going on on my area and related areas. Past two days, I have been intersecting with some data scientist questions. I would like to plot some answers that I loved and found very useful.
But before starting to say these are necessary to become a data scientist, I would like to define a data science and data scientist:
Type A is data scientists who are working mostly on analysis part.
Type B is a data scientist who are working mostly on building part.
How we can be one of the type that we discussed above?
- Math, Algorithms and Databases:
- Calculus-3, Linear Algebra, Algorithms, Database Systems
- Probability and Statistics
- Data Analysis
- R programming
- Scientific Python
- pandas library
Acquire and Scrub Data:
- DFS and Databases:
- Data Munging:
Filter and Mine Data:
- Data Analysis in R:
- Exploratory Data Analysis:
- Data Mining, Machine Learning;
Represent and Refine Data:
This skill is developed through experience working in an industry. Each dataset is different and comes with certain assumptions and industry knowledge. For example, a data analyst specializing in stock market data would need time to develop knowledge in analyzing transactional data for restaurants.
Combining all the above:
Apply the knowledge:
Thanks tofor this amazing answer on Quora.