What is Data Science?
This is an artificial intelligence and machine learning course, so one might question: why are we interested in data science?
"Data science is the field of study that combines domain expertise, programming skills, and knowledge of mathematics and statistics to extract meaningful insights from data. Data science practitioners apply machine learning algorithms to numbers, text, images, video, audio, and more to produce artificial intelligence (AI) systems to perform tasks that ordinarily require human intelligence. In turn, these systems generate insights which analysts and business users can translate into tangible business value." - DataRobot
The diagram above split data science into three main domains: hacking skills, math & statistics knowledge and substantive expertise. The graph has been created by Drew Conway. Hacking skills refer to programming skills, substantive expertise refers to the domain knowledge that a data scientist possesses of the field or topic that is being analysed. In the very core of data science, one can find computer science and statistics. This interdisciplinary process extracts insights from raw data using various automated techniques.
It can be said that data science is the field that applies machine learning. When you land your first position in a machine learning related job, there is a chance that the job title will be 'data analyst', 'data scientist', 'data engineer', 'machine learning engineer' or similar.
Task
Using your favorite search engine, try your best to find answer to at least these questions:
- What are the must-have skills for a data scientist?
- What are the key differences between these two job roles: data scientist & data engineer.
- What is the relation between data science and machine learning and artificial intelligence?
You should spend at least 30 minutes in this process. Try to find a debate. For example, does someone claim that data science is just rebranding of something that already exists?