Generally, Machine Learning is referred to as somewhat training a machine on some labeled data and then testing its decision power on some testing data. While unsupervised learning is defined as "machine learning with unlabeled data". How is the unsupervised learning is the class of machine learning when there is no training included?
Yeah, you are right in both the definitions. But we may say that unsupervised learning doesn't include any sort of training OR its a "run time machine learning". It just starts clustering data using some technique and whenever a new instance comes, that has been classified to one of the clusters. You can better understand it considering K-means (best and easy for dummies to understand unsupervised clustering).
What do people expect from you being a computer scientist?
I, personally, presume that the computer science is the broadest field a scientist can have. Being a computer scientist, you are supposed to have knowledge of a number of computer courses. Of course, being a MS Office expert, is not being a scientist. Rather you are supposed to know back end techniques such as algorithms, databases, operating system as well as extensive programming techniques.
What is the difference between Artificial Intelligence and Machine Learning?
Well, it's a much frequently asked question by the students of the domain. Unfortunately, the two terms have been mixed too much now a days. Precisely speaking, the similarity between the two is analogue to how are Algebra and Math related to each other. Artificial Intelligence (AI) is basically a broader concept encapsulating Machine Learning (ML). ML is just related to how a machine can learn or what the machine learning is one BUT AI is something to use ML for different intelligent tasks. AI includes knowledge reasoning and planning tasks as well.