I have a basic question, mainly about the similarities and differences between Data Science and Machine Learning. When I put it up on StackOverflow, someone want to delete my post because he pointed out that my question is a question unrelated to programming. Fine. And then I went to this site and I put forward the question, some people voted down it again. After that I entered Computer Science but found there was not the label of data science on that at all. So I am wondering where can I post it so as to get kindly answers?
On top of that, I have a suggestion, could you Stack Exchange provide suggested sites to those who posted inappropriate questions or move the posts to correct sites automatically so that they do not have to find one from overall 175 sites? This is definitely an inefficient process and a pure waste of time.
This is my question (I am not going to ask here, please do not say I am out of topic).
Recently I took part in an online project about Data Science, I learned some frameworks such as Pandas, Numpy and Sklearn, some basic knowledge, like kNN, Linear Regression, Regularization, Logistic Regression and Classification/Regression Trees. Although I have finished the course, I am still having a hard time writing my resume for an application of MS, describing the relationship between what I have learned with Artificial Intelligence, or Machine Learning. Since I am going to pursue the field of AI, how can I figure out the similarities between DS and ML/AI so as to express my previous work?
Besides, A couple of days ago, I glanced over Coursera and found the Machine Learning course provided by Professor Andrew Ng is extremely similar to my previous course except Neural Networks. My course did not cover that. So I am confused about what are the differences between DS and ML/AI.
In a nutshell, there are three questions, the link between what I have learned with Machine Learning and the similarites and differences between DS and ML/AI. I hope that my questions do not make you overwhelmed.