Why is Python?

'Cause, it's powerful...and fast; plays well with others; runs everywhere; is friendly & easy to learn; is open.

Python’s elegant syntax and dynamic typing, together with its interpreted nature, make it an ideal language for scripting and rapid application development in many areas on most platforms. 

Has best support of AI libraries - matplotlib, numpy, scipy, scikit-learn and tensorflow...

~ pythonorg

What is Python?

Python is an interpreted (executes the program directly without previously compiling into machine-language instructions), interactive (writing parts of a program while it is already running) and multi-paradigm (meta, generic, imperative, reflection, structured and object-oriented) high level programming language.  

~ Wiki

Why to study Algorithms, when memory is inexpensive?

Computers would be fast, but they are not infinitely fast. And memory would be inexpensive, but it is not free. Computing time is therefore a bounded resource, and so is space in memory. One should use these resources wisely, and algorithms that are efficient in terms of time or space would help one to achieve that.

Also, having a solid base of algorithmic knowledge and technique is one characteristic that separates the truly skilled programmers from the novices. With modern computing technology, one can accomplish some tasks without knowing much about algorithms, but with a good background in algorithms, one can do much, much more.

What is a Data Structure?

A Data structure is a way to store and organize data in order to facilitate access and modifications. Each, among all the existed, has it's strengths and limitations, which are to be understood before using any - No single data structure works well for all purposes.

What is an Algorithm?

An Algorithm is a sequence of computational steps (to reorder set of numbers, say for an instance) that transform the input ({6, 2, 5, 1, 4, 3}) into the output ({1, 2, 3, 4, 5, 6}).

OpenGL client-server Model

OpenGL is also designed to work with X Window System, wherein, multiple computers are connected to one another via network and the computer that displays the graphics you create might not be the computer that runs your graphics program. In which case, the computer on which your program runs and issues OpenGL drawing commands is called the client and the computer that receives those commands and performs the drawing is called the server. OpenGL programs can work across a network even if the client and server are different kinds of computers as the protocol for transmitting OpenGL commands is always the same. 

If an OpenGL program is not running across a network, then there must only be one computer and is both the client and server.

GLU

OpenGL Utility Library is more sophisticated, built on top of OpenGL (which otherwise allows you to build your desired model up from a small set of geometric primitives - points, lines and polygons) that provides high-level interface for describing relatively more complicated models of 3D objects - automobiles, parts of the body, airplanes, or molecules besides setting up matrices for specific viewing orientations and projections, performing polygon tessellation and rendering surfaces. 

AI vs Machine Learning vs Deep Learning

Artificial Intelligence - Human Intelligence exhibited by Machines.

Machine Learning - An Approach to Achieve Artificial Intelligence.

Deep Learning - A Technique for Implementing Machine Learning.

Artificial Intelligence is a generalized form of Machine and Deep Learning and check this incredible post for detailed information.

Succinctly, Deep Learning is-a Machine Learning is-a Artificial Intelligence.

Deep Learning

Deep Learning extends (IS-A a type of) Machine Learning by adding cascade of layers to efficiently exercise data patterns before predicting the outcome to the closest possible, which lead to some scenarios better than humans.

Today's driver-less cars do use this mechanism underneath.

Machine Learning

Machine Learning extends (IS-A type of) Artificial Intelligence (AI) by incorporating algorithms - are often categorized as supervised and unsupervised - into computers with an ability to learn without being explicitly programmed when exposed to the new data.