6 reasons why students of Science and Engineering must learn Python

One of the main reasons for the Python becoming so popular is that it has several powerful libraries and modules that may solve numerous professional application problems. The uses of Python in the Engineering and Scientific field are immense, and learning the language as a student, even before the start of a career can be extremely beneficial. For instance NumPy and SciPy library, one can solve mathematical problems. BioPython can solve biological problems. Here are 6 ways Engineering and Science students will benefit from learning Python:

1. Analyzing Bioinformatics files: Python owns certain special libraries in academic fields like astronomy, biology and medicine. There is an international association of developers of Python tools called the Biopython that are used for computational molecular biology. The capabilities are aplenty and they include the analysis of bioinformatics files into data structures that can be utilized by Python like processing common online database codes of bioinformatics.
2. Using Python for the most important biology object of sequence: Making use of function within Python to create sequence object. This is possible through this object in order to view the attribute of sequence object. The result for this is a sequence object composed of alphabets. This means that it is yet to designate a protein sequence or DNA.
3. Mathematical function of generating dataset: A predefined function can be used to generate dataset that is an arithmetic progression from PI. One can then calculate the sine and cosine values and make use of a function in the pylab module for plotting and adding labels and titles. Sin() and Cos() are fundamental functions in math. In order to carry out complex operations, for example a fast Fourier to transform into a dataset, one can use corresponding functions in SciPy. Maths is used in social sciences and humanities, this way Python finds way more uses, even apart from pure Mathematics.
4. Image and audio processing: Python contains an image processing library called the PIL. This package allow fundamental capabilities of image processing like rotating image, changing size, image enhancements and formats. OpenCV is an image processing library with even better performances. Skimage is another great image processing toolkit for serving SciPy. Engineering students sure have immense use for this in their projects.
5. Language Development: Python’s module and design architecture has influenced the development of a number of languages. The Boo language makes use of syntax, object model, indentation and syntax that are similar to Python. Syntax of other languages like Coffeescript, Swift of Apple, OCaml and Cobra, all are very similar to Python.
6. Prototyping: Apart from being easy and quick to pick up, Python also has the advantage of being open source and free with huge support from a large community. This is what makes it a preferred choice for development of prototypes. The ease of extensibility, scalability and agility, along with ease of refactoring code associated with Python allows for faster development from the prototype.

Ever since Python came into existence in the year 1989, it has grown to become a part of a plethora of desktop based, web-based, scientific, graphic design and computational applications. Python is available for Mac OS, Linux, UNIX, and Windows as it offers the ease of development for enterprises. IIHT offers Python courses in its Programming Stack, Big Data Development Stack and Artificial Intelligence and Machine Learning Stack! Each of these Python courses is taught in respective contexts allowing students to prepare for their career well in advance even while pursuing their graduation. Get in touch with IIHT to know more!