Python is important for software development. While there are more powerful languages (e.g. Java), Python gets a lot of different things right, and right in a combination that no other language has done so far. It's possible to write obfuscated code in Python, but the easiest way to write the code is almost always a way that is reasonable terse, and more importantly: code that clearly signals intent. If you know Python, you can work with almost any Python with little effort.
Python is a very high-level, general-purpose language that is utilized heavily in fields such as data science and research, as well as being one of the top choices for general-purpose programming for programmers around the world. It features a wide number of powerful, high- and low-level libraries and frameworks that complement its delightful syntax and enable Python programmers to be creative. This course introduces some of the most popular libraries and frameworks and goes in-depth into how you can leverage these libraries for your own high-concurrent, highly-performant Python programs. We'll cover the fundamental concepts of concurrency needed to be able to write your own concurrent and parallel software systems in Python. The course will guide you down the path to mastering Python concurrency, giving you all the necessary hardware and theoretical knowledge.
Computational computing can be a complex topic. How to perform various mathematical functions in code isn't straight forward. With Python's Scipy library, we'll walk through a number of examples showing exactly how to create and execute complex computational computing functions. The course starts with an explanation of what Scipy is. Then we see how to install it.
This is a course intended for beginners interested in applying Python in Bioinformatics. We will go over basic Python concepts, useful Python libraries for bioinformatics/ML, and going through several mini-projects that will use these Python/ML concepts. These mini-projects include a sequence analysis (with no libraries) Python example, a Python sequence analysis example using libraries, and a basic Sklearn Machine Learning example.
Python By Example will help you learn the Python programming language from the ground up. We will be using Python 3 in this course. It is currently split into four parts. In part one, you will learn how the basic building blocks of Python, such as strings, lists, dictionaries and tuples. You will also learn how to handle exceptions, create list comprehensions, make functions, classes, etc.