Learn how to create programs with Python, the definite programming language for data science.
Python is considered to be a famous language with a simple syntax and a series of powerful libraries.
While it easier than other languanges for beginners to learn, it is widely used in multiple organizations such as Wikipedia, Google, Yahoo!, Netflix, CERN and NASA, among many others.
This course not only introduces the fundamentals of Python and problems solving such as data types, control flow, functions, data structures but also extends to special issues such as object-oriented programming, I/O handling, exceptions, regural expressions, geospatial applications and data managements.
All the examples and assignments given in this course are draw from real life projects giving the full picture of the usage of programming.
Anyone interested in, planning to learn, or already learning programming and want to add an asset on their CV or to enhance the effectiveness of programming on their job. University students who have difficulties on keeping up with programming are especially encouraged to take the course.
No prior knowledge of programming is required.
We enlist industry experts to plan, author and review our syllabus. It will guide you from fundamental concepts all the way to full scale implementations. It is constantly updated, and you get lifetime access.
Learn the absolute basics in Python: variables and assignments, using expressions, manipulating numbers and strings, how to indicate comments in code, and so forth.
Python provides a complete set of control-flow elements. Learn everything about conditionals, loops and exceptions handling.
A function is a block of code that provide better modularity for your application and a high degree of code reusing. Learn about function definition, function calling with or without parameters, lambda expressions and decorators.
Python supports the famous Object-Oriented Programming (OOP) paradigm. You will learn the constructs available in Python to use OOP in your programs.
Learn how to efficiently use the four major Python complex data types. With lists, tuples, sets and dictionaries you will be able to store data for any real-world scenario.
Modules are used to organize larger Python projects. The Python standard library is split into modules to make it more manageable. Programs are a collection of modules that are executable by the operating system.
Working with files involves two things: basic I/O like opening, reading or writing a file and working with the filesystem like creating or renaming a file or a dictionary.
You will learn some more advanced features, which you may not use every day but which are handy when you need them, like regex expressions, package creation and extending Python types.