When buying any of my courses, I also give you free coupons to the rest of my courses. Just send me a message after enrolling. Pay one course, get 5!!
This course is intended for students aiming to learn Python, with no previous programming experience. After this course, the student will have a general overview of the Python programming language. In order to master Python, the student will need more practice, and more specific training in some areas. Nevertheless, with this course, the student will be familiar with most elements in the Python environment.
We start by explaining how to install and set up the Python environment, and then how to define variables, loops, numbers, and functions. We then review the basics behind Numpy, which is a critical package for mathematics in Python. We then explain the fundamental elements of the Python standard library such as pulling data from the web, storing persistent data, working with decimal numbers, and creating visual applications. Because analysing raw numbers is sometimes a complicated task, we also show how to leverage the powerful Matplotlib package for creating plots. We then review one of the most important elements of Python: Classes. We start with a very simple class, and we then build more complicated ones explaining different aspects.
People working with Python, will most likely need to build applications processing data. And because Python is the most used statistical and machine learning programming language, we finally review the data science packages triad in Python: Pandas (data processing), Scikit-learn (machine-learning), and Statsmodels (statistics). The idea of this part is to introduce the basics behind these packages.
At the end of the course, the student should be able to:
- Code his own Python programs
- Define and use classes
- Use data structures
- Work with dates, strings, Numpy arrays, numbers
- Write and read files in Python
- Leverage the elements in the standard library
- Understand the basics behind Pandas, Scikit-learn and Statsmodels
- Load data via Pandas, pre-process it, and model it using Scikit-learn and Statsmodels
You will find lots of exercises and quizzes!
We try to keep this course as updated as possible, and the student is welcome to formulate questions, as we try to answer them promptly.