Event Phone: 1-610-715-0115

Cancellation Policy: If you cancel your registration at least two weeks before the course is scheduled to begin, you are entitled to a full refund (minus a processing fee of $50).

In the unlikely event that Statistical Horizons LLC must cancel a seminar, we will do our best to inform you as soon as possible of the cancellation. You would then have the option of receiving a full refund of the seminar fee or a credit towards another seminar. In no event shall Statistical Horizons LLC be liable for any incidental or consequential damages that you may incur because of the cancellation.

A 3-Day Livestream Seminar Taught by Edwin Dalmaijer, Ph.D.

Python is one of the most popular languages in the world. It is a general-purpose language, but also highly user-friendly. This makes Python a very powerful tool, with a relatively easy learning curve. It is also open-source and supported by a large international community of users who support each other, and continue to develop additional functionality.

In the field of data science, Python has become indispensable. It is used for quick prototyping of statistical models and machine-learning pipelines, and you can even find highly mature Python applications in production environments! It has also become a go-to language in science, from astrophysics (e.g. black hole imaging) to zoology (e.g. evolution simulation).

This course is aimed at beginners, including those who are new to programming altogether. We will start with the basics of coding, including variables, logic, loops, functions, and object-oriented programming. In addition, we will discuss reading and writing data files, how to process large quantities of data fast, and data visualization. Finally, the course will cover statistics, regression, models, and a bit of machine learning. No prior knowledge on any of these topics is assumed.

More specifically, the course will cover how to write your own functions and classes, using variables, statements, and loops. These make up the majority of code-bases, and are thus a crucial skill to master. You will also be introduced to some of the most commonly used packages: NumPy and SciPy for fast computing, Matplotlib for publication-quality visualizations, and scikit-learn for machine learning.

The course will be very hands-on. It will run through interactive notebooks in your internet browser, so you won’t have to download anything. However, we will provide advice on how to install Python and additional packages, so that you can continue using it at home and at work.

At the end of this course, you should be able to find your own way in Python. You will be equipped to handle datasets and to write full analyses. You will also be well-equipped to start deepening your Python knowledge, as this course will have introduced some of the most commonly used tools.