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 Remote Seminar Taught by Jason Anastasopoulos, Ph.D.

Python is rapidly becoming the preferred language of data scientists in both industry and academia. It’s used by Google, Facebook and other tech giants to perform data analysis and run machine learning algorithms that can handle hundreds of thousands of terabytes of data per day.

Python can be used for:

• Storing and analyzing large and small datasets.
• Web scraping and data collection using APIs.
• Beautiful data visualization.
• Natural language processing and text analysis.
• General machine learning.
• Deep learning.
• Image analysis and much, much more…

This seminar is an intermediate course on statistical computing with Python. The goal is to get participants to learn about advanced data analysis and visualization applications of the Python language.

By the end of this seminar you will be able to do:

• Natural language processing: Grasp the basics of natural language processing and sentiment analysis.
• Advanced data visualization: Advanced Python plotting functionality. This includes: plotting geospatial data and plotting text data.
• Big data analysis and inference: Learn how to deal with massive data in Python.
• Statistical inference: Perform data analysis and basic statistical inference with Python, including: GLMs, ANOVA and hypothesis testing.
• Web-scraping: Scrape and parse semi-structured data, including HTML, XML, and JSON.
• Databases: Create and extract information from SQL and MongoDB databases with Python.