Python and Time Series Forecasting

“We are all interested in the future, for that is where you and I are going to spend the rest of our lives.” — Woody Allen. Every business in the world is interested in estimating future conditions in order to take the best decisions, we face questions like: What are going to be my turkey sales next Thanksgiving? Or How is the temperature expectation for this winter? Many statisticians have worked in this field from a scientific perspective to minimize the risk of a prediction. In this course, we will learn the most common techniques to forecast time series with the amazing open software Python. It will be a mix of basic statistic concepts with practical exercises which allow to explore the most useful libraries and coding lines. 

This is an instructor-led course to introduce you to the Python programming language with Time Series Forecasting. Python is one of the most popular programming languages used in industries ranging from gaming to finance. Python is an interpreted, object-oriented high-level programming language, which has recently become a popular tool in industry and in academia.

• The Python programming language is used by business analysts, software developers to analyze data and to create captivating yet insightful data visualizations
• The Python programming language can be used for developing both desktop, web and mobile applications.
• Python can be used for creating Windows, UNIX and Mac applications, from simple console and web-based to
• elaborate graphic interfaces for video games.
• Also, you can use Python for developing complex scientific and numeric applications for Machine Learning, Robotics and Finance

• Introduce students to the basics of Python.
• Provide students with the hands-on Python programming building block skills needed to develop applications
• Create working Python scripts following best practices
• Use python data types appropriately
• Read and write files with both text and binary data
• Search and replace text with regular expressions
• Get familiar with the standard library and its work-saving modules
• Create "real-world", basic level professional Python applications
• Know when to use collections such as lists, dictionaries, and sets
• Understand Pythonic features such as comprehensions and iterators
• Write robust code using exception handling

This course is a 50% hands-on labs to 50% lecture ratio with engaging instruction, demos, group discussions,

labs, and project work including a capstone assignment.

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