ABOUT THIS COURSE

Designed for both beginners with some programming experience or experienced developers looking to make the jump to Data Science, this course’s content can be adjusted based on student experience level with Python to include full overview of Python and programming if necessary. The course can be adjusted to be between 3-5 days, depending on desired student outcomes and student experience.

COURSE TOPICS

• Programming with Python
• NumPy with Python
• Use matplotlib and Seaborn for data visualization
• Web scraping with Python
• Using pandas Data Frames to solve complex tasks
• Use pandas to handle Excel Files
• Connect Python to SQL
• Use plotly for interactive visualizations
• Machine Learning with SciKit Learn
• and much more!

Each section of the course consists of several lectures and ends with a full project exercise. Each Machine Learning topic has a full walkthrough project and a full exercise to test comprehension.

LEARNING OUTCOMES

• Learn how to program with Python
• How to create amazing data visualizations
• How to use Machine Learning with Python

By the end of this course students will be able to:

• Comfortably program with Python
• Use Python and pandas to read data from a variety of sources (SQL, Excel, CSV, HDFS, etc)
• Use multiple libraries to create data visualizations
• Use Python’s SciKit Learn library to implement Machine Learning Models
• Understand how to use Spark to deal with big data and distributed systems

Course Audience:  Beginners with some programming experience to advanced developers looking to make the jump to Data Science.

Course Duration : 3 – 5 days depending on adjustments.

Tools Needed:  Students will need a local computer with an up to date web browser and a stable internet connection. Any recent version of Internet Explorer, Google Chrome or Mozilla Firefox will work