TDWI San Diego Seminar

Prerequisite: None

Deanne Larson, Ph.D.

DM, CBIP

President

Larson & Associates

Data manipulation and cleaning in machine learning is estimated to take more than 50% of the time allotted for a machine learning project. Python is a powerful tool that enables robust manipulation, and cleansing is also leveraged highly in Python. This course will cover topics important in handling structured and unstructured data, as well as scraping data in Python, including using key packages such as Pandas, NumPy, and Matplotlib. Participants will complete exercises to solidify understanding and build skills with the intent of finishing the course with a toolkit that can be leveraged in building Python manipulation and cleaning skills.

You Will Learn

• Programming review
• Data acquisition via APIs
• Overview of scraping and wrangling
• Cleansing for machine learning
• Leveraging Pandas
• Leveraging NumPy and Matplotlib
• Dealing with strings
• Visualizing results

Geared To

• Data engineers, data scientists, business and data analysts, project managers
• Roles that need insight into best practices and techniques related to data understanding and preparation

Laptop Setup

Students must bring their own laptop to the class.

Laptop setup is required BEFORE the conference. Instructions will be emailed to registrants prior to the event.

There is no time allotted in class for laptop preparation.