Course overview
- Provider
- Coursera
- Course type
- Free online course
- Level
- Intermediate
- Deadline
- Flexible
- Duration
- 11 hours
- Certificate
- Paid Certificate Available
- Course author
- Julian McAuley
-
Develop data strategy and process for how data will be generated, collected, and consumed
Load and process formatted datasets such as CSV and JSON.
Deal with data in various formats (e.g. timestamps, strings) and filter and “clean” datasets by removing outliers etc.
Basic experience with data processing libraries such as numpy and data ingestion with urllib, requests
Description
This is the first course in the four-course specialization Python Data Products for Predictive Analytics, introducing the basics of reading and manipulating datasets in Python. In this course, you will learn what a data product is and go through several Python libraries to perform data retrieval, processing, and visualization. This course will introduce you to the field of data science and prepare you for the next three courses in the Specialization: Design Thinking and Predictive Analytics for Data Products, Meaningful Predictive Modeling, and Deploying Machine Learning Models. At each step in the specialization, you will gain hands-on experience in data manipulation and building your skills, eventually culminating in a capstone project encompassing all the concepts taught in the specialization.
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