Data Science Master Class 1

Subject code: MA5851:03 

Data Science is a field that is transforming society by finding application in essentially all domains from business, to science and healthcare. It is constantly evolving with new techniques in mathematics, statistics, machine learning and computation/data manipulation continually emerging to extract knowledge and value from data. The Data Science Master Classes will bring in leaders in the field to report recent advances in data science techniques and/or applications of data science. Specifically, this master class will explore natural language processing (NLP), WebScraping and API’s to harvest data with python and explore the data science workbench approach to managing production pipelines of work that can be re-used in different data science projects.

It is a two-part subject, you must complete Master Class 1 before enrolling into Data Science Master Class 2.

Software platform: SAS exclusively 


Learning outcomes

  • Understand and apply new data science skills, knowledge and techniques to solve problems in data science using natural language processing (NLP).
  • Apply data science skills, knowledge and techniques to solve problems in data science NLP projects with a focus on web scraping.
  • Understand how to deploy data science projects into production pipelines.
  • Communicate effectively the results of the project as a Strategic insight.

Assessment

Assessment for this course will occur at various times across the seven-week study period. Tasks may include online quizzes, discussion board activity, portfolio development, case studies, reflection, literature reviews presentations and reports.Feedback will be provided to you throughout the study period as well as a final grade at the conclusion of the study period.


This is one of the interdisciplinary subjects studied in the online Master of Data Science

Please note, course structure and content are subject to change. For information on all course subjects download the course guide.

Download Course Guide

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