Machine Learning for Business Professionals

Course aim

To develop skills in machine learning to address opportunities and challenges in business using predictive analytics and pattern detection with (Big) data.

Course content

An overview of artificial intelligence focusing on machine learning and the opportunities for innovation and efficiency in business and management. A business roadmap for the successful integration of machine learning in any organisation. Supervised, semi-supervised and unsupervised learning algorithms including sentiment analysis, market basket analysis, recommender systems and streaming analytics for the Internet of Things using BI software.

Textbook(s)

Nil

Prerequisite(s)

Common to all relevant programs
Subject Area & Catalogue Number	Course Name
INFS 5130	Fundamentals of Data Analytics for Business

Corequisite(s)

Nil

Teaching method

Component	Duration
INTERNAL, CITY WEST
Seminar	3 hours x 10 weeks
Preparatory	1 week x 1 hour
EXTERNAL, CITY WEST, ONLINE
External	30 hours x N/A

Note: These components may or may not be scheduled in every study period. Please refer to the timetable for further details.

Assessment

Project, Test/Quiz

Fees

EFTSL*: 0.125
Commonwealth Supported program (Band 2)
To determine the fee for this course as part of a Commonwealth Supported program, go to:
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Fee-paying program for domestic and international students
International students and students undertaking this course as part of a postgraduate fee paying program must refer to the relevant program home page to determine the cost for undertaking this course.

Non-award enrolment
Non-award tuition fees are set by the university. To determine the cost of this course, go to:
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Not all courses are available on all of the above bases, and students must check to ensure that they are permitted to enrol in a particular course.

* Equivalent Full Time Study Load. Please note: all EFTSL values are published and calculated at ten decimal places. Values are displayed to three decimal places for ease of interpretation.