MIS140 - Introduction to Machine Learning for Business
| Year: | 2025 unit information |
|---|---|
| Enrolment modes: | Trimester 1: Burwood (Melbourne), Online Trimester 3: Burwood (Melbourne), Online |
| Credit point(s): | 1 |
| EFTSL value: | 0.125 |
| Cohort rule: | Nil |
| Prerequisite: | Nil |
| Corequisite: | Nil |
| Incompatible with: | SIT112 |
| Study commitment | Students will on average spend 150-hours over the teaching period undertaking the teaching, learning and assessment activities. |
| Scheduled learning activities - campus | 1 x 1.5 hour on-campus (live-streamed) lecture (recordings provided) and 1 x 1.5 hour on-campus seminar each week |
| Scheduled learning activities - online | 1 x 1.5 hour recorded lecture provided and 1 x 1.5 hour online seminar (recordings provided) each week |
Content
The overarching aim of this unit is to provide students with a strong foundation on machine learning and data analytics, required by business professionals. The unit will introduce business students to fundamental concepts in data analytics, machine learning and their applications in business context. Students will also be introduced to popular software packages for data analytics in Python programming platforms. Through this unit, students will be provided with foundational knowledge and skills to prepare themselves for more advanced analytics and Artificial Intelligence techniques for business applications in the subsequent advanced units. Students will be able to explain and apply data science concepts and develop analytical solutions to business problems and interpret the outcomes to the various stakeholders.
Hurdle requirement
Nil
Unit Fee Information
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Tuition fees increase at the beginning of each calendar year and all fees quoted are in Australian dollars ($AUD). Tuition fees do not include textbooks, computer equipment or software, other equipment or costs such as mandatory checks, travel and stationery.
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