As a professional in business and management, are you eager to know what machine learning or artificial intelligence is about and how you can use them in your future career? Get ready to explore and critically examine modern machine learning theory and methods for business data analysis, including both supervised learning, such asregression and classification,.and unsupervised learning, such asassociation rule discovery and cluster analysis.
You will gain a holistic understanding of multiple forecasting methods, including exponential smoothing methods, the Box-Jenkins method (i.e. the ARIMA model and variants), and deep learning methods for sequential data analysis to master modelling processes.
Through this learning journey you will systematically explore the modelling process by carrying out data analysis of real-world datasets, use machine learning and forecasting software packages and be able to analyse given data to help achieve your business goals.
Lecture 16, PC Lab 16
Online test (45 minutes) worth 20%.
Individual Data Analysis Report (3000 words) worth 80%.
Reassessment Method: 100% Written Assessment (Individual Report, 3,000 words)
On successful completion of this module, students will be able to:
Critically evaluate the types of data analysis problems that can be appropriately dealt with using machine learning and forecasting techniques.
Understand and critically discuss research issues within the area of machine learning and forecasting.
Successfully develop machine learning and forecasting models and apply them to real-world problems.
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