Data Mining and Machine Learning

This subject will commence in 2025

Awards offering Data Mining and Machine Learning

This unit is offered as a part of the following awards:

• Bachelor of Business
• Bachelor of Business (Business Analytics)

Unit Content

Outcomes

1. Evaluate different data mining techniques, such as clustering, classification, and association rule mining, to extract valuable patterns and insights from large datasets; 
2. Employ machine learning algorithms for tasks like regression, classification, and unsupervised learning, enabling data-driven decision-making; 
3. Critically evaluate the performance of machine learning models using appropriate metrics; 
4. Discuss the application of data mining and machine learning to techniques to solve real-world business problems. 

Subject Content

1. Introduction to Data Mining and Machine Learning
2. Data Preprocessing and Cleaning 
3. Supervised Learning Algorithms 
4. Unsupervised Learning and Clustering 
5. Dimensionality Reduction Techniques 
6. Real-World Applications and Case Studies 
7. Feature Selection and Engineering 
8. Evaluation Metrics for Machine Learning Models
9. Ensemble Learning and Model Stacking 
10. Time Series Analysis and Forecasting 
11. Text Mining and Natural Language Processing
12. Deep Learning and Neural Networks 

This course may be offered in the following formats

1. Face to face on site 
2. E-learning (online) 
3. Intensive
4. Extensive

Please consult your course prospectus or enquire about how and when this course will be offered next at Alphacrucis University College.

Assessment Methods

1. Exam (25%)
2. Maching Learning Project and Report (50%)
3. Group Case Study (25%)

Prescribed Text

Raja, R., Nagwanshi, K. K., Kumar, S., & Ramya Laxmi, K. (2022). Data Mining and Machine Learning Applications. Wiley-Scrivener. 
Check with the instructor each semester before purchasing any textbooks