1. General information about the module
Module code: PET10011
Vietnamese module designation: MÁY HỌC VÀ ỨNG DỤNG
English module designation: MACHINE LEARNING AND APPLICATIONS
Credit points: 3
Workload:
- Contact Hours: Lectures, lessons: 30 hours (in class)
- Lab works, project, seminar: 30 hours
- Exercise: 0 hours
- Private study: 90 hours
Type of module: Specialized
Required and recommended prerequisites for joining the module: None
Modules taken before this module: None
2. Module objectives/intended learning outcomes
This course introduces the fundamental concepts and methodologies of machine learning (ML), with a strong emphasis on practical applications in areas such as:
Signal processing and biomedical applications, including EEG, ECG, and sensor data;
Computer vision;
Natural language processing (NLP);
Recommender systems;
Industrial data analytics.
Students will acquire foundational knowledge of supervised and unsupervised learning, including classification, regression, and clustering, as well as modern approaches such as ensemble learning and artificial neural networks.
The course provides an in-depth understanding of the complete machine learning application development lifecycle, including data collection, preprocessing, model development, evaluation, deployment, and monitoring. It establishes an essential foundation for advanced courses such as Deep Learning, Image Processing, Natural Language Processing, and Data Mining, while preparing students to apply ML techniques to scientific and technological research projects and industry-oriented applications.