This course provides students with an overview of the many concepts, techniques and algorithms in data analytics and machine learning. Students will acquire knowledge on classification and regression models such as support vector machines and linear regression etc. The emphasis in this course will be on the application side of data analytics which includes not only creating the predictive model but also deploying and visualizing the output from the models.
More importantly, this course allows students to apply cross-disciplinary and project management approaches while learning and applying machine learning techniques to help Thai companies to effectively and efficiently apply data analytics and machine learning to improve their competitiveness and business efficiency. It hones students’ problem-solving skills and prepares them for the complex regional business environment today.
Thailand, as part of ASEAN, is rich in natural resources eg. gems and precious metals and is considered to be one of the vital exporters of resources globally. Other than the 2 traditional sectors of agriculture and tourism, it is also a prime manufacturing hub for investors in vehicles, electronics and medical equipment. In recent years, Covid-19 has become a key accelerator for digital transformation globally and the Thai government has also been relentlessly encouraging its businesses to adopt digital technologies and the use of data analytics.
This course is not biddable. Students will be shortlisted for interviews and selected students will be enrolled via offline enrolment (e$20 will be deducted).
By the end of this course, students will learn to:
- Cleanse and prepare data to be in a form adequate for machine learning.
- Outline the steps involved in developing and consuming a machine learning model.
- Develop adequate machine learning models to meet different business objectives.
- Tune the performance of machine learning models.
- Create visualizations to consume the output from machine learning models.