Applied Machine Learning - From Data to Deployment
About This Course
Across industries such as healthcare, finance, logistics, and the public sector, organisations increasingly rely on accurate data collection and analysis to improve performance, optimise operations, and support policy and strategic decisions. Through a practical exploration of machine learning workflows, participants will develop competencies in identifying relevant data sources, preparing and structuring datasets, and applying analytical techniques to generate meaningful insights. This course strengthens employability by building job-relevant capabilities in data collection, data preparation, and analysis, which are core requirements in many digital and transformation roles. This is an intermediate course.
What You'll Learn
Apply data collection and preparation techniques within machine learning workflows, including feature engineering methods to ensure data quality for analysis.
Interpret data-driven insights and evaluation metrics to support informed decision-making.
Deploy generative AI applications by applying prompt engineering techniques and integration methods for organizational use cases.
Entry Requirements
-Working Experience: Minimum working experience of 1 month and basic programming knowledge in Python.
- Minimum Education: Diploma
- Age ≥ 20 years old
- Workplace Literacy and Numeracy Level 5 (WPLN: Speaking, Writing, Listening, Reading, and Numeracy at ESS level 5 or equivalent)
-Learners will be advised to attend basic python course if they are unable to meet the minimum entry requirements.