Certified Artificial Intelligence Practitioner (CAIP)
About This Course
This course equips learners with the competencies to apply structured data collection, modelling, and advanced analytics techniques to support data-driven decision-making in organisational contexts. Learners will develop the ability to collect and extract data based on defined requirements, and apply data modelling methods to identify meaningful relationships between variables. The course also covers model deployment, MLOps practices, and ongoing model maintenance, equipping learners with the skills to support end-to-end Machine Learning implementation in an organisational environment. This is an intermediate course.
What You'll Learn
1.Apply data collection and analysis techniques to collect and extract data according to defined requirements.
2.Apply data modelling techniques to identify relationships between variables
3.Analyse clustering results to identify patterns and exceptions.
4.Assess analytical outcomes generated by neural network models.
5.Evaluate data-driven insights by explaining model results to support informed decision-making.
Entry Requirements
Leaners are strongly recommended to have the following skills and knowledge before starting this course:
--Basic understanding of statistics and data visualization
- Python Programming
Education: Diploma and above
Experience: > 1 month