What the course covers.
- Module 1
AI Pipeline Fundamentals
Learners explore the end-to-end process of AI application development, including data acquisition, cleaning, and preprocessing. This module introduces workflows for integrating machine learning models into applications, ensuring that participants understand how to structure projects for maintainability, scalability, and reproducibility.
- Module 2
Building AI Applications
This module focuses on coding and implementing AI models within software applications. Learners use Python frameworks and libraries to build applications that leverage machine learning and deep learning models. Practical exercises include creating recommendation systems, predictive models, and intelligent automation tools, providing hands-on experience in real-world AI development.
- Module 3
Deployment & Integration
Learners learn to deploy AI applications into production environments using APIs, containerisation, and cloud platforms. The module covers testing, monitoring, model versioning, and workflow optimisation. Participants gain the skills needed to maintain reliable, scalable, and efficient AI systems that function seamlessly in business and industrial contexts.
