- This course explores how AI transforms chemical engineering, with applications ranging from process optimization to sustainability and safety. Tailored for chemical engineers, process engineers, and professionals in industries like petrochemicals and pharmaceuticals, it covers practical AI methods for improving chemical processes.
- Level: Intermediate
- Prerequisites: Background in chemical engineering or related fields.
- Assessments: Micro Assessment weekly, Full Assessment in the final week.
Week 1 - AI in Chemical Process Design
Learning OutcomeDiscover how AI improves chemical process design.
1.1 AI-powered process simulation and optimization.1.2 Machine learning for material selection and reaction optimization.
1.3 AI for safety and hazard analysis in chemical processes.
Practical Component
Use AI tools to design and simulate a chemical process.
Week 2 - Optimizing Chemical Production with AI
Learning OutcomeLearn how AI optimizes chemical production efficiency.
2.1 AI for predictive maintenance in chemical plants.2.2 Machine learning for optimizing chemical reaction rates.
2.3 AI-driven solutions for reducing waste in production.
Practical Component
Build an AI-powered production optimization model for a chemical plant.
Week 3 - AI in Sustainable Chemical Engineering
Learning OutcomeExplore AI's role in sustainable chemical engineering practices.
3.1 AI for energy optimization in chemical processes.3.2 Machine learning for reducing environmental impact.
3.3 AI in resource management and waste reduction.
Practical Component
Develop an AI solution for a sustainable chemical engineering process.
Week 4 - AI for Chemical Process Control
Learning OutcomeUnderstand how AI is used in process control systems.
4.1 AI for real-time process monitoring and control.4.2 Machine learning for anomaly detection in chemical processes.
4.3 AI for predictive analytics in process control.
Practical Component
Build an AI model for process control in a chemical plant.
Week 5 - AI in Pharmaceuticals and Biochemical Engineering
Learning OutcomeLearn how AI impacts pharmaceutical and biochemical engineering.
5.1 AI for drug discovery and design.5.2 Machine learning for optimizing bioprocesses.
5.3 AI-driven solutions for quality control in pharmaceuticals.
Practical Component
Design an AI-powered model for drug production optimization.
Week 6 - Capstone Project and Assessment
Learning OutcomeApply AI to a real-world chemical engineering challenge.
6.1 Develop an AI-based solution for a chemical engineering process.6.2 Peer assessment and feedback.
6.3 Final project presentation and evaluation.
Practical Component
Present an AI-driven solution for a chemical engineering problem.