Postgraduate Certificate in AI in FoodTech

•  Artificial Intelligence (AI) Fundamentals in FoodTech: Introduce the basics of AI, its applications, and potential in the Food Technology sector.<br> •  Data Analysis & Machine Learning (ML) for FoodTech: Discuss data-driven decision making, descriptive, predictive, and prescriptive analytics, and various ML techniques.<br> •  Computer Vision in Food Industry: Cover image processing, object detection, and recognition with applications in food inspection, sorting, and safety.<br> •  Natural Language Processing (NLP) for FoodTech: Explore text mining, sentiment analysis, and chatbot development relevant to food, nutrition, and diet.<br> •  Robotics and Automation in Food Production: Examine the use of robotics in farming, food processing, packaging, and delivery, including drones and autonomous vehicles.<br> •  AI Ethics and Regulations in FoodTech: Analyze ethical considerations, data privacy, and regulatory compliance in AI-driven food technologies.<br> •  AI-Driven Innovations in Food Industry: Showcase novel AI applications such as personalized nutrition, smart kitchens, and food waste reduction.<br> •  AI Project Management and Development in FoodTech: Teach students to plan, design, and manage AI projects, emphasizing collaboration with cross-functional teams.<br> •  Capstone Project: AI in FoodTech: Students will demonstrate their understanding of AI in FoodTech by developing a working AI-driven prototype or a detailed project proposal.<br>