MAI611 Data Science
This course will introduce the basic concepts and skills needed to extract knowledge from data. The students will learn the basics of statistical interference and machine learning needed to analyze the data. Students will learn concepts, algorithms and tools they need to deal with various facets of data science, including data exploratory analysis, data science process, feature generation and feature selection, recommendation systems, mining of social network graphs data visualization, and the ethics of data science.
MAI612 AI Essentials for Advanced Applications
This course introduces essential principles and concepts of Artificial Intelligence (AI) while exploring advanced AI applications such as Natural Language Processing (NLP), Generative AI, Computer Vision, and Robotics. Students will learn key AI methodologies, including search algorithms, knowledge representation, reasoning techniques, and constraint satisfaction problems. The course emphasizes practical applications through a lab component, providing hands-on experience in developing AI solutions and exploring real-world use cases. By the end of the course, students will be equipped with foundational knowledge and skills essential for applying AI techniques in advanced and emerging domains.
MAI613 Applied Machine Learning and Pattern Recognition
This course introduces students to the practical aspects of machine learning and pattern recognition techniques, with an emphasis on real-world applications. Students will gain hands-on experience in implementing and evaluating machine learning algorithms for various tasks such as classification, regression, clustering, and pattern recognition.
MAI614 Applied Deep Learning
To introduce students to the fundamentals of deep neural network, network optimization, backpropagation, regularization, transfer learning, convolutional neural network (CNN), application of convolutional neural network in image classification and natural language processing, transformer, graph neural network and generative adversarial networks.
MAI622 Image Processing and Computer Vision
This course will introduce students to the fundamentals of image formation, major ideas, methods, and techniques of computer vision and pattern recognition, design of computer vision and object recognition systems, and programming experience from implementing computer vision and object recognition applications.
MAI615 Research and Ethics in AI
This course provides students with essential skills in AI research design and analysis while instilling a strong foundation in ethical considerations. Topics include research methodologies, data collection, statistical analysis, writing and presenting research papers, and understanding ethical challenges such as bias, privacy, and accountability in AI systems. Students will balance technical research skills with a comprehensive understanding of the ethical responsibilities in AI applications.
MAI632 AI Thesis
The AI Thesis course provides students with the opportunity to apply advanced AI concepts and methodologies to a substantial research project. The course involves conducting original research, developing AI solutions, analyzing results, and presenting findings. Students are guided through the research process, from problem formulation to the final defense of their thesis.
MAI620 Artificial Intelligence in Cybersecurity
This course explores the cutting-edge applications of AI in cybersecurity. Students will gain a comprehensive understanding of how AI techniques are used to detect, prevent, and respond to cyber threats. The course will cover topics such as anomaly detection, malware analysis, threat intelligence, and user behavior analysis. Students will also learn about the challenges and ethical considerations of using AI in cybersecurity.
MAI621 AI Applications in Transportation and GIS
This course explores the integration of Artificial Intelligence (AI) with Intelligent Transportation Systems (ITS) and Geographic Information Systems (GIS) to enable advanced solutions in smart transportation. Topics include predictive modeling, optimization techniques, autonomous vehicle navigation, spatial analysis, and GIS-based decision-making. The course emphasizes hands-on problem-solving using state-of-the-art AI frameworks and GIS tools.
MAI624 Artificial Intelligence for Business and Entrepreneurs
This course introduces the strategic use of artificial intelligence (AI) in business and entrepreneurship. Students will learn to identify AI opportunities, evaluate solutions, and develop strategies for successful implementation. Emphasis is placed on aligning AI initiatives with business goals, managing data quality, addressing ethical concerns, and leveraging emerging trends. Practical assignments and a final project will enable participants to apply AI concepts to real-world scenarios.
MAI623 AI in Bioinformatics and Healthcare Systems
This course explores the applications of Artificial Intelligence (AI) in bioinformatics and healthcare systems. Students will learn to apply machine learning and deep learning techniques to analyze biological data, including genomic, proteomic, and clinical datasets. The course covers bioinformatics tools, predictive modeling, AI-driven diagnostics, personalized medicine, and ethical considerations in healthcare AI. By the end of the course, students will be equipped to design AI-based solutions for bioinformatics and healthcare challenges.
MAI627 Artificial Intelligence in Quantum Computing
The course will explore the intersection of Artificial Intelligence and Quantum Computing, focusing on how quantum technologies can enhance AI capabilities and how AI can advance quantum computing research. It covers the foundational concepts of quantum mechanics, quantum computation, and their implications for solving complex AI problems. Students will explore quantum algorithms, quantum machine learning techniques, and hands-on projects that apply AI methods within quantum systems.
MAI625 AI in IoT and Edge Computing
In this course, the student will learn sensor programming on an embedded device; use Wi-Fi, Bluetooth and MQTT to implement data streaming, remote control, and multi-device networking; explore the IoT data processing life cycle which includes capturing, cloud storage, and data analysis; develop and deploy machine learning models for use in mobile and edge computing environments.
MAI626 Artificial Intelligence for Sustainability and Climate Change
This course aims to equip students with an understanding of how artificial intelligence (AI) can address challenges related to sustainability and climate change. Students will explore AI applications in renewable energy, climate modeling, resource optimization, and sustainable development while critically analyzing ethical considerations and limitations. It explores the application of artificial intelligence (AI) in addressing sustainability challenges and climate change
MAI628 AI in Education
This course examines the transformative impact of Artificial Intelligence on education, focusing on its applications in teaching, learning, and assessment. Topics include learning analytics, intelligent tutoring systems, natural language processing, gamification, accessibility, and, teacher support systems. Students will explore the ethical implications and societal impacts of AI in education, while engaging in practical assignments, case studies, and projects. The course also highlights emerging trends such as AI-driven creativity, lifelong learning, and virtual and augmented reality in education, preparing students to develop innovative and ethical AI solutions for educational challenges.