Master of Science in Artificial Intelligence Inactive
Course Units 10
AI Applications And Case Studies
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AI Applications And Case Studies
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Topics & Notes
AI in Finance
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AI in Healthcare
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AI in Marketing
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AI in Transportation
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Case Study: Amazon's Recommendation System
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Case Study: DeepMind's AlphaGo
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Case Study: IBM Watson in Healthcare
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Introduction to AI Applications
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AI Ethics And Bias
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AI Ethics And Bias
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Topics & Notes
Accountability and Responsibility in AI
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Bias in AI
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Ethical Decision-Making in AI
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Ethical Principles in AI
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Fairness in AI
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Introduction to AI Ethics
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Privacy and Data Protection in AI
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Regulatory Frameworks for AI Ethics
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AI Research Methods
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AI Research Methods
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Topics & Notes
Collaborative Research Practices in AI
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Data Collection Techniques in AI Research
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Ethical Considerations in AI Research
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Experimental Design in AI Research
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Introduction to AI Research Methods
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Literature Review in AI Research
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Mixed-Methods Approach in AI Research
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Qualitative Research Methods in AI
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Quantitative Research Methods in AI
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Research Reproducibility and Transparency in AI
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Capstone Project
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Capstone Project
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Topics & Notes
Choosing a Capstone Project Topic
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Conducting Literature Review for Capstone Project
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Creating Visual Aids and Presentations
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Data Collection and Analysis Methods
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Developing a Capstone Project Proposal
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Final Presentation and Defense
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Peer Review and Feedback
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Writing the Capstone Project Report
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Computer Vision
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Computer Vision
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Topics & Notes
Convolutional Neural Networks (CNNs)
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Ethical Considerations in Computer Vision
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Face Recognition and Biometrics
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Image Captioning and Visual Question Answering
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Image Processing Fundamentals
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Image Segmentation
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Introduction to Computer Vision
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Object Detection and Recognition
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Object Tracking
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Transfer Learning in Computer Vision
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Deep Learning And Neural Networks
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Deep Learning And Neural Networks
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Topics & Notes
Artificial Neural Networks (ANN)
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Case Studies in Deep Learning
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Convolutional Neural Networks (CNN)
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Ethical Considerations in Deep Learning
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Generative Adversarial Networks (GANs)
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Introduction to Deep Learning
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Optimization Techniques in Deep Learning
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Recurrent Neural Networks (RNN)
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Regularization and Dropout in Neural Networks
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Transfer Learning and Fine-Tuning
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