Module #1 Introduction to Cognitive Computing Overview of cognitive computing, its history, and applications
Module #2 Artificial Intelligence and Machine Learning Fundamentals Basics of AI, ML, and deep learning; differences and relationships
Module #3 Cognitive Computing Architecture Components and architecture of cognitive computing systems
Module #4 Natural Language Processing (NLP) Fundamentals Introduction to NLP, text analysis, and sentiment analysis
Module #5 Deep Learning for NLP Applications of deep learning in NLP, including recurrent neural networks and transformers
Module #6 Computer Vision Fundamentals Introduction to computer vision, image processing, and object detection
Module #7 Deep Learning for Computer Vision Applications of deep learning in computer vision, including convolutional neural networks
Module #8 Cognitive Search and Query Cognitive search, query expansion, and relevance ranking
Module #9 Knowledge Graphs and Representation Knowledge graphs, ontology, and entity disambiguation
Module #10 Cognitive Reasoning and Inference Rule-based systems, logical reasoning, and inference engines
Module #11 Cognitive Computing in Healthcare Applications of cognitive computing in healthcare, including medical imaging and diagnosis
Module #12 Cognitive Computing in Finance Applications of cognitive computing in finance, including risk analysis and fraud detection
Module #13 Cognitive Computing in Customer Service Applications of cognitive computing in customer service, including chatbots and virtual assistants
Module #14 Cognitive Computing and IoT Applications of cognitive computing in IoT, including sensor data analysis and predictive maintenance
Module #15 Cognitive Analytics and Visualization Cognitive analytics, data visualization, and insights discovery
Module #16 Cognitive Computing and Cybersecurity Applications of cognitive computing in cybersecurity, including threat analysis and incident response
Module #17 Ethics and Bias in Cognitive Computing Ethical considerations, bias, and fairness in cognitive computing systems
Module #18 Cognitive Computing Platforms and Tools Overview of popular cognitive computing platforms and tools, including IBM Watson and Google Cloud AI
Module #19 Building Cognitive Computing Applications Hands-on development of cognitive computing applications using popular platforms and tools
Module #20 Cognitive Computing Case Studies Real-world case studies and applications of cognitive computing in various industries
Module #21 Cognitive Computing and Cloud Computing Integration of cognitive computing with cloud computing, including scalability and deployment
Module #22 Cognitive Computing and Edge Computing Integration of cognitive computing with edge computing, including real-time processing and IoT
Module #23 Cognitive Computing and Blockchain Integration of cognitive computing with blockchain, including decentralized AI and trustless systems
Module #24 Cognitive Computing and Explainability Explainability and transparency in cognitive computing systems, including model interpretability
Module #25 Course Wrap-Up & Conclusion Planning next steps in Cognitive Computing Technologies career
