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Artificial Intelligence Advance
Advanced AI solutions are crucial in real-world systems, especially within enterprises. Integration and operational practices, including MLOps and AI lifecycle management, are essential for effective deployment and maintenance. Addressing challenges such as data drift and latency ensures the models perform optimally after deployment.
11 Chapters
125 hr
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Course Chapters
Chapter 1
Foundations of Advanced Artificial Intelligence
Chapter 2
Deep Learning Architectures
Chapter 3
Natural Language Processing (NLP) in Depth
Chapter 4
Reinforcement Learning and Decision Making
Chapter 5
Computer Vision and Image Intelligence
Chapter 6
AI in Robotics and Autonomous Systems
Chapter 7
Explainable AI (XAI) and Model Interpretability
Chapter 8
AI Ethics, Bias, and Responsible AI
Chapter 9
AI for Edge Devices and Internet of Things
Chapter 10
The Future of AI – Trends, Challenges, and Opportunities
Chapter 11