Description
- Introduction to Artificial Intelligence: What is AI, its history, and its applications.
- Fundamentals of Machine Learning: Supervised, unsupervised, and reinforcement learning.
- Deep Learning and Neural Networks: Architectures, training, and applications.
- Natural Language Processing (NLP): Text processing, language models, and applications.
- Computer Vision: Image recognition, object detection, and applications.
- Robotics and AI: Combining AI with robots for various tasks.
- AI Ethics and Societal Impact: Responsible AI development and ethical considerations.
- AI Applications: Real-world use cases in various industries.
- AI Tools and Technologies: Programming languages, libraries, and frameworks for AI development.
- AI Research and Future Trends: Exploring current research and future directions in AI.
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