Description
Artificial Intelligence (AI) refers to the simulation of human intelligence in machines that are designed to think, learn, and perform tasks autonomously. AI systems use algorithms and computational models to mimic cognitive functions such as problem-solving, decision-making, understanding language, and recognizing patterns. These systems can range from basic automation to more complex systems like self-driving cars, voice assistants, and sophisticated robotics.
Artificial Intelligence Course Content
Introduction to AI
- Definition and Overview of AI
- Narrow AI (Weak AI)
- General AI (Strong AI)
- Superintelligence
- AI in Everyday Life
Key Concepts in AI Machine Learning
- Supervised Learning
- Unsupervised Learning
- Reinforcement Learning
- Deep Learning
- Introduction to Neural Networks and Artificial Neurons.
AI Techniques and Algorithms
- Breadth-First Search (BFS) and Depth-First Search (DFS)
- Optimization Algorithms
- Gradient Descent
- Natural Language Processing (NLP)
- Computer Vision
AI Tools and Technologies
- Programming Languages:
- Python
- R
- AI Libraries and Frameworks:
- TensorFlow
- PyTorch
- Scikit-learn
- Data Handling:
- Pandas:
- NumPy:
- Matplotlib:
AI Project Development
- AI Workflow
- Supervised Learning Project
- Unsupervised Learning Project:
- Reinforcement Learning Project
Ethical and Social Implications of AI
- Ethics in AI:
- AI in the Future:
AI Applications in the Real World
- Autonomous Systems:
- AI in Healthcare:
- AI in Finance:
Courses Features
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LanguageEnglish
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Lectures02
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CertificationYes
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Project02
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Duration40 hrs
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Max-Students20
