ARTIFICIAL INTELLIGENCE (5 Credits)
Learning Outcomes:
On successful completion of this course, student will be able to: identify value propositions in business with physical / visual representation of an idea; describe what is AI and identify concept of intelligent agent; explain various intelligent search algorithms to solve the problems; explain how to use knowledge representation in reasoning purpose; apply various techniques to an agent when acting under certainty; apply various AI algorithms to solve the problems.
Topics:
- Introduction to Artificial Intelligence
- Search Strategies
- Introduction to Prototype Development 1 (PD1 – F2F)
- Local Search
- Adversarial Search
- Logical Agents
- First Order Logic
- VPC & Idea Profile (PD1 – Discussion Forum)
- Fuzzy Systems
- Quantifying Uncertainty 1
- Quantifying Uncertainty 2
- Probabilistic Reasoning
- Solution Sketch & Storyboard (PD1 – Discussion Forum)
- AI Application
- Probabilistic Reasoning Over Time
- Project Proposal Presentation
- Product / Service Prototype (PD1 – F2F)
- Learning from Examples
- Introduction to Machine Learning
- Products / Services Features & Function (PD1 – Discussion Forum)
- Linear Regression & Classification
- K-Nearest Neighbour
- Support Vector Machine
- Artificial Neural Network
- Key Resources & Pitch Deck
- Learning Probabilistic Models
- Natural Language Processing
- Natural Language for Communication
- Introduction to Computer Vision
- Project Presentation
- Report (PD1 – F2F)
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