Artificial Intelligence: Concepts and Techniques

Overview

ABOUT THE COURSE:

Artificial Intelligence is found being increasing used nowadays to carry out tasks which used to be done by humans manually. This is a post graduate level course which teaches about the terminology and techniques employed in Artificial Intelligence.

This covers concepts such as general problem solving, logic and reasoning, machine learning and deep learning, generative AI, and planning. Topics like genetic algorithms and swarm intelligence are also covered.

Some AI programming languages like Lisp, Prolog and CLIPS are taught with assignments being covered in these languages. Practical applications like web-based agents, mobile agents, and negotiating agents are covered.

Philosophical and ethical considerations are also discussed.INTENDED AUDIENCE:

Instructors and students of academic institutes, employees in IT sector especially working in the Artificial Intelligence fieldPREREQUISITES:

Bachelors degree in engineering, MCA, M.Sc.(Maths)INDUSTRY SUPPORT:

Industries working on Artificial Intelligence

Syllabus

• Introduction to Artificial Intelligence
Overview of AI and its applications
History and evolution of AI
• General Problem Solving Techniques
Search algorithms: BFS, DFS, A*
Optimization and heuristic search
• Logic and Reasoning
Propositional and first-order logic
Rule-based systems and inference
• Machine Learning
Supervised learning: classification and regression
Unsupervised learning: clustering and dimensionality reduction
Reinforcement learning basics
• Deep Learning
Neural networks and backpropagation
Convolutional Neural Networks (CNN)
Recurrent Neural Networks (RNN)
• Generative AI
Generative models: GANs and VAEs
Applications of generative AI
• Planning and Decision Making
Automated planning and scheduling
Decision trees and Markov decision processes
• Evolutionary Computation
Genetic algorithms
Swarm intelligence: ant colony and particle swarm optimization
• AI Programming Languages
Lisp: syntax and semantics
Prolog: logical programming basics
CLIPS: expert system language
• Applications of AI Agents
Web-based agents
Mobile agents
Negotiating agents
• Philosophical and Ethical Considerations
Ethics in AI: bias, privacy, and accountability
Future implications of AI technologies
• Practical Assignments and Project Work
Programming assignments in Lisp, Prolog, and CLIPS
Case studies and project reports in AI applications
• Industry Trends and Case Studies
Emerging trends in AI
Real-world applications and case studies across industries

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Taught by

Prof. V. Susheela Devi

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Subjects

Computer Science