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Starts 6 June 2025 18:12

Ends 6 June 2025

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Artificial Intelligence: Concepts and Techniques

Master AI concepts including problem-solving, logic, machine learning, deep learning, generative AI, planning, and programming languages like Lisp, Prolog, and CLIPS. Explore practical applications and ethical considerations.
NPTEL via Swayam

NPTEL

125 Courses


12 weeks

Optional upgrade avallable

Intermediate

Progress at your own speed

Free Online Course

Optional upgrade avallable

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

Taught by

Prof. V. Susheela Devi


Subjects

Computer Science