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Tribhuvan university CSIT 2065 Syllabus Introduction to Cognitive Science

Introduction to Cognitive Science - Syllabus

Course Overview and Structure
Syllabus Notes Old Questions Unit Wise Questions Question Bank

Embark on a profound academic exploration as you delve into the Introduction to Cognitive Science course () within the distinguished Tribhuvan university's CSIT department. Aligned with the 2065 Syllabus, this course (CSC-255) seamlessly merges theoretical frameworks with practical sessions, ensuring a comprehensive understanding of the subject. Rigorous assessment based on a 60+20+20 marks system, coupled with a challenging passing threshold of , propels students to strive for excellence, fostering a deeper grasp of the course content.

This 3 credit-hour journey unfolds as a holistic learning experience, bridging theory and application. Beyond theoretical comprehension, students actively engage in practical sessions, acquiring valuable skills for real-world scenarios. Immerse yourself in this well-structured course, where each element, from the course description to interactive sessions, is meticulously crafted to shape a well-rounded and insightful academic experience.


Course Synopsis: An introduction to cognitive science and its relation with other sciences. It covers briefly the area of Artificial Intelligence, Computational models and connectionist approach. 
Goal: 
  • The student will gain an introductory understanding of what it means to say that intelligence is computational
  • The student will:
    • Acquire a good understanding of what an algorithm is and learn how to implement algorithms in the programming language LISP
    • Develop an introductory understanding of formal models for computation, the limits of computation, the Chomsky hierarchy, and the Turing-Church hypothesis
  • The student will study some of the modern attempts to demonstrate a computational model for intelligence through an introduction to the discipline of artificial intelligence, including introductions to knowledge representation, search, and artificial neural networks.
  • Finally, the student will explore some of the positions taken in the ongoing discussion of this issue. In Philosophy and Linguistics, we will begin with Descartes, and look (and discuss) Turing, Gelernter, Newell and Simon, Penrose, Searle, and others, finishing with a partial response to Descartes given to us by Chomsky and others.

Units

Key Topics

  • Introduction to E-commerce
    IN-1

    Overview of E-commerce and its significance in the digital age.

  • E-business vs E-commerce
    IN-2

    Understanding the differences between E-business and E-commerce.

  • Features of E-commerce
    IN-3

    Key characteristics and benefits of E-commerce.

  • Pure vs Partial E-commerce
    IN-4

    Types of E-commerce models and their applications.

  • History of E-commerce
    IN-5

    Evolution and development of E-commerce over time.

Key Topics

  • History and Background of Artificial Intelligence
    BR-1

    This topic covers the origins and development of Artificial Intelligence as a field of study, including key milestones and contributors.

  • Knowledge Representation
    BR-2

    This topic explores how computers can store, organize, and retrieve knowledge, including data structures and formats used to represent knowledge.

  • Human Information Processing and Problem Solving
    BR-3

    This topic examines how humans process information, reason, and solve problems, including cognitive biases and heuristics.

  • Search
    BR-4

    This topic introduces search algorithms and strategies used in Artificial Intelligence, including uninformed and informed search methods.

  • Expert Systems
    BR-5

    This topic covers the design and development of expert systems, which mimic human expertise in specific domains.

  • Introduction to Neural Networks
    BR-6

    This topic provides a foundational understanding of neural networks, including their structure, function, and applications in Artificial Intelligence.

Key Topics

  • Nature of Internship
    CO-1

    The internship work should be relevant to the field of computer science and information technology, with a minimum duration of 180 hours or ten weeks.

  • Phases of Internship
    CO-2

    The internship evaluation consists of three phases: Proposal Submission, Mid-Term Submission, and Final Submission.

  • Provision of Supervision
    CO-3

    A regular faculty member of the college is assigned as a supervisor to supervise the students throughout the internship period.

  • Provision of Mentorship
    CO-4

    A regular employee of the intern providing organization is assigned as a mentor to guide the students throughout the internship period.

  • Evaluation Scheme
    CO-5

    The evaluation scheme consists of Proposal Defense, Midterm, and Final Defense, with a total of 200 marks.

  • Report Contents
    CO-6

    The internship report should contain prescribed content flow, including introduction, problem statement, objectives, and references.

The connectionist approach, Different models and tool: Gelernter, Penrose, Pinker, Searle; Response to Descartes: Natural Language Processing, Parameters in the Natural Language Processing.