Cognitive Science - Syllabus

An overview of computers and their significance in today's world. This topic sets the stage for understanding the basics of computers.

Understanding the difference between digital and analog computers, their characteristics, and applications.

Exploring the key characteristics of computers, including input, processing, storage, and output.

A brief history of computers, from their inception to the present day, highlighting key milestones and developments.

Understanding the different generations of computers, including their features, advantages, and limitations.

Categorizing computers based on their size, functionality, and application, including desktops, laptops, and mobile devices.

An in-depth look at the components of a computer system, including hardware and software.

Exploring the various applications of computers in different fields, including business, education, and healthcare.

Understanding the legal framework governing E-commerce in Nepal.

This topic explores the various application areas of simulation, including engineering, economics, and healthcare.

Ethical considerations and principles in software engineering, including accountability, privacy, and intellectual property.

Exploring the role of distributed computing in grid and cloud environments, including its applications and benefits.

Current and emerging trends in data warehousing, including big data, cloud computing, and real-time analytics.

This topic introduces the concept of programming languages, their importance, and brief history. It sets the foundation for understanding the basics of programming.

This topic covers the different types of programming languages, including procedural, object-oriented, functional, and scripting languages. It explains the characteristics and uses of each type.

This topic explains the role of a language processor, including compilers, interpreters, and assemblers. It discusses how they translate source code into machine code.

This topic discusses the different types of program errors, including syntax, runtime, and logical errors. It explains how to identify, debug, and fix errors.

This topic outlines the characteristics of a good program, including readability, maintainability, efficiency, and reliability. It provides guidelines for writing good programs.

This topic explores different programming paradigms, including procedural, object-oriented, functional, and declarative programming. It explains the principles and applications of each paradigm.

This topic explores the different models that explain how human memory works, including the process of information encoding, storage, and retrieval. It lays the foundation for understanding human cognition.

This topic delves into the specifics of Atkinson-Shiffrin's model of memory, which proposes a multi-store model of memory consisting of sensory memory, short-term memory, and long-term memory. It explains the flow of information between these stores.

This topic discusses Tulving's model of memory, which highlights the distinction between episodic and semantic memory. It explores the role of episodic memory in storing personal experiences and semantic memory in storing factual knowledge.

This topic examines the concept of mental imagery, which refers to the ability to generate mental representations of objects, events, or scenarios. It explores the role of mental imagery in cognition and problem-solving.

This topic presents Kosslyn's view on mental imagery, which proposes that mental images are pictorial representations that are similar to visual perceptions. It discusses the implications of this view on our understanding of cognition.

This topic presents Moyer's view on mental imagery, which suggests that mental images are propositional representations that are similar to linguistic representations. It compares and contrasts Moyer's view with Kosslyn's view.

This topic presents Peterson's view on mental imagery, which proposes that mental images are a combination of pictorial and propositional representations. It discusses the strengths and limitations of Peterson's view.

This topic explores the concept of cognitive maps, which are mental representations of spatial environments. It discusses the role of cognitive maps in navigation, problem-solving, and decision-making.

This topic examines the process of problem understanding, which involves the interpretation and representation of problems. It discusses the role of problem understanding in cognitive processing and decision-making.

This topic discusses the different states of cognition, including attention, perception, and awareness. It explores the neural mechanisms underlying these states and their role in cognitive processing.

This topic explores the application of cognitive science principles to artificial intelligence, including the development of cognitive models and architectures for AI systems. It discusses the potential and limitations of AI in simulating human cognition.

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

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

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

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

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

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

The principles of formatting and organizing brief correspondence, including headings, paragraphs, and white space. This topic covers how to make your message clear and easy to read.

This topic explores models of information processing inspired by the structure and function of the brain. It introduces the concept of neural networks and their application to information processing.

This topic delves into the basics of single-layer neural networks and their relationship with Boolean functions. It covers the fundamentals of neural network architecture and its application to simple logical operations.

This topic builds upon the basics of single-layer networks and explores the architecture and functionality of multilayer neural networks. It discusses the advantages and limitations of multilayer networks in information processing.

This topic examines the process of information processing within neural networks. It covers how neural networks receive, process, and transmit information, and the implications for cognitive science.

This topic investigates the application of neural networks to language learning and processing. It explores how neural networks can be used to model language acquisition and understanding.

This topic applies neural network models to the study of children's physical reasoning and cognitive development. It examines how neural networks can be used to understand and simulate children's problem-solving abilities.