Software Development
Cognitive Models
Cognitive Models: Approaches to Cognitive Learning
Cognitive Models: Overview of Cognitive Models

Cognitive Models: Approaches to Cognitive Learning

Course Number:
it_aiapcmdj_02_enus
Lesson Objectives

Cognitive Models: Approaches to Cognitive Learning

  • discover the key concepts covered in this course
  • name and describe different types of cognitive learning
  • define symbolic learning and describe examples of its use
  • define sub-symbolic learning and describe multiple models used with this approach
  • define hybrid learning and describe examples of its use
  • specify how AI has affected cognitive modeling and enhanced its power
  • describe and distinguish between different types of modeling tools
  • work with popular NLP techniques to implement text understanding and decision-making
  • work with EEG data to implement student’s confusion classifier with respect to MOOC’s
  • implement human personality classifier based on online forums conversation using Myers Briggs Personality types
  • describe five dimensions commonly used to describe human personality and psyche
  • implement an interactive chat-bot capable of simple conversation
  • summarize the key concepts covered in this course

Overview/Description

Practice plays an important role in AI development and helps one get familiarized with commonly used tools and frameworks. Knowing which methods to apply and when is critical to completing projects quickly and efficiently. Based on code examples provided, you will be able to quickly learn important cognitive modeling libraries and apply this knowledge to new projects in the field. In this course, you'll learn the essentials of working with cognitive models in a software system. First, you will get a detailed overview of each type of learning used in cognitive modeling. Further, you will learn about the toolset used for cognitive modeling with Python and recall which role cognitive models play in AI and business. Finally, you will go through various cognitive model implementations to develop skills necessary to implement cognitive modeling in real world.



Target

Prerequisites: none

Cognitive Models: Overview of Cognitive Models

Course Number:
it_aiapcmdj_01_enus
Lesson Objectives

Cognitive Models: Overview of Cognitive Models

  • discover the key concepts covered in this course
  • name and describe basic concepts in and cognition and cognitive modeling
  • describe distinct features of adaptive, interactive, iterative, and contextual cognitive models
  • identify different types of cognitive models and name popular cognitive modeling applications
  • specify multiple disciplines involved in cognitive modeling and describe their role
  • describe how cognitive models are used in healthcare and name multiple solutions used in the industry
  • describe how cognitive models are used in neuroscience and name multiple solutions used in the industry
  • describe how cognitive models are used in manufacturing and name multiple solutions used in the industry
  • describe how cognitive models are used in decision making and name multiple solutions used in the industry
  • "describe how cognitive models are used in psychology and name multiple solutions used in the industry "
  • compare cognitive modeling and artificial intelligence
  • recognize major events that shaped the history of cognitivism
  • illustrate how computer science is connected with cognitive modeling
  • summarize the key concepts covered in this course

Overview/Description

To implement cognitive modeling inside AI systems, a developer needs to understand the major differences between commonly used cognitive models and their best qualities. Today cognitive models are actively utilized in healthcare, neuroscience, manufacturing and psychology and their importance compared to other AI approaches is expected to rise. Developing a firm understanding of cognitive modeling and its use cases is essential to anyone involved in creating AI systems. In this course, you'll identify unique features of cognitive models, which help create even more intelligent software systems. First you will learn about the different types of cognitive models and the disciplines involved in cognitive modeling. Further, you will discover main use cases for cognitive models in the modern world and learn about the history of cognitive modeling and how it is related to computer science and AI.



Target

Prerequisites: none

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