Brief Introduction
At the conclusion of this class, you will be able to accomplish three primary tasks. First, you will be able to design and implement a knowledge-based artificial intelligence agent that can address a complex task using the methods discussed in the course. Second, you will be able to use this agent to reflect on the process of human cognition. Third, you will be able to use both these practices to address practical problems in multiple domains.Course Summary
This course introduces students to the field of Knowledge-Based AI and Cognitive Systems, which combines concepts from Artificial Intelligence, Cognitive Science, and Neuroscience to create intelligent systems that can understand and reason about the world.Key Learning Points
- Learn the fundamentals of Knowledge-Based AI and Cognitive Systems
- Understand how to apply these concepts to real-world problems
- Gain hands-on experience with programming assignments
Related Topics for further study
Learning Outcomes
- Understand the fundamentals of Knowledge-Based AI and Cognitive Systems
- Be able to apply these concepts to real-world problems
- Gain hands-on programming experience
Prerequisites or good to have knowledge before taking this course
- Basic programming experience
- Familiarity with Artificial Intelligence concepts
Course Difficulty Level
IntermediateCourse Format
- Online
- Self-paced
Similar Courses
- Intro to Artificial Intelligence
- Machine Learning Engineer
Related Education Paths
Notable People in This Field
- Dr. Jane Smith
- Dr. Mark Johnson
Related Books
Description
The twin goals of knowledge-based artificial intelligence (AI) are to build AI agents capable of human-level intelligence and gain insights into human cognition.Requirements
- A good course on computer programming such as CS 1332 or Udacity’s CS 101 is beneficial for students. An introductory course on Artificial Intelligence, such as Georgia Tech's CS 3600 or CS 6601, is recommended but not required. To succeed in this course, you should be able to answer 'Yes' to the following four questions: Are you comfortable with computer programming? Are you familiar with concepts of data structures and object-oriented programming, such as inheritance and polymorphism? Are you familiar with concepts of algorithms, such as sorting and searching algorithms? Are you confident with either Java or Python? See the Technology Requirements for using Udacity.
Knowledge
- Instructor videosLearn by doing exercisesTaught by industry professionals
Outline
- lesson 1 Introduction to KBAI and Cognitive Systems Where Knowledge-Based AI fits into AI as a whole Cognitive systems: what are they? AI and cognition: how are they connected? lesson 2 Fundamentals Semantic Networks Generate & Test Means-Ends Analysis Problem Reduction Production Systems lesson 3 Common Sense Reasoning Frames Understanding Common Sense Reasoning Scripts lesson 4 Planning Logic Planning lesson 5 Learning Learning by Recording Cases Incremental Concept Learning Classification Version Spaces & Discrimination Trees lesson 6 Analogical Reasoning Case-Based Reasoning Explanation-Based Learning Analogical Reasoning lesson 7 Visuospatial Reasoning Constraint Propagation Visuospatial Reasoning lesson 8 Design & Creativity Configuration Diagnosis Design Creativity lesson 9 Metacognition Learning by Correcting Mistakes Meta-Reasoning AI Ethics
Summary of User Reviews
Discover the world of Knowledge-Based AI and Cognitive Systems with this comprehensive course on Udacity. Students have rated this course highly for its in-depth coverage of the subject matter and engaging instructor. Many users have praised the practical applications of the course material, making it a great choice for anyone looking to develop their AI skills.Key Aspect Users Liked About This Course
Practical applications of the course materialPros from User Reviews
- In-depth coverage of the subject matter
- Engaging and knowledgeable instructor
- Real-world examples and applications
- Interactive quizzes and exercises
- Clear and concise explanations
Cons from User Reviews
- Some users found the course material to be too advanced
- Limited opportunities for interaction with other students
- Lack of hands-on projects
- Some technical issues with the online platform
- Course content may become outdated quickly
Data Science & Machine Learning(Theory+Projects)A-Z 90 HOURS
- 4.3
-
![]()
![]()
![]()
![]()
![]()
Mastering Data Science & Machine Learning using Python-A to Z-Learn Statistics, Preprocessing & Reinforcement Learning Comprehensive Course Description: Fast forward to today....
Teaching Impacts of Technology: Data Collection, Use, and Privacy
- 4.6
-
![]()
![]()
![]()
![]()
![]()
By the end, you’ll be prepared to teach pre-college learners to be both savvy and effective participants in their digital world....
Using GPUs to Scale and Speed-up Deep Learning
- 0.0
-
![]()
![]()
![]()
![]()
![]()
Training complex deep learning models with large datasets takes along time. Enroll to learn more, complete the course and claim your badge!...
Microsoft Azure Management Tools and Security Solutions
- 4.7
-
![]()
![]()
![]()
![]()
![]()
Microsoft Azure offers a wide range of services to deploy your applications. Some modules cover software development processes and services. AI Services & Solutions...
