This course includes materials on AI programming, logic, search, game playing, machine learning, natural language understanding, and robotics, which will introduce the student to AI methods, tools, and techniques, their application to computational problems, and their contribution to understanding intelligence. The material is introductory; the readings cite many resources outside those assigned in this course, and students are encouraged to explore these resources to pursue topics of interest. Upon successful completion of this course, the student will be able to: Describe the major applications, topics, and research areas of artificial intelligence (AI), including search, machine learning, knowledge representation and inference, natural language processing, vision, and robotics; Apply basic techniques of AI in computational solutions to problems; Discuss the role of AI research areas in growing the understanding of human intelligence; Identify the boundaries of the capabilities of current AI systems. (Computer Science 405)
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This unit will help you to understand the forms of data that are handled by software and look at the various processes that can be applied to the data. These ideas are demonstrated through the use of a supermarket till and illustrate how simple data sets can be manipulated.
The internet provides a world of information, but how do you find what you are looking for? This unit will help you discover the meaning of information quality and teach you how to evaluate the material you come across. You will learn how to plan your searches effectively and be able to experiment with some of the key resources in this area.
Quantum computing has the potential to solve some of the world’s most complex problems. So how are quantum computers different from the traditional computers...
- Author:
- IBM Think Academy
Unified theory of information with applications to computing, communications, thermodynamics, and other sciences. Digital signals and streams, codes, compression, noise, and probability. Reversible and irreversible operations. Information in biological systems. Channel capacity. Maximum-entropy formalism. Thermodynamic equilibrium, temperature. The Second Law of Thermodynamics. Quantum computation.
- Subject:
- Biology
- Life Science
- Material Type:
- Full Course
- Textbook
- Author:
- Lloyd, Seth
- Date Added:
- 01/01/2008
The focus of the course is on medical science and practice in the age of automation and the genome, both present and future. It includes an analysis of the computational needs of clinical medicine, a review systems and approaches that have been used to support those needs, and an examination of new technologies.
- Subject:
- Applied Science
- Computer Science
- Health, Medicine and Nursing
- Material Type:
- Full Course
- Textbook
- Author:
- Ohno-Machado, Lucila
- Date Added:
- 01/01/2003