Five Courses Found in Artificial Degree Programs
- Concepts in Artificial Intelligence
- Introduction to Machine Learning
- Vision Sensors
- Designing Human-Centered Systems
- Introduction to Deep Learning
Courses in artificial intelligence degree programs can depend a lot on what students need from their programs. From undergraduate to graduate curriculums, the differences in programs often stems from whether a degree is applied or academic in nature. Here are five courses that are commonly found in an artificial intelligence program.
Concepts in Artificial Intelligence
This course is often also known as Introduction to Artificial Intelligence and is the prerequisite course for any further advanced study in the field. Most students will take this course in their first semester. The course is developed for students to learn about the history of artificial intelligence, what an intelligent agent is, game playing, constraint satisfaction problems, and more. Students will also learn by doing hands-on projects and completing research papers. This course is usually not an in-depth look of the field but functions to introduce new concepts to learners.
Introduction to Machine Learning
Most students will have heard of machine learning, but in order to be successful in the field of artificial intelligence, they must also learn this concept. Machine learning is the science of getting computers to work without a program attached to them. It is the technology behind self-driving cars, smartphone assistants, and even web search engines. This course serves as an introduction to the discipline and includes a variety of projects that must be completed individually as well as with a team; case studies and laboratory projects may also be required. Students will most often have to complete prerequisites in math and statistics.
A course in vision sensors focuses on displays and cameras that give the public new visual experiences. This is a course that covers everything from cameras to film equipment to advancements in technology, including solid state drives and the use of cameras in conjunction with other technologies. Students who are interested in working in a specialized field that includes the daily use of cameras will want to complete a course in this discipline. Students are advised that this course will require lab days and these must be completed in order to complete the experiential learning component of the course.
Designing Human-Centered Systems
Designing Human-Centered Systems is a course that focuses a student’s attention on the skills, tools, and concepts needed in order to design systems and software that meets the public’s needs. The core concept of this course is Human-Computer Interaction, the skillset that every professional will need in order to design and improve existing systems for human use. Most students who take this course are not specializing in the field and therefore will only be taught the wider aspects of the field.
Introduction to Deep Learning
Introduction to Deep Learning is not the same as machine learning, although many students believe that they are. This course focuses on deep learning methods that apply to machine translation, image recognition, game playing, and even machine learning. Students will have the opportunity to learn how deep learning algorithms work as well as work on projects that make up the majority of their final grade. There are prerequisites required for this degree, so students are advised to ensure they meet the requirements before attempting to sign up.
The interest surrounding artificial intelligence is only growing; Venture Beat reported last year that Carnegie Mellon University will be the first university in the country to offer an undergraduate degree in the field. With so many students wishing to specialize in the field, it has become important for schools to release more specializations and degrees that center on artificial intelligence. The above five courses can be found in artificial programs all over the country and should be considered required for any student.
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