AI B.A. is usually not just an AI student from the first day. The real foundation is still program design, algorithms, linear algebras, calculus, probability statistics and computer systems, extending in the direction of Machine Learning, Deep Learning, NLP, Computer Vision, Robotics, etc.
I. AI Two of the most common structures for B.A.
Computing-based： First, the core of Computer Science will be bottomed and then added year after year to Machine Learning, Deep Learning, NLP, Computer Vision, Robotics. Imperial's Commanding (Artificial Inteligence and Machine Learning) is this kind of structure.
Math + Computing： More mathematically, the emphasis will be on Calculus, Linear Algebra, Probability, Statistical Modeling, and the combination of Machine Learning and Software Engineering. Such courses are suitable for students with a strong mathematical base.
Two, AI, Computer Science, Data Science. What's the score?
- Computer Science： Most widely, including algorithms, systems, software, databas, networks, AI.
- Artificial Intelligence： It's more focused on learning, reasoning, making, language, robotics.
- Data Science： It's more heavy, it's bigger, it's bigger, it's bigger, it's bigger, it's bigger, it's bigger, it's bigger, it's bigger, it's bigger, it's bigger, it's bigger, it's bigger, it's bigger, it's bigger, it's bigger, it's more like, it's more like, it's more, it's more, it's more, it's more, it's more, it's more, it's more, it's more, it's more, it's more, it's more, it's more, it's more, it's more, it's more, it's more, it's more, it's more, it's more, it's more, it's more, it's more, it's more, it's more.
III. How to prepare for high school?
The most important thing is math. If the target is a stronger AI/Communication course in the UK or Canada, special attention is paid to Mathematics, Calculus, and the mathematical requirements of progress. Program design experience is very helpful, but not "ChatGPT" as an AI academic preparation.
For what students?
Those who prefer abstract logic, mathematics, programming, repeated error-cutting, and are willing to understand why models work or fail are better suited. If you only like AI applications, but don't like math and coding, you can look at Business Analytics, AI in Business or Digital Business.
V. Common career
Machine Learning Engineer、AI Engineer、Data Scientist、NLP Engineer、Computer Vision Engineer、Software Engineer、Research Engineer。 A master ' s degree or doctorate is usually required for a research career.
