About

Artificial Intelligence

OVERVIEW OF WHAT THEY DO  

An Artificial Intelligence (AI) major teaches you about creating intelligent systems that mimic human cognitive functions. You'll learn about algorithms, machine learning, and data analysis. With this knowledge, you can develop AI applications such as virtual assistants, autonomous vehicles, and medical diagnosis systems. Ultimately, you'll be equipped to drive innovation and solve complex problems using AI technology.

Difficulties and concerns in studying Artificial Intelligence:

Mathematical Foundations: AI requires a strong understanding of mathematical concepts such as calculus, linear algebra, probability, and statistics. Students need to grasp complex mathematical theories and techniques to develop and analyze AI algorithms effectively.

Programming Skills: Proficiency in programming languages such as Python, Java, and C++ is essential for AI development. Students must learn how to write efficient and scalable code, implement algorithms, and work with libraries and frameworks used in AI applications.

Deep Learning and Neural Networks: Understanding deep learning concepts, including neural networks, convolutional neural networks (CNNs), recurrent neural networks (RNNs), and deep reinforcement learning, is crucial for AI research and applications. Students must learn how to design, train, and optimize deep learning models for various tasks.

Domain Knowledge: AI is applied in various fields like healthcare, finance, or gaming. Understanding the specific domain you're working in is crucial for developing effective AI solutions. If you lack knowledge in a particular area, it might be hard to apply AI effectively.

Algorithm Complexity and Interpretability: Developing complex AI algorithms and models requires expertise in algorithm design, optimization, and interpretation. AI professionals must navigate the trade-offs between model complexity and interpretability to balance performance and explainability in AI systems.

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Main RIASEC codes: Conventional (C), Investigative (I)
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Conventional (C): Conventional traits are also relevant for AI majors, particularly those involved in AI deployment, implementation, and maintenance in various industries and sectors. AI professionals often adhere to industry standards, best practices, and regulatory requirements when developing and deploying AI systems. They ensure that AI applications meet ethical, legal, and safety standards while maintaining data privacy and security. Conventional skills such as organization, attention to detail, and adherence to guidelines are essential for AI majors to ensure the reliable and responsible deployment of AI technologies.

Investigative (I): Investigative traits are prominent in AI majors due to the field's heavy reliance on research, analysis, and problem-solving. AI professionals delve into complex algorithms, data structures, and mathematical models to develop intelligent systems and algorithms. They investigate patterns, trends, and correlations in data to create AI solutions that can recognize patterns, make predictions, and automate tasks. AI majors require strong analytical skills, critical thinking, and curiosity to explore new technologies and solve challenging problems in AI research and development.

- AI Engineer/Developer
- Data Scientist
- AI Research Scientist

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