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Data science is multifaceted and can be described as a science, a research paradigm, a research method, a discipline, a workflow, and a profession. [4] Data science is "a concept to unify statistics, data analysis, informatics, and their related methods" to "understand and analyze actual phenomena" with data. [5]
Artificial intelligence engineering (AI engineering) is a technical discipline that focuses on the design, development, and deployment of AI systems. AI engineering involves applying engineering principles and methodologies to create scalable, efficient, and reliable AI-based solutions.
Artificial intelligence (AI), in its broadest sense, is intelligence exhibited by machines, particularly computer systems.It is a field of research in computer science that develops and studies methods and software that enable machines to perceive their environment and use learning and intelligence to take actions that maximize their chances of achieving defined goals. [1]
Formal methods are best described as the application of a fairly broad variety of theoretical computer science fundamentals, in particular logic calculi, formal languages, automata theory, and program semantics, but also type systems and algebraic data types to problems in software and hardware specification and verification.
Academic programs vary between colleges, but typically include a combination of topics in computer science,computer engineering, and electrical engineering. Undergraduate courses usually include programming, algorithms and data structures, computer architecture, operating systems, computer networks, parallel computing, embedded systems, algorithms design, circuit analysis and electronics ...
Game theory – Useful in artificial intelligence and cybernetics. Discrete mathematics - Study of discrete structures. Used in digital computer systems. Graph theory – Foundations for data structures and searching algorithms. Mathematical logic – Boolean logic and other ways of modeling logical queries; the uses and limitations of formal ...
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