IIntroduces programming concepts within social, cultural, scientific, mathematical, and technological context. Topics include programming fundamentals (control structures, data types and representation, operations, functions and parameters), computer organization, algorithmic thinking, introductory software engineering concepts (specifications, design, testing), and social and professional issues.
IITransition from basic programming skills to a rigorous process of software development. Familiarization with higher level programming techniques (recursion, generic programming, stacks, queues, trees, searching, and sorting). Emphasizes connection between algorithmic thought and implementation.
Surveys the software engineering processes, tools, and techniques used in software development and quality assurance. Topics include life-cycle models, process modeling, requirements analysis and specification techniques, quality assurance techniques, verification and validation, testing, project planning, and management.
IIntegrating mathematical principles with detailed instruction in computer programming. Explores mathematical reasoning and discrete structures through object-oriented programming. Includes algorithm analysis, basic abstract data types, and data structures. May not be repeated.
Principal ideas and developments in artificial intelligence, such as problem solving, knowledge representation, search, reasoning under uncertainty, learning, and natural language processing.
Explores the most effective methods of communication based on the common expectations for computing and other engineering professionals. Examines various writing patterns commonly used in technical writing, including compare/contrast, persuasive, process, instructions, and problem/solution, and when/why is used.
IIDevelops competencies associated with problem-solving, algorithms, and computational models. Explores algorithm development and analysis; abstract data types including trees, priority queues, heaps, graphs, and hash tables; use of object-oriented design/programming and design patterns; regular expressions; and language modeling.
Basic machine learning (ML) and artificial intelligence (AI) methods and the related techniques used in modern AI systems. Students learn about both the theory of the algorithms and the challenges of implementing them in a modern programming language.
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