Concepts of problem solving using an object-oriented programming language, algorithm design, structured programming, fundamental algorithms and techniques.

Problem solving by programming with an object-oriented programming language. Introduces data structures. Overview of computer science topics.

Register-level computer organization. Instruction set architecture. Assembly language. Processor organization and design. Memory organization. IO programming. Exception/interrupt handling.

Introduces the procedural, object-oriented, functional and declarative languages.

Ethics for computing majors: history of computing, intellectual property, privacy, ethical frameworks, professional ethical responsibilities and risks of computer-based systems.

Advanced data structures and algorithms, including stacks, queues, trees (B, B+, AVL), and graphs. Searching for graphs, hashing, external sorting.

Operating system structure and services, processor scheduling, concurrent processes, synchronization techniques, memory management, virtual memory, input/output, storage management, and file systems.

Formal syntactic and semantic descriptions, compilation and implementation issues, and theoretical foundations for several programming paradigms.

Introduces formal language theory and automata, Turing machines, decidability/undecidability, recursive function theory, and complexity theory.

Software life cycle models; project management, team development environments and methodologies; software architectures; quality assurance and standards; legal, ethical issues.

Concepts of information assurance (IA); basic IA techniques, policies, risk management, administration, legal and ethics issues.

Logic, sets, functions, elementary number theory and combinatorics, recursive algorithms, and mathematical reasoning, including induction. Emphasizes connections to computer science.

Limits and continuity, differential calculus of functions of one variable, introduction to integration.

Methods of integration, applications of calculus, elements of analytic geometry, improper integrals, Taylor series.

Solving linear systems, matrices, determinants, vector spaces, bases, linear transformations, eigenvectors, norms, inner products, decompositions, applications. Problem solving using MATLAB.

Applications-oriented course with computer-based experience using statistical software for formulating and solving engineering problems.

Introduces the engineering design process; working in engineering teams; the profession of engineering; engineering models, written and oral technical communication skills.

Number systems, conversion methods, binary and complement arithmetic, Boolean algebra, circuit minimization, ROMs, PLAs, flipflops, synchronous sequential circuits.

Students will learn about ASU's mission as the New American University, the importance and benefits of an entrepreneurial approach to problem solving, solutions to sustainability challenges, and the importance of social embeddedness. Additionally, through various course discussions and assignments, students will examine the concept of academic integrity and its potential impact on their future, gain awareness of the value of engaging in research activities, and learn about taking an interdisciplinary perspective.