Fundamentals of software engineering using a group project as the basic vehicle. Topics covered include the software crisis, managing complexity, requirements specification, architectural and detailed design, testing and analysis, software process, and tools and environments.

Explores concepts and techniques for design and construction of reliable and maintainable software systems in modern high-level languages: specifications; program structure and design; program-correctness approaches, including testing; and event-driven programming (e.g., graphical user interface).

Covers abstractions and implementation techniques in the construction of distributed systems, including cloud computing, distributed storage systems, and distributed caches.

Techniques for design of efficient algorithms. Methods for showing lower bounds on computational complexity. Particular algorithms for sorting, searching, set manipulation, arithmetic, graph problems, pattern matching.

Includes substantial programming experience in languages that expose machine characteristics and low-level data representation (e.g., C and C++); explicit memory management; modern libraries and language features; interacting with operating-system services; introduction to concurrent programming.

Principal ideas and developments in artificial intelligence: Problem solving and search, game playing, knowledge representation and reasoning, uncertainty, machine learning, natural language processing.

Introduces database management systems and writing applications that use such systems; data models (e.g., relational, semi-structured), query languages (e.g., SQL, XQuery), language bindings, conceptual modeling, transactions, security, database tuning, data warehousing, parallelism, and web-data management.

User interfaces for computing systems, including principles and implementation techniques. Covers key topics and programming paradigms for interactive systems, such as event handling; graphical layout, design, and widgets; undo; accessibility; and context awareness. Provides experience with modern application domains and frameworks (e.g., mobile applications).

Foundations of modern computer security, including software security, operating system security, network security, applied cryptography, human factors, authentication, anonymity, and web security.

Examines fundamentals of logic, set theory, induction, and algebraic structures with applications to computing; finite state machines; and limits of computability.

Examines fundamentals of enumeration and discrete probability; applications of randomness to computing; polynomial-time versus NP; and NP-completeness.

Covers abstract data types and structures including dictionaries, balanced trees, hash tables, priority queues, and graphs; sorting; asymptotic analysis; fundamental graph algorithms including graph search, shortest path, and minimum spanning trees; multithreading and parallel algorithms; P and NP complexity classes.

Algorithmic and analytic techniques underlying analysis of large-scale biological data sets such as DNA, RNA, and protein sequences or structures, expression and proteomic profiling. Hands-on experience with databases, analysis tools, and genome markers. Applications such as sequence alignment, BLAST, phylogenetics, and Markov models.

Examines key computational abstraction levels below modern high-level languages; number representation, assembly language, introduction to C, memory management, the operating-system process model, high-level machine architecture including the memory hierarchy, and how high-level languages are implemented.

Introduction to tools commonly used in software development. Topics include using a command-line interface, writing scripts for file and string manipulation, managing user permissions, manipulating text with regular expressions, using build-management tools, and using version-control systems.