Education

Computer science curriculum covering algorithms, data structures, software engineering, and systems.

Foundation in business principles, economics, accounting, and quantitative methods aligned to transfer pathways.

Hands-on coverage of DynamoDB data modeling, APIs, indexes, and performance patterns for developers.

Overview of core AI concepts including search, knowledge representation, and basic machine learning approaches.

Core JavaScript concepts and modern syntax for building interactive, client-side applications.

Algorithm analysis and core data structures including sorting, trees and graphs (BFS/DFS, topological order, MST), plus regex parsing and hash tables.

Low-level programming and computer organization: instruction sets, memory, addressing, procedures, I/O, and performance-aware assembly.

Software lifecycle practices: requirements, design, testing, and teamwork using version control and modern development processes.

Systems programming in C/UNIX: processes, threads, files, memory, concurrency, and interprocess communication.

Design and analysis of algorithms: greedy, divide-and-conquer, dynamic programming, advanced graph algorithms, and complexity.

Introductory AI: state-space search, knowledge representation and reasoning, and basic machine learning concepts.

Database fundamentals: relational model, SQL, schema design and normalization, transactions, indexing, and query processing.

Syntax, semantics and computation models of programming languages. Formal foundations of major programming paradigms and in-depth study of key features of high-level programming languages from each paradigm.