# Computer Science in Data Analytics

#### Bachelor of Science (B.S.)

This STEM program is designed to help students understand data analysis methodologies, as well as to appreciate, visualize, describe and analyze data.

## A high-demand profession

The labor market demand for computer science degrees and related disciplines is growing substantially

— glassdoor

## CSDA Courses

The core courses in the CSDA major comprise a 15-unit core in common with the Applied Computer Science program. The curriculum also includes the core of mathematics courses required of majors in mathematics, sciences, engineering and technology

#### Lower Division Courses

Analytic Geometry and Calculus I
This course covers limits, derivatives, applications of differentiation, integrals, and the fundamental theorem of calculus. Proofs of primary calculus theorems are reviewed Prerequisite: PreCalculus with a grade of “C” or better.

Analytic Geometry and Calculus II
Techniques of integration, numerical integration, improper integrals and applications of the integral. Taylor polynomials, sequences and series, and power series. Prerequisite: Analytic Geometry 1 with a grade of “C” or better.

Linear Algebra
Applications of linear equations, matrices, determinants, eigenvectors and vector spaces in the mathematics of social sciences. Prerequisite: Analytic Geometry II.

Discrete Math
An introduction to the mathematics needed in computer science. Logic and boolean algebra, discrete logic circuits (apps of and/or/nor), number systems, proofs, set theory, matrix theory, counting methods, discrete probability, sequences, induction, recursion, counting, and graph theory (including tree)s. Prerequisite: PreCalculus with a grade of “C” or better.

Multivariable Calculus
Functions in multiple variables; partial differentiation, multiple integrals, and vector calculus.

Introduction to Programming I
This studio course serves as a practical introduction to the fundamentals of computational media with emphasis on code as the language of computing. No prior background in computer programming is assumed as the course covers basic concepts of syntax, code structure, programming constructs, algorithms, data organization and computer applications. Concepts such as procedural animation, generative graphics and interaction will be explored using a creative coding approach. Students will complete weekly programming assignments, culminating in an original semester project that elaborates on the concepts and techniques covered in the course. Prerequisite: None.

Introduction to Programming II
This course introduces intermediate programming concepts through the construction of interactive experiences for the web by building on programming fundamentals learned in the introductory programming course. Students will learn software design patterns, synchronous and asynchronous programming, unit testing, version control, hosting, data formats and how to work with an API. Students will create interactive works using a variety of back-end and front-end technologies. Possible projects include interactive data visualization, networked games, and responsive design.

Data Structures and Algorithms (Lab, 3 units)

Windows-Based Application Development

Database Design and Programming
The study of relational database systems. Topics include standard query language (SQL), the relational model, security, normalization, functional dependency and entity relationship diagrams, database design, recovery, transaction processing, ethics, and client server systems. The course also covers DBMS packages, report generators, and the use of Visual Studio and .NET languages as a front-end to database systems.

#### Upper Division Courses

Artificial Intelligence

Advanced Data Structures and Algorithm Analysis

Probability and Statistics I

Probability and Statistics II
Estimation theory, hypothesis testing, linear regression, and correlation and analysis of variance. Prerequisite: MATH 3xx (Probability and Statistics I)

This course explores advanced topics in client server and database development. It covers the programming and administration of database systems and includes views, stored procedures, triggers, indexes, constraints, security, roles, logs, maintenance, transaction processing, XML, reporting, and other relevant topics. Students will be exposed to several database packages and will do considerable database programming. Prerequisite: Database Design and Programming.

Data Mining
Introduction to basic concepts behind data mining. Survey of data mining applications, techniques and models. Discussion of ethics and privacy issues with respect to invasive use. Introduction to data mining software suite. Prerequisite: Advanced Database Development.

#### Electives

Combinatorics

Statistics
This course will introduce students to statistical methods and practices which are most relevant to the analysis of financial and economic data. Topics include autoregressive models, moving average models, and their generalizations. The course develops models that are closely focused on particular features of financial series such as the challenges of time dependent volatility. Prerequisites: Mathematical Statistics 2 and Linear Algebra both with a grade of “C” or better.

Spatial and Geo Statistics
Topics cover practical spatial and geostatistical analysis, including spatial and temporal autocorrelation, point patterns, interpolation, and multivariate analysis. Prerequisites: Mathematical Statistics 2 and Linear Algebra both with a grade of “C” or better.

Topics in Mathematical Statistics

Topics in Probability and Statistics
This course will cover topics in probability and statistics not covered elsewhere in the program. Part A is usually devoted to multivariate statistics, Part B to stochastic processes, and Part C to probability theory. Part D is left to a topic chosen by the individual instructor. Prerequisites: Mathematical Statistics 2 and Linear Algebra both with a grade of “C” or better.

— TechTarget