Department Requirements -Data Science
1) CCDS 211 Introduction to Data Science
This course provides foundation in the area of data science concepts and techniques based on data statistical analysis. The primary goal of this course is for students to learn data analysis concepts and techniques that facilitate making decisions from a rich data set. Students will learn about different concept, techniques, and tools that allow them to extract knowledge from data
2) CCDS 221 Data Warehousing
In the modern world, information technology is ubiquitous, resulting in the collection of massive quantities of data. Many organizations hope that, through the analysis of the data they have collected, they can gain new insights that will allow them to be more effective in accomplishing their goals. However, the analysis of large data sets poses many challenges: How can data from disparate sources be organized in a coherent manner? How can datasets that are many gigabytes in size be efficiently queried? What are the right questions to ask about the data in order to yield useful insights?
3) CCDS 223 Data Mining
Data mining is concerned with the extraction of novel information from small or large amounts of data. This is in addition to understanding different types of data and how each type could be handled. Preprocessing data and dealing with outliers is also one of the concerns of data mining. This course introduces and studies the concepts, issues, tasks and techniques of data mining
4) CCDS 313 Business Intelligence
The course introduce students to decision-making and analytics. The course further introduce student to the concept of data warehouse, data mining, and expert systems as central elements to Business Intelligence and used as a tool for further analysis in Big Data.
5) CCDS 321 Big Data Analytics
The concept of Big Data refers to massive and often unstructured data that needs special processing capabilities and data management tools. This course is concerned with storage of big data including NoSQL data stores and corresponding data retrieval mechanisms. In addition, it will cover big data analytics algorithms and tools.
6) CCDS 323 Multimedia Data Analysis
With the advancement in the information and communication technologies, multimedia streams (photos, music, video) are becoming vitally important information sources. To cope with the huge and diverse data and to extract valuable information from multimedia data, there arise thought provoking theoretical problems and industrial needs. This course will introduce the students, knowledge of basic multimedia elements (text, sound, image, video, animation) and the hardware, software and files used in the multimedia technology. The course introduces the students, principles and modern technologies of multimedia systems, issues in effective representation, processing, and communication of multimedia data. The students will get hands-on experience for performing multimedia contents analysis, multimedia indexing and retrieval and multimedia data mining.
7)CCDS 411 Senior Project 1
This course is the first part of a sequence of two courses that constitute the graduation capstone project. In this course the students integrate the knowledge areas they learnt into a development based project in which they will deliver proposals, reports, and oral presentations. The course topics cover planning, analysis, and design phases of the projects.
8) CCDS 413 Information Retrieval
The course will cover basic information retrieval concept such as the organization, representation, access and maintenance of information in digital environment. The course will also explore and expose the students to advanced techniques in building text-based information system and search engines projects.
9) CCDS 421 Senior Project 2
This course is the second part of a sequence of two courses that constitute the graduation capstone project. In this project, the student will continue the system/research development of the project that started in CCDS 411. The student will deliver oral presentations, progress reports, and a final report.
10) CCDS 423 Data Integration
Combing data from multiple heterogenous data sources to offer an integrated data system is critical to many applications. The course covers various topics related to data integration such as data acquisition, processing, schema matching/mapping, data cleaning, semantics, source modeling, and fusion of data from heterogeneous data sources to support decision making. The students will be working on team projects and will use tools covered in the class.
11) CCDS 311 Data Visualization
In this course, the students will be introduced to visualization techniques for data coming from different sources. To get a better understanding of the visualization techniques, the students will be introduced to the information perception model of Human Visual System (HVS). Visualization techniques for different types of data such as spatial and geospatial data, time-series, trees and graphs, and text and documents will be explained. Some concepts of interactive visualizations will be introduced. The course provides hands-on experience of applying the learned techniques on different datasets through exercises in lab and a team-project.
1) CCDS431 Social Web Analysis
The course is focusing on the understanding of how social media analytics integrates and affects other area of business. The course will explore the main layers of social media analytics – text, actions, networks, hyperlinks, mobile applications, and search engine and location data. Student will also be exposed to the legal, privacy and security issues of social media.
2)CCDS 433 Biomedical Science and Healthcare Application
Biomedical data is becoming increasingly diverse and complex. Big Data, as this has been called, creates many new challenges, as well as new opportunities. Biomedical Data Science applies concepts and methods from computer science and other quantitative disciplines together with principles of information science to solve challenging problems in biology, medicine, and public health. This course intended to prepare students to deal with the structure, acquisition and use of medical/health information. This course provides basic understanding of generating data-driven solutions through comprehension of complex real-world health problems, employing critical thinking and analytics to derive knowledge from data. The course focuses on the development of tools for data preprocessing, storage, extraction of valuable information, data analysis and visualization techniques for medical decision-making.
3) CCDS 435 Database Administration
This course will help students to explore advanced concepts of databases in context of design, administration and applications. Topics included in this course are: database architecture, modeling, designing, implementation, backup and recovery procedures, security, change management and performance management.
4) CCDS 437 Introduction to Geographic Information System
This course provides an overview of the theoretical foundations and the applied use of Geographic Information Systems (GIS). At the end of the course, students will have a working knowledge of GIS and how to apply it in various situations and organizational settings. Students demonstrate their understanding of the principles and fundamental concepts of GIS in a culminating project.
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