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BDS1100 Storytelling with Data
3 Credits
This course introduces students to building and effectively presenting compelling narratives and stories with data for multiple audiences. It acquaints and takes students to the life-cycle of a data science project. Students work with case studies, examples, and data visualization tool kits, and practice with different strategies and techniques for building visual analytics and stories that can help organizations and individuals with better decisions or social impact.
BDS2240 Programming for Computer Science and Data Science
3 Credits
This course is designed to provide students with the skills necessary to use Python programming for computer science and data science projects. This course is designed to give students fundamental programming skills, and show how to utilize python to manipulate data in ways commonly used in data science practice and applications with a focus on use cases.
Prerequisite: BDS1100 Storytelling with Data
BDS2260 Machine Learning
3 Credits
This course introduces students to the theory and applications of machine learning concepts and algorithms. It covers key topics in machine learning including both supervised and unsupervised learning algorithms. The key topics will include linear models for regression and classification, decision trees, support vector machines and kernel methods, ensemble methods, unsupervised learning, and dimension reduction. We will apply these algorithms to solve problems with real data.
Prerequisite: BDS2240 Programming for Computer Science and Data Science
BDS3360 SQL and Managing Data
3 Credits
This course is designed to help students develop proficiency in database design and gain knowledge of SQL programming. Additionally, students will be introduced to NoSQL database systems optimized for big data analytics. This course will demonstrate how a relational database coupled with efficient programming can help data scientists to effectively manage data and deliver accurate and reliable resultsPrerequisite: BDS2240 Programming for Computer Science and Data Science
BDS4410 Data Security and Privacy
3 Credits
This course introduces students to the concepts, tools, trends, and technologies for data and application security. The focus will be on examining data and information security methodologies for the control, protection, and access as well as the preservation of the integrity of the data. Topics covered will include secure databases and distributed systems, privacy, confidentiality, and trust management, and cybersecurity
Prerequisite: BDS3360 SQL and Managing Data
BDS4483 Data Science Internship
3 Credits
Allows students to work in a position related to Data Science. The internship experience is about exploring and understanding data science needs and practices within a real-life organizational context. Students integrate the skills and knowledge learned through their academic experiences and reflect on it in focused reflective online discussions/projects.
Prerequisite: Department permission
BDS2210 Artificial Intelligence
3 Credits
This course aims to introduce students to some basic concepts, techniques and a variety of applications of artificial intelligence. The course begins by discussing the processes and limits of human decision-making and learning in combination with AI systems. This course will include hands-on exercises and the final project, groups of students will create an AI-based application.
Prerequisite: BDS1100 Storytelling with Data
ITM3330 Object-Oriented Programming
3 Credits
Provides an introduction to the principles of computer programming using a current programming language such as Visual Basic, NET, C++, or Java. This course is a beginning programming course and focuses on basic principles of object-oriented design
Prerequisite:
BDS4440 Advanced Programming for AI and Big Data
3 Credits
This course is designed to provide students with advanced machine learning and Python programming skills to learn today’s most compelling leading-edge computing technologies including AI, big data and cloud case studies on natural language processing, IBM Watson cognitive computing, machine learning, deep learning, computer vision, Hadoop, Spark and the internet of things.
Prerequisites: BDS2240 Programming for Computer Science and Data Science, and, BDS2260 Machine Learning
BDS4450 Applied Deep Learning and Chatbots
3 Credits
Chatbots have come and transformed the way we have been conducting online business. At this time, this course aims to introduce students to the concepts and applications of deep learning and theories behind AI-powered Chatbots and introduce them to the tool kits for building and implementing Chatbots.
Prerequisite: BDS2241 Artificial Intelligence
BUS2210 Business Intelligence and Analytics
3 Credits
Introduces students to the fast-growing field of business intelligence and analytics. The course provides students with a general understanding of quantitative methods, analytical software, and data analysis to help them comprehend and analyze contemporary business issues and problems. The emphasis is placed on critical thinking and quantitative reasoning skills.
ITM2260 IT Project Management
3 Credits
IT projects face unique challenges for all project team members, and most of all, for the project manager. This course is designed along the IT project management lifecycle. Topics entail the basic concepts of IT project management, including initiating, planning, controlling, executing, and closing projects. The course also shows students how IT projects should be managed, from inception to post-implementation review. Students will use Microsoft Project software.
ITM3313 Cloud Computing
3 Credits
The Cloud Computing course introduces underlying concepts of cloud models, virtualization, infrastructure, security, resource management, and business continuity. Emphasizes terminology and technologies in Cloud environments and provides a general overview of the field of Cloud Computing in business and technology.
Prerequisite:
BUS4420 Data Mining for Business Analytics
3 Credits
This course provides an overview of the fundamental principles and techniques of data mining for business analytics. We will examine case studies to place data-mining techniques in context and to develop data-analytic thinking. Emphasis will be placed on real-world applications to illustrate that proper application of data-mining in business analytics is as much an art as it is a science. In addition, we will work "hands-on" with analytics/data mining software.
Prerequisites: BUS2210 Business Intelligence and Analytics