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Big Data Needs Big Answers
With more and more data collected every day, the demand for data analytics experts is booming. In nearly every industry, critical thinking and keen analytical skills are required to define, discuss, and solve complicated problems. Collecting, managing, analyzing, disseminating, and making decisions based on vast amounts of information is the challenge and excitement of this ever-evolving profession.
With an MSBDA from LTU, you’ll develop the accelerate your career in a field projected to grow much faster than average for all occupations.
Course Name
Course #
Credits
This course will introduce the basic concepts of data analytics as applied in various business contexts. After learning the basic concepts, students will learn how to differentiate between various topics such as statistical analysis, data mining, business intelligence, business analytics, and data science to describe which approach is most suitable given a certain problem. Finally, students will gain exposure to the various tools and programming languages that are relevant to both business and data analytics, and how these tools yield critical analysis leading to improved business decisions.
MBA6103
3
This course introduces students to the strategic and operational uses of information systems. The use of information systems is examined for achieving and maintaining competitive advantage, as well as managerial issues concerning the development, implementation, and management of enterprise information systems. Case studies address the impact of information systems on the organization, the challenges involved in managing technological change in organizations, and the impact of emerging technologies. Students will develop a socio-technical perspective on the use of information systems to solve real-world problems.
INT6043
3
This course is designed to introduce students with little or no prior programming experience to the art of programming through the lens of exploring data. Students will build a core foundation in the Python programming language as well as data analysis and visualization. This course is a hands-on, experiential class that students learn by solving actual business problems using Python under the guidance of the instructor. Topics will include programming fundamentals and logic such as variables, input & output, control structures, functions, data types, data manipulation, and object-oriented concepts. Students will apply the Python programming language and essential data science techniques to solve various problems. At the
end of this course, students will complete a final project as a team which cohesively ties together all the covered concepts.
INT6103
3
This course covers the principles, practices, design, and development of database management systems (DBMS) with an emphasis on the relational
database systems. More specifically, it focuses on logical modeling, physical data modeling, normalization, and database query languages. Additionally, this course will explore database implementation, concurrency control, Data models, normal forms, relational systems, object-oriented systems, object-relational systems, transaction processing and even business intelligence and data warehousing. This course emphasizes on hands-on skills. Students are required to use database applications to practice database design and implementation through assignments exercises and conduct a class project involving the data modeling, database development and implementation.
INT6113
3
This class is an introductory undergraduate course, and it provides a broad introduction to machine learning algorithms, principles, models and techniques. It covers topics in learning theory, dimension reduction, classification, clustering, Bayesian theory, support vector machines, neural networks, deep learning, and reinforcement learning. The course is a programming-focused introduction to Machine Learning and students will gain practical experience by conducting a project and using the algorithms and methods introduced in the course to solve real-world problems. By the end of the course, students will have developed practical skills in building learning models, deploying and evaluating their performances.
INT6203
3
Business Analytics and Intelligence (BA&I) are applications and technologies can be used to analyze data to improve business performance through fact-based decision-making. The demand for building and managing BA&I systems in today’s very competitive and challenging economy is high. This course is designed to provide in-depth Business Analytics knowledge of handling data and Business Intelligence tools that can be used for fact-based decision-making. The class will be hands-on and the emphasis will be placed on the “know-how” aspect – how to extract and apply business intelligence to improve business decision making. This course will cover the complete lifecycle for building, deploying and managing BA&I systems including defining and analyzing the business opportunity, creating a dimensional model, designing the ETL process, developing the data warehouse solution, and supporting the BI solution.
INT7213
3
In this course, students will learn the basics of analysis of social media data, using R programming language. Students will use R for techniques such as sentiment analysis in order to gain behavioral insights from social media data utilizing various application programming interfaces (API), and will take a critical approach to the benefits and limits of such analysis.
INT6303
3
This course is an introduction to grounded principles and techniques of design, cognition, perception, and human-computer-interaction for visualizing data interactively. Today, the amount of digital data has grown exponentially, which poses a major challenge for business to manipulate and analyze data efficiently. To gain useful insight from business data, the visual analytics techniques have drawn attention to the public. The major goal of this course is to teach business students, typically nonprogrammers, how to use visualization techniques to analyze big data. Students will work as groups and learn a wide array of visualization methods and be able to apply the techniques to our everyday life or research problems.
INT7253
3
The emergence of massive datasets containing millions or even billions of observations provides the primary impetus for the business analytics field. Such datasets arise, for instance, in large-scale retailing, supply chain network, marketing channel, and social media. This course will emphasize theoretical foundation of business analytics and practical techniques for working with business data to support decision making. Specific topics covered will include statistical modeling, machine learning, predictive modeling, text mining, web mining, social network analytics in real world topics and case studies. The use of statistical and data manipulation software and basic programming skills will be required.
INT7623
3
This graduate course will expose students to the digital marketing fundamentals and provide a solid foundation in the key concepts around this constantly changing field. Through a combination of readings, lectures, case studies, and course projects, students will develop knowledge of online social media and networks, mobile marketing, publishing blogs, rules of engagement, publishing podcasts, and mobile computing. Students will exit the course with a solid understanding of digital marketing tactics, tools, and social media marketing plans. The case study method of learning utilized in this course will allow students to learn digital marketing from a practical perspective. Topics include: why social media?, goals and strategies, identifying target audiences, rules of engagement for social media, publishing blogs publishing podcasts and webinars, publishing articles, white papers, and e-books, sharing videos, sharing photos and images, social networks, microblogging, discussion boards, social news, and Q&A sites mobile computing and location marketing, social media monitoring, social media marketing plan.
MBA7073
3
Total Credits:
30
Application to College of Business and Information Technology MSBDA Program must possess an undergraduate degree from an accredited university or its equivalent in another country.
Students seeking admission into the MSBDA program may be admitted on a regular or conditional basis. The admissions committee will review the student’s educational background and work experience to determine the student’s admission status based on the following criteria:
All international students must follow the same application process mentioned above in addition to the following:
Proof of English Proficiency
If English is not your native language, English proficiency requirements can be fulfilled with one of the following:
Students must submit a Graduate Transfer Credit Request form along with course descriptions, syllabi, and transcripts before completing their first semester. Up to 12 credits may be transferred for the MBA program and up to 9 credits for MSIT and MSBDA programs, provided the courses are graduate-level, from an accredited university, and completed within the last 7 years with a minimum grade of 3.0. Pass/fail courses are not accepted. Additional documentation or proficiency exams may be required.
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