Master of Science

Curriculum

Practical Curriculum

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In this two-year program, MS students need to complete a total of 45 credit hours, consisting of
15 credits for core, 9 credits for specialization, and 21 credits for electives.

Students are strongly advised to read course descriptions, identify pre-requisites and plan the sequence of their progress through the program. They may consult their mentors and faculty members in such planning. SolBridge also provides the opportunity for students to take non-credit foreign language classes to prepare them for a globalized yet diverse world.

  • FIRST YEAR SECOND YEAR
    Fall Semester Spring Semester Summer/Winter Fall Semester Spring Semester Summer/Winter
    CREDITS 9 9 6 9 9 3
    CORE Business Economics Marketing Management
    Managerial Skills Regression Analysis with R for Business
    Statistical Analysis
    ELECTIVES Elective Electives (2) Electives (3) Elective
    SPECIALIZATION Specialization courses

    * Required Courses (graduation requirement for regular students).

Core Courses

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Core Courses Credits
Business Economics ▼
This is an introductory course in statistics designed to provide students with the basic concepts of data analysis and statistical computing. Topics covered include Credit Hours: 3 SolBridge 2021 MS in Marketing Analytics curriculum basic descriptive measures, measures of association, probability theory, confidence intervals, and hypothesis testing. The main objective is to provide students with pragmatic tools for assessing statistical claims and conducting their own statistical analyses.
3
Managerial Skills ▼
This course introduces the student to the basic skills for managing people and organizations as well as how to understand different backgrounds of different people so that they can communicate each other. The course deals with motivation, individual and group decision-making, conflict, power and politics, leadership, job design, performance maintenance, organizational environment, organization structure and design, and emerging trends and challenges.
3
Statistical Analysis ▼
This is an introductory course in statistics designed to provide students with the basic concepts of data analysis and statistical computing. Topics covered include basic descriptive measures, measures of association, probability theory, confidence intervals, and hypothesis testing. The main objective is to provide students with pragmatic tools for assessing statistical claims and conducting their own statistical analyses.
3
Marketing Management ▼
The course introduces marketing management theories and concepts involving in the analysis of marketing environment, planning and implementation of marketing programs (product, price, place and promotion) and marketing strategies to attract, satisfy, and retain customers. The course enables students to develop marketing strategies and framework with moral, socially responsible and ethical consideration.
3
Regression Analysis with R for Business ▼
In this course, students will learn what is and how to use regression by analyzing a variety of real world problems. Heavy emphasis will be placed on analysis of actual datasets. Topics covered include: review of probability and statistics; simple linear regression (SLR); multiple linear regression (MLR); inference; dummy variables; asymptotics; further issues on MLR; heteroskedasticity; specification and data problems; limited dependent variables; time series; instrumental variables (IV) and two-stage least squares (2SLS) (optional); simultaneous equations (optional); panel data (optional).
3

Specialization courses

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Specialization courses provide in-depth knowledge in a functional area. Our graduates will thus have expertise in one functional specialization
(i.e. Data Analytics, Financial Technology, Management & Technology, Marketing Analytics and Technology Entrepreneurship & Innovation.)
and will be well-prepared to meet the challenges of a globalized economy.

Study Area Specialization Courses Credits
Data Analytics Exploratory Data Analysis and Visualization ▼
This course provides students with a thorough study of exploratory data analysis and visualization techniques. Exploratory Data Analysis employs a variety of techniques, mostly graphical, that enable the data to reveal its structural secrets and provide new insight into the data. This approach allows the data scientist to discover patterns, to spot anomalies, to test hypothesis and to check assumptions with the help of summary statistics and graphical representations. This course provides hands-on experience in data visualization and summary statistics using real-world data examples.
3
Statistical Modeling and Inference ▼
This course introduces two key components of statistical data analysis – 1) modeling and 2) inference. Analysis of the complex problems arising in practice requires an understanding of fundamental statistical principles together with knowledge of how to use suitable modelling techniques. Computation using a high-level software is also an essential element of modern statistical practice. This course provides students with these skills by giving an introduction to the principles of statistical modeling and inference using the freely available statistical package R.
3
Introduction to Machine Learning ▼
This course introduces several fundamental concepts and methods for machine learning. The objective is to familiarize students with some basic machine learning algorithms/techniques and their applications. The course also covers general principles and approaches related to analyzing and handling big data sets.
3
Financial Technology Strategic Innovation in Fintech ▼
This course extends issues of strategy, innovation and management to the context of modern fintech developments. Students analyze examples of successful innovation to understand the unique challenges, payoffs and rewards in modern fintech industry.
3
Blockchain Technology in Finance ▼
This course introduces students to the use of blockchain technology in financial industry. Emphasis is on the role of blockchain technology in issues of security, integrity and efficiency across the financial services area.
3
Digital Platforms & Online Financial Services ▼
3
Management & Technology FIN 501 Financial Management ▼
This course is an introduction to business finance, corporate financial management and investments. Students gain an understanding of tools and frameworks necessary to analyze financial decisions based on principles of modern financial theory.
3
FIN 500 Accounting & Decision Making ▼
This course is the accumulation, analysis and presentation of a business enterprise’s relevant financial data for creditors, investors, and other external decision makers.
3
INF 500 Management Information Systems ▼
Information Technology (IT) has become a vital part of the operations and management of organizations of every kind and size. Increasingly, the successful manager is the one who knows how to take advantage of this situation by deploying IT in the most effective manner. This course covers the general structure of Information Technology applications and their use. It also delves into the different kinds of information systems that managers are likely to encounter and investigates how to make best use of these systems.
3
Marketing Analytics Exploratory Data Analysis and Visualization ▼
This course provides students with a thorough study of exploratory data analysis and visualization techniques. Exploratory Data Analysis employs a variety of techniques, mostly graphical, that enable the data to reveal its structural secrets and provide new insight into the data. This approach allows the data scientist to discover patterns, to spot anomalies, to test hypothesis and to check assumptions with the help of summary statistics and graphical representations. This course provides hands-on experience in data visualization and summary statistics using real-world data examples.
3
MKT617 Marketing Research ▼
This unit provides a rigorous experience in market research methods and frameworks to guide when which technique is most useful. The course is aimed at individuals whose decision-making is enhanced through marketing research, which transforms “data” into “information.” The unit will introduce types of research, techniques of data collection, evaluation of alternative sources of information, methods for analyzing data and presenting the results
3
MKT 610 Marketing Analytics ▼
The primary objective of this course is to provide students with foundational knowledge and a basic skill set required for a market analyst. This course objective is aligned mainly with “Creative Management Foundation”, one of the SolBridge’s five mission-based goals. It is also supplemented by a variety of real-world examples used in class lectures.
3
Technology Entrepreneurship & Innovation ENT New Venture Creation ▼
This course is designed around two important sections. The first section covers six themes: defining your target industry; defining your target customers; defining the needs and wants of those customers; defining winning product and service solutions; carefully designing a strong business model; determining competitive positioning, and then testing the entire concept against a small population of target customers—all before writing the plan. Think, design, test, and learn are the guiding principles. The second section then focuses on different types of investors and the process for raising capital, creating realistic financial projections, writing a concise but powerful business plan, organizing the venture team, and creating a compelling pitch that speaks to the needs and concerns of investors. This course is also known as ‘business model generation and testing’.
3
ENT652 Small Business Management ▼
This course is designed around three important themes. First, small business owners must understand the need to incorporate the use of technology and e-business as a way to gain a competitive advantage over larger rivals. Technology is omnipresent in today's business world. Small businesses must use it to their advantage. Hence, the course provides practical discussions and examples of how a small business can use these technologies without having extensive expertise or expenditures. Second, small business owners need to understand how their decisions affect cash flow. As the lifeblood of all organizations, cash flow implications must be a factor in all business decision-making. Third, small business owners need to clearly identify sources of customer value and bring that understanding to every decision. Decisions that do not add to customer value should be seriously reconsidered.
3
ENT601 Tech Entrepreneurship & Product Development ▼
This course blends traditional development and entrepreneurship processes encouraging students to consider how technology-based solutions can solve economic and socially oriented problems. The course prepares also students for a more technological approach to product development together with an experience-based introduction into the process of starting a technology company. This course is also known as ‘product design and development’ and ‘design thinking’.
3

Elective Courses

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For detailed information about the elective courses, download this course description file.pdf

Electives Credits Electives Credits
Computer Programming with Python 3 Corporate Finance 3
Computer Programming with R 3 Financial Derivatives 3
Regression Analysis with R for Business 3 Financial Markets and Institutions 3
Database Marketing 3 investment Analysis 3
Data Analytics for Business 3 Mergers &Acquisitions 3
Pricing Analytics 3 Special Topics In Finance 3
Social Media and Digital Marketing 3 Doing Business in China 3
Cybersecurity 3 Doing Business in Korea 3
Database Management 3 Global Strategic Management 3
Digital Business &Innovation 3 International Business in Asia 3
Software Engineering 3 Special Topics in International Business 3
Strategy for Tech 3 Brand Management 3
Business Communication 3 Consumer Behavior and Decision Making 3
Master’s Thesis 3 International Marketing 3
Operations Management 3 Marketing Communications and Advertising 3
Project Management 3 Marketing Strategy 3
Strategic Management 3 Special Topics in Marketing 3

Graduation Requirements

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  • Curricular: 36 credits (18 for core, 15 for electives, and 3 for Capstone Project).
  • Minimum 3.0 out of 4.5 CGPA.

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