Speciality Requirements Student must complete 27 credit hours

Course Code	Course Name	Credit Hours	Prerequests
455602	Computer Programming	3
Business Intelligence (BI) Course is a course that encompasses processes, technologies, and tools for transforming raw data into actionable insights, enabling organizations to make informed decisions. This course provides a comprehensive introduction to BI concepts and practices, covering data warehousing, data mining, reporting, and dashboard development. Through hands-on exercises and case studies, students will learn how to leverage BI tools like Tableau, Power BI, or QlikView to visualize data effectively and communicate key findings to stakeholders. Additionally, the course explores emerging trends in BI, including self-service analytics, predictive analytics, and big data integration, preparing students to harness the full potential of data-driven decision-making in modern businesses.
455603	Introduction to Data Science	3
This course offers a deep dive into the dynamic fields of machine learning and data analytics, providing students with the essential knowledge and practical skills to navigate and thrive in today's data-driven world. Through a blend of theoretical concepts and hands-on exercises, participants will explore various machine learning algorithms and techniques, including supervised learning, unsupervised learning, and deep learning. Additionally, students will delve into data preprocessing, feature engineering, and model evaluation, gaining proficiency in extracting valuable insights from diverse datasets. With a focus on real-world applications across industries, from healthcare to finance, this course empowers learners to tackle complex data challenges and drive impactful decision-making through advanced analytics and machine learning technologies. Whether aspiring data scientists, analysts, or business professionals, this course equips individuals with the tools and knowledge needed to excel in the rapidly evolving landscape of data analytics and machine learning.
455604	Machine Learning in Fintech	3
This course provides a comprehensive exploration of database systems, covering the principles, design, implementation, and management of databases. Students will gain a solid understanding of relational database concepts, including entity-relationship modeling, normalization, and SQL querying. Through hands-on projects and exercises, participants will learn how to design and create efficient databases, optimize database performance, and ensure data integrity and security. Additionally, the course explores advanced topics such as distributed databases, NoSQL databases, and big data platforms, preparing students to navigate the evolving landscape of database technologies. Whether pursuing a career in database administration, data engineering, or software development, this course equips learners with the essential skills to build and manage robust database systems to meet the diverse needs of modern organizations.
455605	Operations Research	3
This course immerses students in the dynamic world of financial modeling and analytics, offering a comprehensive exploration of techniques and tools essential for effective decision-making in finance. Participants will delve into key financial concepts, including valuation methods, risk analysis, and portfolio optimization, and learn how to apply them in practical scenarios. Through hands-on projects and case studies, students will master spreadsheet modeling techniques, financial statement analysis, and forecasting methodologies. Additionally, the course covers advanced topics such as Monte Carlo simulation, option pricing models, and machine learning applications in finance, empowering students to leverage cutting-edge techniques for insightful financial analysis and strategic planning. Whether aspiring financial analysts, investment bankers, or corporate finance professionals, this course equips learners with the skills and knowledge needed to excel in the fast-paced and data-driven world of finance.
455606	Financial Modeling and Analytics	3
This advanced course delves into the sophisticated realm of Decision Support Systems (DSS), equipping participants with the tools and methodologies to facilitate effective decision-making in complex and dynamic environments. Students will explore advanced techniques for data analysis, modeling, and optimization, leveraging cutting-edge technologies such as artificial intelligence, machine learning, and big data analytics. Through hands-on projects and case studies, participants will learn how to design and implement DSS frameworks tailored to specific organizational needs, with a focus on enhancing efficiency, accuracy, and strategic insight. Additionally, the course covers emerging trends in DSS, including prescriptive analytics, real-time decision support, and cognitive computing, preparing students to address the evolving challenges of decision-making in today's interconnected and data-rich world. Whether pursuing careers in management consulting, operations research, or business analytics, this course empowers learners to develop and deploy advanced decision support systems that drive innovation and competitive advantage in diverse industries.
455607	Econometric Modeling	3
455691	Research Skills	3
This course provides a comprehensive overview of the scientific research process, equipping students with the knowledge and skills to conduct rigorous and impactful research across various disciplines. Participants will explore key components of research methodology, including hypothesis formulation, experimental design, data collection, analysis, and interpretation. Through practical exercises and case studies, students will learn how to critically evaluate existing literature, identify research gaps, and develop research proposals that adhere to ethical standards and best practices. Additionally, the course covers quantitative and qualitative research methods, as well as advanced techniques such as meta-analysis and mixed methods approaches, enabling students to tailor their research strategies to specific research questions and objectives. Whether pursuing careers in academia, industry, or government, this course empowers learners to contribute meaningfully to the advancement of knowledge and innovation through high-quality scientific research.
455699	Thesis	6
The Thesis in Business Intelligence course is the capstone component of the Master's program, providing students with the opportunity to conduct original research and contribute to the field of business intelligence. Under the guidance of a faculty advisor, students will identify a research topic related to business intelligence, formulate research questions or hypotheses, conduct a comprehensive literature review, design and implement a research methodology, collect and analyze data, and present their findings in a formal thesis document. This course emphasizes critical thinking, problem-solving, and research skills, as students apply theoretical knowledge and analytical techniques to address real-world challenges in the field of business intelligence. The thesis project allows students to demonstrate their ability to synthesize and apply concepts learned throughout the program, while contributing new insights to the academic and professional community in the rapidly evolving field of business intelligence.

Speciality Optional Requirements Student must complete 9 credit hours

Course Code	Course Name	Credit Hours	Prerequests
455650	Business Intelligence	3
Business Intelligence (BI) Course is a course that encompasses processes, technologies, and tools for transforming raw data into actionable insights, enabling organizations to make informed decisions. This course provides a comprehensive introduction to BI concepts and practices, covering data warehousing, data mining, reporting, and dashboard development. Through hands-on exercises and case studies, students will learn how to leverage BI tools like Tableau, Power BI, or QlikView to visualize data effectively and communicate key findings to stakeholders. Additionally, the course explores emerging trends in BI, including self-service analytics, predictive analytics, and big data integration, preparing students to harness the full potential of data-driven decision-making in modern businesses.
455651	Data Structures and Algorithms	3
This course delves into the intricate world of econometric modeling, equipping students with the theoretical foundation and practical skills to analyze economic data and test economic theories rigorously. Participants will explore key concepts such as linear regression, time series analysis, and panel data methods, learning how to apply them to real-world economic problems. Through hands-on projects and empirical exercises, students will gain proficiency in econometric software packages such as R, Python, or STATA, enabling them to estimate econometric models, interpret results, and make informed policy recommendations. Additionally, the course covers advanced topics such as instrumental variables, simultaneous equations, and nonparametric methods, preparing students to address the complexities and nuances of economic data analysis. Whether pursuing careers in academia, government, or industry, this course empowers learners to conduct high-quality econometric research and contribute meaningfully to the understanding of economic phenomena and the formulation of evidence-based policies.
455652	Database Systems	3
This course delves into the realm of advanced data structures and algorithms, providing students with a deep understanding of the fundamental principles and advanced techniques essential for solving complex computational problems efficiently. Participants will explore a wide range of data structures, including trees, graphs, heaps, and advanced hashing techniques, learning how to design and implement them to optimize memory usage and runtime performance. Through hands-on coding assignments and algorithmic problem-solving exercises, students will develop proficiency in analyzing algorithm complexity, identifying optimal solutions, and implementing them in programming languages such as Python, Java, or C++. Additionally, the course covers advanced algorithmic techniques such as dynamic programming, greedy algorithms, and divide-and-conquer strategies, preparing students to tackle challenging problems in areas such as artificial intelligence, computational biology, and optimization. Whether aspiring software engineers, data scientists, or computer scientists, this course equips learners with the skills and knowledge needed to excel in designing efficient and scalable solutions to complex computational problems.
455653	Big Data Analytics	3
This course delves into the diverse landscape of big data analytics tools, providing students with a comprehensive understanding of the technologies and methodologies essential for extracting insights from large and complex datasets. Participants will explore a range of cutting-edge tools and platforms, such as Hadoop, Spark, Apache Flink, Apache Kafka, and others, learning how to leverage their unique capabilities for data ingestion, storage, processing, and analysis at scale. Through hands-on exercises and real-world case studies, students will gain practical experience in building and deploying big data pipelines, implementing machine learning algorithms, and visualizing results using tools such as Apache Zeppelin, Jupyter Notebooks, and Tableau. Additionally, the course covers emerging trends in big data analytics, such as stream processing, real-time analytics, and serverless computing, preparing students to address the evolving challenges and opportunities of big data in today's digital landscape. Whether aspiring data engineers, data scientists, or business analysts, this course equips learners with the skills and knowledge needed to harness the power of big data analytics tools for driving innovation and making data-driven decisions in diverse industries.
455654	Analytics and Management of Human Resources	3
This course offers a comprehensive exploration of analytics and management in the context of human resources (HR), equipping students with the tools and strategies to leverage data-driven insights for effective HR decision-making. Participants will delve into key HR metrics and analytics techniques, learning how to collect, analyze, and interpret data to inform talent acquisition, performance management, employee engagement, and retention strategies. Through case studies and practical exercises, students will gain hands-on experience in using HR analytics software and tools to identify trends, predict workforce behavior, and optimize HR processes. Additionally, the course covers topics such as workforce planning, diversity and inclusion analytics, and ethical considerations in HR analytics, preparing students to address the complex challenges and opportunities of managing human capital in organizations. Whether aspiring HR professionals, people analytics specialists, or organizational leaders, this course empowers learners to harness the power of analytics to drive strategic HR initiatives and enhance organizational performance and success.
455655	Analytics of Managerial Accounting	3
This advanced course delves into the realm of managerial accounting with a focus on advanced analytics techniques, equipping students with the tools and methodologies to extract valuable insights from financial data for informed decision-making and strategic planning. Participants will explore key concepts such as cost behavior analysis, variance analysis, and performance measurement, learning how to apply advanced statistical and quantitative techniques to analyze financial and operational data. Through case studies and practical exercises, students will gain hands-on experience in using analytics tools and software to optimize resource allocation, evaluate business performance, and support strategic decision-making processes. Additionally, the course covers emerging trends in managerial accounting analytics, including predictive modeling, machine learning applications, and data visualization techniques, preparing students to leverage cutting-edge technologies for enhancing managerial decision support systems. Whether aspiring financial analysts, management consultants, or business leaders, this course empowers learners to apply advanced analytics techniques to drive efficiency, profitability, and sustainable growth in organizations.
455656	Marketing Management and Analytics	3
This advanced course delves into the intersection of marketing management and analytics, providing students with the tools and techniques to drive strategic marketing decisions through data-driven insights. Participants will explore advanced marketing concepts such as market segmentation, targeting, positioning, and brand management, learning how to leverage analytics to optimize marketing strategies and campaigns. Through hands-on projects and case studies, students will gain practical experience in using marketing analytics tools and techniques to analyze customer behavior, measure campaign effectiveness, and forecast market trends. Additionally, the course covers topics such as customer lifetime value analysis, marketing attribution modeling, and social media analytics, preparing students to harness the power of big data and digital technologies for strategic marketing decision-making. Whether aspiring marketing managers, data analysts, or digital marketers, this course empowers learners to navigate the complexities of the modern marketing landscape and drive business growth through data-driven marketing strategies and insights.
455657	Business Statistics	3
This advanced course offers a deep dive into business statistics, equipping students with the advanced analytical tools and techniques necessary to derive actionable insights from complex business data. Participants will explore advanced statistical methods such as multivariate analysis, time series analysis, and predictive modeling, learning how to apply them to real-world business problems. Through hands-on projects and case studies, students will gain practical experience in using statistical software packages such as R, Python, or SAS to analyze large datasets, identify patterns, and make informed business decisions. Additionally, the course covers topics such as experimental design, hypothesis testing, and Bayesian statistics, preparing students to address the challenges of uncertainty and variability in business decision-making. Whether aspiring business analysts, data scientists, or decision-makers, this course empowers learners to leverage advanced statistical techniques to drive innovation, optimize processes, and achieve strategic objectives in diverse business environments.
455658	Special Topics	3
This course delves into special topics within the field of Business Intelligence (BI), providing students with an in-depth exploration of advanced concepts, emerging trends, and cutting-edge technologies shaping the BI landscape. Participants will delve into specialized areas such as predictive analytics, prescriptive analytics, text mining, and sentiment analysis, learning how to extract valuable insights from diverse data sources to drive strategic decision-making and competitive advantage. Through case studies, research projects, and guest lectures from industry experts, students will gain practical experience in applying advanced BI techniques to real-world business challenges across various industries. Additionally, the course covers topics such as data ethics, privacy concerns, and regulatory compliance in BI, preparing students to navigate the ethical and legal implications of collecting, storing, and analyzing data for business intelligence purposes. Whether aspiring data scientists, BI architects, or business analysts, this course empowers learners to stay at the forefront of BI innovation and develop the skills needed to harness the full potential of data for driving organizational success in the digital age.