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Online Business Analytics Courses

Curriculum Details

  • 10 courses
  • 30 credits
  • 8-week course duration

The online master’s in business analytics degree from Illinois Tech provides in-depth analytics training for business professionals who are ready to pursue career advancement. The program is designed to be completed in 12 months with eight-week courses and features a STEM-designated curriculum grounded in practical application. You will graduate with hands-on experience in data visualization, strategic decision-making, data mining tools, SQL, and more.

Core

Credits

How do companies outperform their rivals to become market leaders in today’s hyper-competitive global business environment? The answer lies in developing great strategies and executing them flawlessly. Strategic Management is the rigorous business process that helps you develop and execute highly effective strategies. The SM process has three major components: Analysis (of external and internal environments), Strategy (business-level, corporate and functional) and Performance (strategic competitiveness and above-normal profits). The course has a strong experiential learning component. With the help of a strategic management computer simulation game, you will run a simulated company in a highly competitive marketplace to outperform your competitors and become market leader. At the end of the course, you will learn business fundamentals, the strategic management process, strategy formulation and implementation, data-driven decision making, and a good understanding of accounting, finance, human resources, marketing and production. This graduate course is suitable for students with or without a business background.
This course covers statistics, optimization, and simulation tools that are critical for managers in enabling their firms to have a competitive advantage. The course covers probability, sampling, estimation, hypothesis testing, linear regression, ANOVA, goodness-of-fit tests, and managerial decision-making under uncertainty. The models address problems in a variety of business functional areas and business processes. The focus of the course is on using business analytics to build models and using software to aid in decision-making.

This course is designed to develop each student’s financial analysis skill set. Throughout this course, students will be exposed to a variety of companies and industries with the goal of using various quantitative tools and qualitative factors to determine the financial health and risk of a company. The material covered in this course will correspond to various business applications including credit analysis, financial analysis, and investment analysis. During the latter part of this course, students will be exposed to advanced case study analysis using a team-building approach. MBA 501 will also introduce fundamental business concepts that will be used in other MBA courses.

Spreadsheets are a popular model-building environment for managers. Add-ins and enhancements to Excel have made powerful decision-making tools available to the manager. This course covers how to use the spreadsheet to develop and utilize some of these decision-making aids. Visual Basic for Excel allows the nonprogrammer to create modules for functions, subroutines, and procedures. Topics include forecasting (both regression and time series), decision-making under uncertainty and decision trees, using SOLVER for optimization, and probabilistic simulation using @RISK.

This course covers the fundamentals of relational databases including its design and provides an in-depth coverage of SQL which is the de-facto language used to manipulate relational databases. This course places emphasis on understanding the concepts and principles of both relational database design and SQL in a platform/software neutral manner which equip students to work with most database systems used in the modern workplace.
This course provides an introduction as well as hands-on experience in data visualization. It introduces students to design principles for creating meaningful displays of quantitative and qualitative data to facilitate managerial decision-making . Analytics involves the extensive use of computer applications, data (both “big” and “small”), and quantitative methods to help drive business decisions. Students will learn essential theories, concepts, methodologies, and use leading computer tools to visualize and analyze real world data.

The digital enterprise captures significantly more data about its customers, suppliers, and partners. The challenge, however, is to transform this vast data repository into actionable business intelligence. Both the structure and content of information from databases and data warehouses will be studied. Basic skills for designing and retrieving information from a database (e.g., MS Access) will be mastered. Data mining and predictive analytics can provide valuable business insights. A leading data mining tool, e.g., IBM/SPSS Modeler, will be used to investigate hypotheses and discover patterns in enterprise data repositories. Analysis tools include decision trees, neural networks, market basket analysis, time series, and discriminant analysis. Both data cleaning and analyses will be discussed and applied to sample data. Applications of data mining in a variety of industries will be discussed. Software exercises, case studies, and a major project will prepare the students to use these tools effectively during their careers.

The effective development, planning, execution, and communication of special projects are critical to all types of public service organizations and private sector organizations. Service organizations, healthcare providers, nonprofits, government organizations, and private sector organizations constantly pursue new initiatives and projects to address the demands of their constantly changing environments. This course will offer an introduction to basic concepts and methods for directing projects and will provide students with tools that prepare them for success in project management. Examples will be drawn from both the public and private sector.

Electives

Credits

The course examines digital marketing analytics strategies, platforms for data ingestion, preparation, and reporting. The course focuses beyond social media marketing analytics. Digital marketing analytics is foundational to Digital Marketing because analytics is the language used to optimize and connect results across all digital marketing tactics – search, social media, email marketing, display ads, video ads, etc. An effective digital marketer is well versed in data and is a data translator for a business. Becoming well versed in analytics and data requires the cultivation of both technical and soft skills. This course aims to arm students with such skills.
This course is designed to provide an introduction to the evolving area of AI, with an emphasis on potential business applications and related managerial insights. Artificial Intelligence (AI) is the science behind systems that can program themselves to classify, predict, and offer solutions based on structured and unstructured data. For millennia, humans have pondered the idea of building intelligent machines. Ever since, AI has had highs and lows, demonstrated successes and unfulfilled potential. Today, AI is empowering people and changing our world. Netflix recommends movies, Amazon recommends popular products, self-driving cars learn to navigate safely around other vehicles without human assistance, and programmed robots distinguish trash from dishes that are to be washed. This course focuses on how AI systems understand, reason, learn and interact; learn from industry’s experience on several AI cases; develop a develop a deeper understanding of machine learning (ML) techniques and the algorithms that power those systems, and propose solutions to real world scenarios leveraging AI methodologies.

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