Aston Online Masters in Business Analytics Course Curriculum
Below is the list of courses you will study during the online Business Analytics degree:
Big Data for Decision Making
Examine large and varied data sets to uncover hidden patterns, unknown correlations, market trends, customer preferences and other information for managerial business decision making. Learn to employ Big Data software packages, machine-learning algorithms, text analytics, and predictive modeling.
Data Mining and Web Analytics
Explore neural networks, predictive models and data mining techniques and their usage in uncovering data patterns, regularities, and trends. Develop an understanding of the data available on the web and its value to business intelligence by applying data mining methods to solve real-world problems.
Business Analytics in Practice
Explore and learn how to apply predictive business analytics techniques, advanced statistical models, marketing models and financial analytics that drive a better-informed decision-making process.
Use modeling concepts to turn real-world problems into mathematical and spreadsheet models that can aid in rational decision-making across many business scenarios. Topics include linear programming, integer programming, decision trees, multi-objective decision making and more.
Descriptive Business Analytics
Learn about descriptive and inferential statistical methods for extracting meaningful information from data, and develop visualization techniques (e.g. dashboards and infographics) for displaying and summarizing information.
Effective Management Consultancy
Understand different approaches to best-practice consulting including Hard and Soft Systems methodology and how to complete successful consulting projects – either as an external investigator or line manager. Understand how to structure problems and explore the realities and characteristics of today’s consulting industry.
Use analytical methods such as Data Envelopment Analysis (DEA) and econometrics to derive benchmarks, targets, and measures of efficiency and productivity in complex multi-output/multi-input environments. Develop the use of specialized software to carry out comparative efficiency assessment.
Learn the basic skills and tools needed to develop software solutions to analyze Big Data. Grow as a data analytics expert through hands-on work with established software packages such as R, Python, SQL, and their related languages.
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