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Most companies have terabytes of business and customer data but are not sure how to leverage this treasure for growth and value creation. The Applied Management Analytics program will help you demystify the increasingly available variety of data for informed business decisions. To drive digital transformation, companies and employees must adopt to new management approaches that holistically integrate people and technology into the change process, and master data science tools and technologies including artificial intelligence (AI), predictive analytics, and data visualization.
This short program is designed for executives and professionals who want to learn how to transform their organization and master the change to a data-driven organization. As the technology for data analysis continues to advance, business leaders have to manage how an organization turns data into impact with the help of data science technologies and data science teams
Excellent teaching: Fundamentals of data analysis, data science, predictive analytics, AI and machine learning taught by leading experts from research and business practice
Part-time online format: Live sessions alternating with recorded learning content every 14 days, fixed times only every second Friday afternoon and Saturday
Versatile perspectives: Exchange of experiences among the participants from different industries and functions
Please note: Dates are subject to change.
Management Analytics / Leveraging big data for management decisions and transforming companies into data-driven organizations
Big data and artificial intelligence are an important driver for the digital transformation of companies and today’s society. Therefore, the first module introduces the perspective of digitization and business transformation that runs through the entire program – how to create growth and business value, such as more sales or profits, with big data and artificial intelligence. We discuss how organizations can use big data and artificial intelligence to create and expand competitive advantages.
Contents of the module/course:
At the end of the course, participants will be able to make meaningful use of the data and information available in organizations and to develop management strategies and programs based on both analytical arguments and quantitative metrics. The overall goal of the first module is to train analytical thinking skills by discussing proven and successful big data and artificial intelligence applications from participants’ industries and business areas.
Data Science Lab for a Competitive Advantage / Creating and maintaining competitive advantages with data science
In this course, participants will be introduced to the most modern data science methods. The overarching goal of the course is for participants to learn how to analyze and gain insights from data using various data science methods and to feel comfortable incorporating (big) data into day-to-day work. In addition, the participants learn how to model data using certain functions and how to determine the future development of company KPIs on the basis of data.
By the end of the course, participants will know all the essential analytical tools that will help them use data science to extract insights from data in a robust, correct and actionable way. Although the course has a solid theoretical basis, it is designed in such a way that participants apply what they have learned in practice from day one, solving cases and problems in the fields of marketing, logistics, HR or production. The course starts with the basics of statistics and ends with the introduction of machine learning models to include temporal components in predictive analytics.
Please note: Date is subject to change.
In companies, there is often a great amount of uncertainty how data can be used from a legal perspective, so that it doesn’t violate laws such as GDPR. Due to this uncertainty, companies often decide to completely discontinue the use of data and thus stop the often necessary transformation. In this module you will get an introduction to the legal framework and be shown that companies have far greater freedom to use data for analysis, growth and value creation.
AI and Machine Learning is changing the way companies do business. In particular, unstructured data such as images, texts and videos are rapidly gaining in importance. In this course, you will acquire fundamental knowledge of a wide range of AI and machine learning methods. In addition, you will gain basic knowledge of a wide range of methods for the automatic analysis of textual content (from lexicon-based methods to more recent transformer-based deep neural networks). In addition, you will gain insights into various real-world applications and ethical considerations related to machine learning.
Goals of the course:
The course offers a mix of theoretical foundations, several applied case studies, real-world examples and break-out sessions. Overall, you will experience an interactive learning environment.
This course introduces you to the fundamentals of the Python programming language, with a focus on topics required to apply Python in a data science context. Because of its ease of use and abundance of data science libraries, Python is a valuable tool for all kinds of data-related tasks. The course is designed to guide you through the necessary steps to learn Python from scratch. The videos introduce new content by showing illustrative examples of Python code that run interactively in the presentation. Programming exercises are offered to deepen the topics discussed.
Companies are currently spending millions of dollars on data-gathering initiatives, but few are successfully capitalizing on all this data to generate revenue and increase profit. Converting data into increased business performance requires the ability to extract insights from data through analytics. Marketing analytics is the practice of measuring, managing and analyzing marketing performance to maximize its effectiveness and optimize return on investment (ROI) of marketing efforts. With a profound understanding of marketing analytics, marketers will be more efficient and will improve the performance of their marketing actions and minimize wasted marketing dollars.
In this course you will learn state-of-the-art models and analytical approaches for a better understanding of consumers, customers, markets and competitors as well as increasing efficiency of marketing actions and enhancing competitive advantage. By the end of the course, you will be able to make sense of the information and knowledge available and create marketing strategy and programs based on both analytical arguments and quantitative metrics. Via cases and real-life applications, you will
The overall objective of the course is to train analytical thinking skills by analyzing and framing marketing problems and using problem-solving techniques to create marketing intelligence, all while considering ethical issues. Overall, you will develop a data analytics mindset, learn new tools, and understand how to convert numbers into actionable marketing insights.
People are often referred to as the most important asset of a company, data now as the oil of the 21st century. It is therefore not surprising that people analytics is seen as a crucial factor in human resource management practice. Instead of listening to intuition and gut feeling, analytical approaches and insights can now drive decision-making in companies. People analytics facilitates this data-driven decision-making to improve decision quality in various areas of HR such as employee engagement, recruitment, performance management, and leadership.
From research to modeling to forecasting, every aspect of finance is more driven by data and analytics than ever before. Data science, and in particular statistical and mathematical methods, is now part of most financial activities and is changing the financial services industry inexorably. This course will help you gain the foundational knowledge of data analytics in finance and apply them to create a framework for financial strategies that meet the needs of your company. From fine-tuning customer sales to assessing corporate credit risk, you'll learn to apply the analytics principles that enable informed decision making in this growing industry. In this course, you will learn the methodological tools to use Big Data as a lender for faster and better credit decisions or as a trader for data analysis to maximize portfolio returns.
Supply chain management is among the areas in which analytical methods have a particularly high impact. It is concerned with all activities aimed at satisfying customer demand. As such, it is paramount to the creation of business value. Notable complexities arise from manifold interdependencies between supply chain processes, resulting in intricate trade-offs, and from the interplay between different supply chain members, each having their own objectives. Supply chain analytics provides powerful levers to counter these challenges, resulting in better decisions and, ultimately, maximized performance.
Please fill out the registration form and send it to Admissions Manager Katja Gold email@example.com. Ms. Gold will also be happy to answer your questions about the course.