Making Evidence-Based Strategic Decisions (Coursera)

Making Evidence-Based Strategic Decisions (Coursera)

This course will give you a framework to help you successfully navigate the challenges posed by digital transformation. First, we will discuss how to use the organization's dynamic capabilities to start the digital transformation. Second, we will use fitness landscapes to build a competitive digital business model. Finally, we will implement a strategic foresight function to help evolve the digital business model for the organization's continued success.

Class Deals by MOOC List - Click here and see Coursera's Active Discounts, Deals, and Promo Codes.

Every modern organization is a digital organization or will rapidly become digital. Artificial intelligence, Google/Amazon/Facebook/Uber, and big data have dramatically raised customer expectations and demand.
Organizations that are effective in using data will win in the economies of the mid-21st century. These must-have core competencies include data analysis, machine learning, data visualizations, data mining, and predictive analytics, and deep learning. Organizations that won't or can't digitally transform will go the way of Blockbuster or Border's Bookstore.
The organization that better harnesses the power of data to create a superior customer experience will thrive in the new business realities.
The question is, how does an organization digitally transform? There are many digital technologies for organizations to choose from - too many choices! And digital technologies are only part of creating a digital organization. The employees must be trained in the new technologies, leaders must learn how to use data in making strategic decisions, and the organization's business processes must be reinvented. So many choices to make and the stakes have never been higher!
This course is part of the Transforming Your Company's Data Analytics Specialization.

Syllabus

Week 1 Decision Factories
Week 2 Data-Enabled Decision Making
Week 3 Low-Code/No-Code Tools for Data Analytics Products
Week 4 Artificial Intelligence in Data Analytics
Final Exam

Go to Class
MOOC List is learner-supported. When you buy through links on our site, we may earn an affiliate commission.

Related Courses

Pattern Discovery in Data Mining (Coursera) Coursera
University of Illinois at Urbana-Champaign

Pattern Discovery in Data Mining (Coursera)

Learn the general concepts of data mining along with basic methodologies and applications. Then dive into one subfield in data mining: pattern discovery. Learn in-depth concepts, methods, and applications of pattern discovery in data mining. We will also introduce methods for data-driven phrase mining and some interesting applications of pattern discovery. This course provides you the opportunity to learn skills and content to practice and engage in scalable pattern discovery methods on massive transactional data, discuss pattern evaluation measures, and study methods for mining diverse kinds of patterns, sequential patterns, and sub-graph patterns.

Jun 22nd 2026
4 Weeks
Learn to code with AI (Coursera) Coursera
Scrimba

Learn to code with AI (Coursera)

Imagine waking up tomorrow as a web developer. What would you want to build? With AI tools like ChatGPT, you're already a developer, regardless of your experience, if you know how to work with them. So in this course, you'll build functional, interactive front-end projects while learning how to write effective prompts and debug and refine your code with the help of AI.

Jun 24th 2026
2 Weeks
Marketing Analytics (Coursera) Coursera
University of Virginia

Marketing Analytics (Coursera)

Organizations large and small are inundated with data about consumer choices. But that wealth of information does not always translate into better decisions. Knowing how to interpret data is the challenge -- and marketers in particular are increasingly expected to use analytics to inform and justify their decisions. Marketing analytics enables marketers to measure, manage and analyze marketing performance to maximize its effectiveness and optimize return on investment (ROI). Beyond the obvious sales and lead generation applications, marketing analytics can offer profound insights into customer preferences and trends, which can be further utilized for future marketing and business decisions.

Jun 22nd 2026
5-12 Weeks
Exploratory Data Analysis (Coursera) Coursera
Johns Hopkins University

Exploratory Data Analysis (Coursera)

This course covers the essential exploratory techniques for summarizing data. These techniques are typically applied before formal modeling commences and can help inform the development of more complex statistical models. Exploratory techniques are also important for eliminating or sharpening potential hypotheses about the world that can be addressed by the data.

Jun 22nd 2026
4 Weeks
Fundamentals of GIS (Coursera) Coursera
University of California, Davis

Fundamentals of GIS (Coursera)

Explore the world of spatial analysis and cartography with geographic information systems (GIS). What you will learn: define core geospatial concepts; practice with subset data using selections and feature attributes; create map books using advanced mapping techniques; create layer and map packages.

Jun 22nd 2026
4 Weeks
Interprofessional Healthcare Informatics (Coursera) Coursera
University of Minnesota

Interprofessional Healthcare Informatics (Coursera)

Interprofessional Healthcare Informatics is a graduate-level, hands-on interactive exploration of real informatics tools and techniques offered by the University of Minnesota and the University of Minnesota's National Center for Interprofessional Practice and Education. We will be incorporating technology-enabled educational innovations to bring the subject matter to life. Over the 10 modules, we will create a vital online learning community and a working healthcare informatics network.

Jun 22nd 2026
5-12 Weeks
Introduction to Probability and Data with R (Coursera) Coursera
Duke University

Introduction to Probability and Data with R (Coursera)

This course introduces you to sampling and exploring data, as well as basic probability theory and Bayes' rule. You will examine various types of sampling methods, and discuss how such methods can impact the scope of inference. A variety of exploratory data analysis techniques will be covered, including numeric summary statistics and basic data visualization.

Jun 22nd 2026
5-12 Weeks
Practical Predictive Analytics: Models and Methods (Coursera) Coursera
University of Washington

Practical Predictive Analytics: Models and Methods (Coursera)

Statistical experiment design and analytics are at the heart of data science. In this course you will design statistical experiments and analyze the results using modern methods. You will also explore the common pitfalls in interpreting statistical arguments, especially those associated with big data. Collectively, this course will help you internalize a core set of practical and effective machine learning methods and concepts, and apply them to solve some real world problems.

Jun 22nd 2026
4 Weeks
Leadership Through Marketing (Coursera) Coursera
Northwestern University

Leadership Through Marketing (Coursera)

The success of every organization depends on attracting and retaining customers. Although the marketing concepts for doing so are well established, digital technology has empowered customers, while producing massive amounts of data, revolutionizing the processes through which organizations attract and retain customers. In this course, students will learn how to identify new opportunities to create value for empowered consumers, develop strategies that yield an advantage over rivals, and develop the data science skills to lead more effectively, allocate resources, and to confront this very challenging environment with confidence.

Jun 28th 2026
4 Weeks
Text Retrieval and Search Engines (Coursera) Coursera
University of Illinois at Urbana-Champaign

Text Retrieval and Search Engines (Coursera)

Recent years have seen a dramatic growth of natural language text data, including web pages, news articles, scientific literature, emails, enterprise documents, and social media such as blog articles, forum posts, product reviews, and tweets. Text data are unique in that they are usually generated directly by humans rather than a computer system or sensors, and are thus especially valuable for discovering knowledge about people’s opinions and preferences, in addition to many other kinds of knowledge that we encode in text.

Jun 22nd 2026
5-12 Weeks
Value and Individual Decision Making (Coursera) Coursera
Yunus Social Business Fund Bengaluru

Value and Individual Decision Making (Coursera)

This course is part of a Specialization titled “Strategy and Finance for a Lifecycle of a Social Business”. It is an introduction to time value of money and will help the learner understand the basics of finance with the ultimate goal of valuing a company from a societal lens. The beauty of the modern decision-making framework is that it can be used to understand value creation at any level – the individual, the corporate or nonprofit entity level and from the point of view of society. The applications however become increasingly complex as your lens expands from the individual to the corporate/nonprofit to the global society.

Jun 24th 2026
5-12 Weeks