EdX

A Hands-On Introduction to Process Mining (edX)

Offered by RWTH Aachen, RWTHx,
A Hands-On Introduction to Process Mining (edX)

Compact course to learn the basics of Process mining. After this course, you will understand the concepts and you will be able to analyze event data. Using the provided software, you can immediately start improving any operational process.

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

Process mining is an exciting new technology that enables organizations to improve operational processes in a data-driven manner. Process mining can be applied in logistics, finance, production, sales, and healthcare. This hands-on course explains the key concepts and techniques in process mining. You will learn about automated process discovery, conformance checking, performance analysis, and applications of machine learning to event data. The theoretical concepts learned are tool and application-independent. However, to be able to apply these concepts, the course provides several data sets and access to the Celonis process mining software. After taking this compact course, participants understand current trends in process management and automation, know the key process discovery and conformance checking algorithms, and can apply these to real-life data sets using the Celonis software. Moreover, it is clear how comparative and predictive process mining techniques can be used to perform root cause analysis of performance and compliance problems in any domain.

What you'll learn

  • Understand and apply process discovery techniques
  • Understand and apply conformance checking techniques
  • Process modeling techniques such as DFGs, BPMN, and Petri nets
  • Extracting event data for process mining
  • Compare and analyze operational processes
  • Know the connection between process mining, data science, and machine learning
  • Know the connection between process mining, process science, automation, and process management
  • Use the Celonis process mining software using your own data sets

Syllabus

Week1: Welcome and basic concepts
Overview of the Process Mining Field and Basic Concepts
Introduction to Celonis Tool

Week2: Process discovery
Process Discovery and Directly-Follows Graphs * Discover Sophisticated Process Models (introduction to inductive miner and different process modeling notations)

Week3: Conformance checking
Alignment-Based Conformance Checking Footprint-Based Conformance Checking Token-Based Replay Conformance Checking

Week4: Process Analysis
From Traditional Event Logs to Object-Centric Event Logs * Comparative and Predictive Process Mining

Week5: Closing and Final Quiz
Closing Talk * Theoretical and Hands-on Final Exam (verified track)

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

Related Courses

Programming for Data Science (edX) EdX
University of Adelaide,AdelaideX

Programming for Data Science (edX)

Learn how to apply fundamental programming concepts, computational thinking and data analysis techniques to solve real-world data science problems. There is a rising demand for people with the skills to work with Big Data sets and this course can start you on your journey through our Big Data MicroMasters program towards a recognised credential in this highly competitive area. Using practical activities you will learn how digital technologies work and will develop your coding skills through engaging and collaborative assignments.

Self Paced
Self-Paced
Data Science: Capstone (edX) EdX
HarvardX,Harvard University

Data Science: Capstone (edX)

Show what you’ve learned from the Professional Certificate Program in Data Science. To become an expert data scientist you need practice and experience. By completing this capstone project you will get an opportunity to apply the knowledge and skills in R data analysis that you have gained throughout the series. This final project will test your skills in data visualization, probability, inference and modeling, data wrangling, data organization, regression, and machine learning.

Self Paced
Self-Paced
Data Science: Wrangling (edX) EdX
HarvardX,Harvard University

Data Science: Wrangling (edX)

Learn to process and convert raw data into formats needed for analysis. In this course, we cover several standard steps of the data wrangling process like importing data into R, tidying data, string processing, HTML parsing, working with dates and times, and text mining. Rarely are all these wrangling steps necessary in a single analysis, but a data scientist will likely face them all at some point.

Self Paced
Self-Paced
Recommender Systems: Behind the Screen (edX) EdX
Université de Montréal,UMontrealX

Recommender Systems: Behind the Screen (edX)

How are items recommended when you’re browsing for movies, jobs or clothing online? Register here and you’ll discover the fundamental concepts and methods allowing the most relevant item suggestions to users from e-commerce to online advertisement. In this course, you will explore and learn the best methods and practices in recommender systems, which are an essential component of the online ecosystem. This course was developed by IVADO and HEC Montréal as part of a workshop that took place in Montreal.

Self Paced
5-12 Weeks
SQL for Data Science (edX) EdX
IBM

SQL for Data Science (edX)

Learn how to use and apply the powerful language of SQL to better communicate and extract data from databases - a must for anyone working in the data science field. Much of the world's data lives in databases. SQL (or Structured Query Language) is a powerful programming language that is used for communicating with and extracting various data types from databases.

Self Paced
Self-Paced
Digital Marketing Analytics: Tools and Techniques (edX) EdX
University of Maryland, College Park,University System of Maryland - USM,USMx,UMD

Digital Marketing Analytics: Tools and Techniques (edX)

Learn how to leverage leading tools and approaches to digital marketing data analysis. Dive into SEO and SEM strategies including web analytics, machine learning and AI/Big Data applications to strengthen your digital marketing efforts and leverage your resources most effectively.

Self Paced
Self-Paced
Introduction to Data Science (edX) EdX
IBM

Introduction to Data Science (edX)

Learn about the world of data science first-hand from real data scientists. The art of uncovering the insights and trends in data has been around for centuries. The ancient Egyptians applied census data to increase efficiency in tax collection and they accurately predicted the flooding of the Nile river every year.

Self Paced
Self-Paced
Data Science: R Basics (edX) EdX
HarvardX,Harvard University

Data Science: R Basics (edX)

Build a foundation in R and learn how to wrangle, analyze, and visualize data. This course will introduce you to the basics of R programming. You can better retain R when you learn it to solve a specific problem, so you’ll use a real-world dataset about crime in the United States. You will learn the R skills needed to answer essential questions about differences in crime across the different states.

Self Paced
Self-Paced
Introduction to Computer Science and Programming (edX) EdX
Tokyo Institute of Technology,TokyoTechX

Introduction to Computer Science and Programming (edX)

The term “Computation” refers to the action performed by a computer. A computation can be a basic operation and it can also be a sophisticated computer simultation requiring a large amount of data and substantial resources. This course aims at introducing learners with no prior knowledge to basics and key concepts of computer science. By following the lectures and exercises of this course you will have an understanding of algorithms and you will get a real experience of programming using the language Ruby.

Self Paced
Self-Paced
Introduction to Data Science and Basic Statistics for Business (edX) EdX
Tecnológico de Monterrey,TecdeMonterreyX

Introduction to Data Science and Basic Statistics for Business (edX)

In this course you will acquire statistical methods for decision making in business, as well as technological tools to develop quantitative skills. Areas such as " big data" require very clear knowledge of statistics and business, technology provides us various applications that require solid training in statistics for proper use and interpretation .

Self Paced
Self-Paced
Data Science: Probability (edX) EdX
HarvardX,Harvard University

Data Science: Probability (edX)

Learn probability theory — essential for a data scientist — using a case study on the financial crisis of 2007–2008. In this course, you will learn valuable concepts in probability theory. The motivation for this course is the circumstances surrounding the financial crisis of 2007–2008. Part of what caused this financial crisis was that the risk of some securities sold by financial institutions was underestimated. To begin to understand this very complicated event, we need to understand the basics of probability.

Self Paced
Self-Paced