After attending this course you should have achieved the following objectives:

• Know the importance and relevance of Business Process Management (BPM) in modern organisations;
• Know the phases of the BPM lifecycle;
• Can identify the relevant processes to be considered in a BPM initiative
• Can model a business process using BPMN (Business Process Modelling Notation)
• Can analyse and redesign a business process to improve efficiency, possibly using simulation techniques
• Know how business processes can be automated
• Know the importance and role of ERP system to support organizational operations and business processes
• Know the importance of Process Mining as a technique to discover and analyse business process
• Can discover and analyse processes mined from existing enterprise systems event logs

After attending this course you should have achieved the following objectives:

• Know the importance and relevance of Business Process Management (BPM) in modern organisations;
• Know the phases of the BPM lifecycle;
• Can identify the relevant processes to be considered in a BPM initiative
• Can model a business process using BPMN (Business Process Modelling Notation)
• Can analyse and redesign a business process to improve efficiency, possibly using simulation techniques
• Know how business processes can be automated
• Know the importance and role of ERP system to support organizational operations and business processes
• Know the importance of Process Mining as a technique to discover and analyse business process
• Can discover and analyse processes mined from existing enterprise systems event logs

The main aim of this course is to understand how a computer can store and process data effectively. To do this, data structures and algorithms must be studied with the help of a programming language. In this course, we will use Python as a programming language.

So, besides becoming an expert about data structures and algorithms, a (positive) side effect of this course is that you will learn a new programming language, i.e., Python (which, by the way, is used extensively in Data Science and scientific programming)

After attending this course you should have achieved the following objectives:

• Understand growth rate of algorithms using the Big-Oh notation
• Understand how recursion can be used to design algorithms
• Understand the principles and usage application of basic data structures, such as arrays, stack, queues and lists.
• Understand the principles and usage applications of advanced data structures, such as trees and hash tables
• Understand and apply typical sorting and searching algorithms
• Understand graphs, graph traversal and paths within graphs
• Implement basic and advanced data structures in Python
• Implement the algorithms covered by this course in Python
• Design and evaluate efficient algorithms in Python to solve specific applied problems
• Understand and utilise Python libraries to solve applied problems, such as using APIs (Twitter and Google maps are used as examples), creating and processing graphs, data science with Pandas.

The objective of this course is to discuss the fundamentals of modeling, analyzing and improving business processes in organizations using the data produced by their execution. The first part of the course covers the basics of business process management (modeling, simulation, improvement); the second part of the course covers the basics of “process mining”, i.e., a collection of techniques to analyze process data.

The objective of this course is to cover the basics of blockchain technology as a technology for designing and implementing cross-organisational information systems. The course starts with an overview of blockchain technology and its emergence in the field of cryptocurrency and then will focus more extensively on designing systems using blockchain.
Particular attention will be given to Bitcoin (as the first and prominent example of public blockchain), Ethereum (for smart contracts), and Hyperledger (as an example of permissioned business blockchain).

The course requires some basic knowledge of programming (Python is preferable). The level achieved with the course “Applied Programming for ME” will be more than sufficient.

After attending this course you should have achieved the following objectives:

• Know the basics of blockchain technology
• Know how blockchain can be used to implement cryptocurrency
• Understand how different cryptography tools (hashing, digital signatures) can be used to implement blockchain
• Can understand how public blockchains (e.g. Ethereum) can be used to design open systems
• Can understand how private (permissioned) blockchains can be used to design trustful multiparty systems
• Knows the basics of different framework to implement blochain-based systems (e.g., Ethereum, Hyperledger)
• Can understand the importance of blockchain in different real world case studies.

This course covers the fundamentals of predictive monitoring using business process event logs. The course covers mainly the design and implementation of business process predictive monitoring models built using machine learning techniques. As such, it focuses on topics such as feature extraction and engineering from event logs and encoding of event log information. In the second part, the course also discusses techniques for anomaly detection in event logs.

(Unedited!) recordings of this course lectures in 2020 are available at: Click Here