In this course you will learn state-of-the-art statistical modelling for the purpose of analysing industrial data. The course also presents the basics of relational databases and data manipulation techniques needed to prepare the data for analysis.
In contrast to learning how to do manual testing, in this course you will learn how to generate tests automatically in the sense that test creation satisfying a given test goal or given requirement is performed automatically.
This course provides an understanding of automating software testing using program analysis with the goal of intelligently and algorithmically creating tests. The course covers search-based test generation, combinatorial and random testing while highlighting the challenges associated with the use of automatic test generation.
Statistics is vital in every field and in this course, you will learn the role it can play in the field of sustainable development. You will learn certain statistical tools, how to apply them, and ways of thinking about results that will aid you in your studies and future career.
The starting point for the course is Lean Production, with an understanding of principles and concepts that can lead to higher efficiency. Then we introduce computer-based application for modelling and simulation of production systems. This provides the opportunity to simulate a production system, perform experiments on it according to different conditions, and optimize the system to increase efficiency.
This course is for professionals who work with production systems at different levels with a responsibility for individual production lines, departments, or has a role as production manager or production development. The course will mainly focus on the manufacturing industry in application examples, but principles that will be addressed will be applicable to a number of industries, including consulting companies working towards the manufacturing industry.
The course contains the following:
Production systems and concepts such as Industry 4.0 and Smart Industry
Lean Production and workshop with the Lean game
Programming exercises with event-based simulation of production systems
Analysis and optimization of production systems
The majority of the course will take place on Campus (Växjö), and at a distance according to the schedule below. Some of the exercises are preferably attend on Campus, but we plan for it to be possible to follow the full course at a distance due to the Covid-situation.
This course introduces students to the fundamentals of experiment design and statistical inference models for data analysis. The courses provides a hands on experience in designing an experiment, collecting data and drawing conclusions.
Statistics in a science of decision making and conclusion drawing in the presence of variability. In rare cases, to be able to make a decision about a new product, or draw conclusions from an observed phenomena, we can collect observations from the entire population and as a result make a definitive conclusion about its attributes, but most often that is not the case. As a we often opt to performing an experiment, or making passive observation with only a-sub sample of the population that will help us extrapolate and make decision about the rest of the unobserved samples.
This course is given on-line with three mandatory Zoom-meetings.
This contract education initiative is aimed at working professionals with a higher education qualification of 180 credits earned at the first cycle (bachelor's level) which includes 15 credits of computer programming. In addition, English B/English 6 is required.
Maybe you want to connect monitoring to a truck, or why not build a connected pump control? Do you want to measure temperatures, pressures or vibrations? Do you want knowledge about how to connect one of your existing products? Then this course is for you.
Do you work as an engineer in the industry and want to learn how to develop an idea with IoT? Do you work as a developer at an IT company and want to learn more about the hardware and the entire infrastructure within IoT? The course is primarily aimed at those who are professionals in the engineering profession, but you do not need to be either a programmer or an electronics engineer to take advantage of the course. The content is adapted so that you can work with your specific ideas.
The course is focused on providing both theoretical and practical knowledge in the field of Internet of Things. You will gain knowledge of the area's applications and definitions, and you will learn how to build an IoT device, all the way from hardware to visualization. You will have the opportunity to practically work with hardware, sensors, as well as infrastructure and security. We will work with, among other things, WiFi, BLE, LoRaWAN, SigFox, NB-IoT / LTE-M1, as well as insight into how data is transported throughout from the device to the database and then to the application.
The course will be held mostly at a distance with a couple of scheduled workshops (13/9, 6/10, 27/10) either on site or online. All lectures will be available online. The course will be delivered in a flexible way to facilitate the combination of coursework with your ongoing professional commitments.
You will need to buy IoT hardware before the start of the course, the cost can be different depending on the type of project, guide value is approx: SEK 1,000.
The total scope of the course is normally about 80 hours.Language of instruction: EnglishThe course is free of charge
Today, the explosion of data has created new opportunities to apply machine learning (ML). Handling of the large amounts of data created by the very rapid digitization would not be possible without Machine Learning (ML). The purpose of the course "Introduction to Machine Learning" is to give you the foundation for ML. You will get an introduction to the basic areas of ML: data, statistics and probability for ML.