Modern web applications can often be described in terms of cooperation and sharing, both on the level of the users of the application and on the level of the application and the service providers. This course covers the most prevalent security challenges of web applications, from a theoretical and practical perspective.
The purpose of this course is to introduce security practices within the Software Development Lifecycle (SDLC) at the requirements, design, implementation, verification, and after release stages of software development.
This course is the guide to the cybersecurity issues arising throughout the entire development process. We consider the development from the security perspective from the beginning stage until the final release and beyond. The course is adapted to give a solid introduction to non-security-experts mainly and addresses both how professionals (developers, managers, decision-makers) can utilize security to improve (software-based) products/services, and how they are affected by security issues and challenges.
Whether you are a software developer in a bank or telecom company, or you are a product manager in a gaming company, this course will be relevant for you.
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.
The manufacturing industry collects increasingly large volumes of big data, that is, data at high speed, generated from a wide range of sources in different formats and quality levels. But what is data without insight? This course will help you master the fundamental concepts of big data, cloud computing and smart decision-making for industrial analytics.
Designed specifically for manufacturing sector professionals, this Master’s course provides knowledge and insights in handling and processing data, using machine learning and data analytics in the cloud environment. You will learn machine learning-based solutions for industrial applications, such as smart decision-making and predictive maintenance, using state of the art cloud platform tools.
The course will give insights in fundamental concepts of machine learning and actionable forecasting using predictive analytics. It will cover the key concepts to extract useful information and knowledge from big data sets for analytical modeling
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.
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.