Knowing how well security measures work, or how protected an organisation or systems is, can be difficult to quantify. The course aims to answer questions such as: – How to measure security? – What can be measured? The course presents several security metrics and how they can be implemented and used as KPIs.
In the modern IT world, businesses often have access to large amounts of data collected from customer management systems, web services, customer interaction, etc. The data in itself does not bring value to the business; we must bring meaning to the data to create value. Data mining and machine learning is an area within computer science with the goal of bringing meaning to and learning from data.
This course will focus on applied machine learning, where we learn what algorithms and approaches to apply on different types of data.This course is for experienced developers working in the industry. The course includes the following: Supervised learning, different types of data and data processing, Algorithms for handling text documents, Algorithms for handling data with numerical and categorical attributes, Neural Networks and Deep Learning for image recognition
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
The purpose of the course “Artificial Intelligence for Managers” is to give managers and decision makers a principle understanding of AI and to increase their understanding of opportunities, difficulties, benefits, and risks connected to AI. It is neither an “Introduction to AI” nor an “AI for dummies” course. Instead, it is set to demystify AI and to transform it into an actionable tool for manages and decision makers.
Target groupThis course is for product managers, project managers, executives, and engineering managers in organizations that have already made, or are about to make, the transition to working with AI.
ContentThe course is organized in three modules. The initial module will focus an introduction to AI, giving an understanding of what type of cases can be addressed with AI and what managers need to know about AI technology. Module two will cover tools and concrete on how to set up an AI strategy and roadmap, how to get started on AI projects, how to integrate AI and IT development, how to (self) evaluate AI in use, and, not to forget, the ethical and legal aspects of AI. The third module will give the participants the chance to use their new knowledge and tools and work with their own practical cases and how they could be addressed using AI.
The goal of the course is to empower the participants to:
Describe the principal concept of AI, its strengths, and shortcomings
Understand opportunities, myths, and pitfalls of AI
Identify problem areas in industry, society, and in management where AI could be utilized
Analyze how AI can be applied in a particular problem area
Manage an AI strategy and get started: implement a strategy and a roadmap to apply AI in a particular problem area
Understand how to integrate AI with IT development
Assess the maturity of AI utilization in an organization
Reflect on applications of AI from an ethical and legal perspective as well as the future challenges (technical, organizational, social, etc.)
Practical informationAll materials will be accessible and include reading material, lecturer slides etc. The lectures can either be attended live via Zoom or later using the recordings at a time that is convenient for the participants. There will be 3 onsite workshops with a focus on interaction with the teacher and the co-participants of sharing real-life experiences and insights. The course will be delivered in a flexible manner to facilitate the combination of course work with your ongoing professional commitments.
The total effort to pass this course is typically around 200 hours.
Teaching language: English
Entry requirementsThe basic eligibility for this course is a bachelor’s degree. Candidates with corresponding work experience are also invited to apply. Two years of relevant work experience is considered equivalent to one year of university studies at bachelor level.
The course is free
Vill du utveckla ditt ledarskap och samtidigt bli mer effektiv i din kommunikation? KI erbjuder nu utbildningen Motiverande ledarskap på 7,5 högskolepoäng. Kursen har fokus på ledarskap som identifierar och förstärker de beteenden inom en organisation som bidrar till verksamhetens mål. Då kommunikation är en central del i allt ledarskap ger kursen även praktisk träning i hur man genom kommunikation kan väcka medarbetarnas motivation.
Chefer och ledare har ett särskilt ansvar för att leda och utveckla organisationer, team och individer. Motiverande ledarskap (ML) baseras på den beteendeanalytiska organisationsteorin Organizational Behavior Management (OBM) och samtalsmetoden Motiverande samtal (MI). OBM bygger på forskning om vad som påverkar människors beteenden. MI är en samtalsmetod som syftar till att skapa motivation för att underlätta förändringsprocesser. Tillsammans ger metoderna chefer och ledare verktyg för att kunna styra och motivera sina medarbetares beteenden med direkt påverkan på organisationens prestationer och resultat.
Kursen ger grundläggande kunskap och träning i att tillämpa ett motiverande ledarskap, med fokus på att initiera, facilitera och utvärdera utveckling och förändring utifrån teorierna MI och OBM.
Kursen ger dig kunskaper och träning i hur du:
Identifierar och utvecklar förändringsbara nyckelbeteenden inom den egna organisationen
Planerar och genomför en organisatorisk förändringsprocess utifrån OBM
Informerar och kommunicerar på ett effektivt och anpassat sätt utifrån MI
Ger och tar emot lärande feedback
Genomför utvecklingssamtal och krävande samtal, enskilt och i grupp
Reflekterar över etiska frågor kopplat till ledarskap och motivation/beteendeförändring
The course is part of the programme MAISTR (hh.se/maistr) where participants can take the entire programme or individual courses. The course is for professionals and is held online in English. Application is open as long as there is a possibility of admission. The courses qualify for credits and are free of charge for participants who are citizens of any EU or EEA country, or Switzerland, or are permanent residents in Sweden. More information can be found at antagning.se.
About the course Smart Healthcare with Applications, 4 credits
Who is this course for?The course suits you with any Bachelor’s degree (equivalent of 180 Swedish credit points / ECTS credits at an accredited university) who have an interest in applying Artificial Intelligence (specifically Machine Learning) to healthcare. Leadership/management experience in health-related organization/industry OR a Bachelor degree in computer science is advantageous.
What will you learn from this course?Healthcare as a sector together with other health-related sources of data (municipalities, home sensors, etc.), is now in a place and can take advantage of what data science, Artificial Intelligence (AI), and machine learning (ML) have to offer. Information-driven care has the potential to build smart solutions based on the collected health data in order to achieve a holistic fact-based picture of healthcare, from an individual to system perspective. This course aims to provide a general introduction to information-driven care, challenges, applications, and opportunities. Students will get introduced to artificial intelligence and machine learning in specific, as well as some use cases of information-driven care, and gain practice on how a real-world evidence project within information-driven care is investigated.
What is the format for this course?Instruction type: The lectures, announcements, and assignments of this course will be fully online via a learning management system and presented in English. Each lecture is delivered through a video conference tool with a set of presentation slides displayed online during each class session. Online practical labs (pre-written Python notebooks) are also provided in the lectures.
This course looks at where important materials in products we use every day come from and how these materials can be used more efficiently, longer, and in closed loops. This is the aim of the Circular Economy, but it doesn’t happen on its own. It is the result of choices and strategies by suppliers, designers, businesses, policymakers and all of us as consumers.
In addition to providing many cases of managing materials for sustainability, the course also teaches skills and tools for analyzing circular business models and promotes development of your own ideas to become more involved in the transition to a Circular Economy. You will learn from expert researchers and practitioners from around Europe as they explain core elements and challenges in the transition to a circular economy over the course of 5 modules:
Module 1: Materials. This module explores where materials come from, and builds a rationale for why society needs more circularity.
Module 2: Circular Business Models. In this module circular business models are explored in-depth and a range of ways for business to create economic and social value are discussed.
Module 3: Circular Design, Innovation and Assessment. This module presents topics like functional materials and eco-design as well as methods to assess environmental impacts.
Module 4: Policies and Networks. This module explores the role of governments and networks and how policies and sharing best practices can enable the circular economy.
Module 5: Circular Societies. This module examines new norms, forms of engagement, social systems, and institutions, needed by the circular economy and how we, as individuals, can help society become more circular.