COURSE DESCRIPTION
FOR WHO: The course is targeting professionals who want to deepen their knowledge of emissions from transportation, e.g. high school teachers, civil servants and politicians in public administration, engineers in the field of transport (car manufacturers, fuel production, logistics, ...)
WHAT AND WHY: The purpose of the course is to provide a holistic perspective and increased knowledge in air pollution, to distinguish between climate effects and health effects, but also to provide insight into the tools to bring about social change.
The climate is changing at an increasingly rapid pace and all the focus is on reducing CO2 emissions. However, our society relies heavily on energy conversions, e.g. for transport. Although some transport uses renewable (liquid) fuels, the CO2 balance is affected. Even if some transport is electrified, more CO2 emissions arise in the manufacture of, for example, batteries (and many cases of fossil-based electricity production). But transport also creates other emissions, so-called local emissions which mainly affect people and nature. As modern combustion engines emit very little air pollution, the composition changes and so-called wear particles also play a greater role in human health. Air pollution causes about 5 million premature deaths and is, after cancer, the greatest threat to human health. But local emissions also affect the climate. For example, marine transport will contribute with so-called albedo effects due to particle emissions (from internal combustion engines) and risk worsening climate change even more. This course deals with all the different aspects of air pollution from transport.
WHEN AND HOW: You choose when and at what pace you want to carry out the steps. All parts of the course are free of charge.
The course consists of five modules:
1. Introduction
2. The energy system and energy carriers
3. Energy converters (engines) and reduction of emissions (exhaust gas treatment)
4. Measurement and monitoring
5. Health effects, societal aspects
Each module contains several lectures and for each lecture and module there is a quiz where you can get confirmation that you have understood the most important things.
Going through the entire course takes about 3–5 weeks, depending on how intensively/extensively you read. You can also choose to read parts of the course
Skills in development work are becoming increasing importance in professional life. This course offers you the opportunity to develop knowledge and skills in product development, production development, and business development, as well as the relationship between these areas. You will be introduced to systematic working methods for product development, production development, and business development, with a specific focus on innovation and creativity in practical contexts. The goal of the course is to provide a deep understanding of the application of various processes in different types of development work. The objective is for course participants to enhance their ability to understand and apply development processes and gain deeper insights into how these processes relate to organizations' innovation and business strategies in order to achieve circular flows, resilience, and sustainability in the manufacturing industry. The teaching consists of self-study using course literature, films, and other materials through an internet-based course platform, as well as scheduled webinars and written reflections. There are no physical meetings; only digital online seminars are incuded. Study hours: 40 hours distributed over 7 weeks from week 13, 2024 to week 22, 2024. Target Group This course is primarily intended for engineers in management or middle management positions within industry, whether they are recent graduates or individuals with extensive experience. The course is suitable for individuals with backgrounds in mechanical engineering, industrial engineering management, or similar educational background. Entry Requirements To be eligible for this course, participants must have completed courses equivalent to at least 120 credits, with a minimum of 90 ntry Requirementscredits in a technical subject area, with at least a passing grade, or equivalent knowledge. Proficiency in English is also required, equivalent to English Level 6. Link to Syllabus Please note that the number of participants for this course is limited, so we encourage you to apply as soon as possible!
Målet med kursen är att ge lärare fortbildning inom ämnet djurvälfärd och hållbarhet. Kursens mål är också att ge lärare inspiration att designa sin egen undervisning, att ge lärare möjlighet att ta till sig ny forskning och att dela med sig av läraktiviteter som kan användas av fler.
The Internet of Things (IoT) is a networking paradigm which enables different devices (from thermostats to autonomous vehicles) to collect valuable information and exchange it with other devices using different communications protocols over the Internet. This technology allows to analyse and correlate heterogeneous sources of information, extract valuable insights, and enable better decision processes. Although the IoT has the potential to revolutionise a variety of industries, such as healthcare, agriculture, transportation, and manufacturing, IoT devices also introduce new cybersecurity risks and challenges. In this course, the students will obtain an in-depth understanding of the Internet of Things (IoT) and the associated cybersecurity challenges. The course covers the fundamentals of IoT and its applications, the communication protocols used in IoT systems, the cybersecurity threats to IoT, and the countermeasures that can be deployed. The course is split in four main modules, described as follows: Understand and illustrate the basic concepts of the IoT paradigm and its applications Discern benefits and drawback of the most common IoT communication protocols Identify the cybersecurity threats associated with IoT systems Know and select the appropriate cybersecurity countermeasures Course Plan Module 1: Introduction to IoT Definition and characteristics of IoT IoT architecture and components Applications of IoT Module 2: Communication Protocols for IoT Overview of communication protocols used in IoT MQTT, CoAP, and HTTP protocols Advantages and disadvantages of each protocol Module 3: Security Threats to IoT Overview of cybersecurity threats associated with IoT Understanding the risks associated with IoT Malware, DDoS, and phishing attacks Specific vulnerabilities in IoT devices and networks Module 4: Securing IoT Devices and Networks Overview of security measures for IoT systems Network segmentation, access control, and encryption Best practices for securing IoT devices and networks Organisation and Examination Study hours: 80 hours distributed over 7 weeks Scehduled online seminars: January 30th 2024, February 12th 2024 and 11th of March Examination, one of the following: Analysis and presentation of relevant manuscripts in the literature Bring your own problem (BYOP) and solution. For example, analyse the cybersecurity of the IoT network of your company and propose improvements The number of participants in the course is limited, so please hurry with your application!
KursinnehållKursen syftar till att ge en introduktion och överblick av artificiell intelligens. Fokus ligger på att förstå begreppet och några viktiga tekniker som hur sökning och maskininlärning fungerar samt konsekvenser av AI på samhället. Börja läsa när du vill Du kan börja läsa kursen i stort sett när du vill då kursen är en online-kurs med flexibel antagning. Du gör ansökan till den termin du tänker börja läsa kursen. Vill du börja direkt så ansöker du till innevarande termin, eller så väljer du den termin du tänker börja. Termin väljer du här ovan, så kommer du till rätt ansökningstillfälle. KursformatKursen är en distanskurs som görs i egen takt och hanteras i sin helhet i en web-baserad kursmiljö. Kursen baseras på självstudier av kursmaterialet och examineras med självrättande tester och inlämningar. Du som har gjort Elements of AI kan anmäla dig till den här kursen för att få dina resultat validerade. Det gäller både den svenska och den engelska versionen av kursen. Du måste inte göra om kursen, däremot måste du ladda upp certifikatet från Elements of AI och göra ett valideringstest med frågor motsvarande de som finns i Elements of AI för att säkerställa att det verkligen är du som gått igenom kursen. För mer information se denna länk. Kursen handleds över internet. Information om behörighetObservera att du vid ansökan till kursen måste kunna styrka att du har grundläggande behörighet. Om dina gymnasiemeriter inte redan finns på dina sidor på antagning.se så behöver du ladda upp gymnasieexamen, eller motsvarande, på antagning.se i samband med din ansökan.
Big data and the algorithms used in data science, together with the corresponding process and its technology tools, have important implications for addressing climate change. From machine learning algorithms to data visualization, data science methods are used to investigate and better understand climate change and its various effects on land, sea, food, etc.Data science is a powerful approach which is capable of helping practitioners, and policy-makers understand the uncertainties and ambiguities inherent in data, to identify interventions, strategies, and solutions that realize the benefits for humanity and the environment, and to evaluate the multiple– and sometimes conflicting–goals of decision-makers. In this MOOC course, we introduce methods pertaining to the growing field of data science and apply them to issues relevant to climate change. Topics Data science Analytics as a process Data-driven decisions Climate change Applications of data science in climate change Course content Understand data science Learn about the sources of big data Understand the basics of climate change, its impacts and sustainable development goals Get to know data-driven decisions and how they are made Highlight some climate change challenges that are directly or indirectly related to data science Apply data science knowledge and skills to make climate change related decisions Learn how others have used data science in association with addressing climate change problems You will learnBy the end of the course, you will be able to: obtain and analyze datasets; make data-driven decisions; identify and address climate change challenges using data science Who is the course for?This course is designed for those who want to improve their analytics and data-driven decision-making skills, with an emphasis on utilizing such skills for addressing climate change challenges. The course will also be useful for practitioners and policy-makers as they can benefit from understanding the uncertainties and ambiguities inherent in data and using it to identify interventions, strategies, and solutions that realize benefits for humanity and the environment.
Miljö, klimat och hälsa Kursen ger en fördjupad förståelse för hur hälsa samspelar med globalisering och miljö- och klimatförändringar, och hur hållbara lösningar kan utvecklas på lokal och global nivå för att möta framtidens utmaningar. Kursens innehåll Globala processer såsom miljö- och klimatförändringarDe globala hållbarhetsmålen / Agenda 2030HälsokonsekvensanalysKlimatanpassningRamverk inom miljö- och klimatpolitik. Vidare behandlar kursen specifikt klimatförändringar och deras effekter på hälsa i vårt nordeuropeiska klimatområde. I det sammanhanget behandlas också särskilt utsatta miljöer respektive känsliga patientgrupper och individer. Även värmens effekter vid arbete samt klimatanpassning och förebyggande av väderrelaterade risker för boende och inom hälso- och sjukvård ingår. Larmkedjor, handlingsplaner och beredskapsfrågor inom vård- och omsorg tas upp, och effektiviteten av förebyggande åtgärder inom vård- och omsorg. Omfattning Kursen är uppdelad i tre delar, med totalt 15 filmade föreläsningar. Medverkande Christofer Åström (Medicine doktor, Folkhälsa och klinisk medicin, Umeå universitet) Maria Nilsson (Professor, Epidemiologi och global hälsa, Umeå universitet) Chris Ebi (Professor, Center for Health and the Global Environment, University of Washington) Eva-Lotta Glader (Docent, överläkare, Folkhälsa och klinisk medicin, Umeå universitet) Gustav Strandberg (Filosofie doktor, SMHI)