Mathematics and statistics

Mathematics and statistics form the basis for calculations, algorithms and models used in AI

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Samhället och AITillämpningar av AI

Emerging AI technologies offer a wide range of business opportunities with the promise of marvelous results.  However, starting an AI project and maximizing the trade-off between business impact and resources spent is still a demanding task requiring a thorough understanding of what AI can and cannot do for your business.

By taking this course, you will learn:

  • what you can use artificial intelligence for,
  • how you as a business leader should approach it from a corporate strategy point of view,
  • what crucial strategic decisions you have to make in advance,
  • what competences you need in order to succeed,
  • how you should start and proceed with the different stages of your project.
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Samhället och AITillämpningar av AI

Emerging AI technologies offer a wide range of business opportunities with the promise of marvelous results.  However, starting an AI project and maximizing the trade-off between business impact and resources spent is still a demanding task requiring a thorough understanding of what AI can and cannot do for your business.

By taking this course, you will get a brief introduction to:

  • what you can use artificial intelligence for,
  • how you as a business leader should approach it from a corporate strategy point of view,
  • what crucial strategic decisions you have to make in advance,
  • what competences you need in order to succeed,
  • how you should start and proceed with the different stages of your project.
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Machine LearningApplications of AI

AI Class sets out to improve general knowledge about Artificial Intelligence (AI), Machine Learning (ML) and Deep Learning (DL). The aim to increase understanding of how these techniques can be used to improve the use of large amounts of data.

The education modules have been developed by researchers at Mälardalen University and RISE SICS Västerås, in cooperation with BillerudKorsnäs and PulpEye.

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Machine LearningHuman-AI InteractionApplications of AI

Artificial intelligence (AI) is not just a technology. Beyond the algorithms, AI drives services that are rapidly changing our work, our personal lives, and in extension the very fabric of society. The course Human-Centered Machine Learning is podcast-based and aims to provide professionals with more knowledge on machine learning, how to design better services, and how to avoid some of the pitfalls with different AI techniques (predominantly various kinds of machine learning and deep learning). The content is on the one hand focused on the basics of the technology, and on the other hand a design-oriented approach to building human-centered services using AI technology. The podcast is in English and consists of 12 episodes of varying length, most of them around 40 minutes.

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Samhället och AISamverkan mellan människor och AITillämpningar av AI

This four-week course titled AI and Law explores the way in which the increasing use of artificially intelligent technologies (AI) affects the practice and administration of law defined in a broad sense. Subject matters discussed include the connection be between AI and Law in the context of legal responsibility, law-making, law-enforcing, criminal law, the medical sector and intellectual property law.
The course aims to equip members of the general public with an elementary ability to understand the meaningful potential of AI for their own lives. The course also aims to enable members of the general public to understand the consequences of using AI and to allow them to interact with AIs in a responsible, helpful, conscientious way.

At the end of this course, you will have a basic understanding of how to:
• Understand the legal significance of the artificially intelligent software and hardware.
• Understand the impact of the emergence of artificial intelligence on the application and administration of law in the public sector in connection with the enforcement of criminal law, the modelling of law and in the context of administrative law.
• Understand the legal relevance of the use of artificially intelligent software in the private sector in connection with innovation and associated intellectual property rights, in the financial services sector and when predicting outcomes of legal proceedings.
• Understand the importance of artificial intelligence for selected legal fields, including labour law, competition law and health law.

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MaskininlärningMatematik och statistik

This online MOOC course introduces you to Artificial Intelligence (AI) and Machine Learning. Additional to this, it will give you basic knowledge in Big Data, Mathematics, Probability, Statistics, and the programming language Python.

In addition to giving you this knowledge, successful completion of the course will make you eligible for these academic online courses at Mälardalen University (MDH):

  • Machine Learning with Big Data 7.5 credits
  • Predictive Data Analytics 2.5 credits
  • Deep Learning with Industrial Imaging 2.5 credits

If you pass the final test of the Basic Knowledge on Machine Learning MOOC course you can apply for the above academic courses at MDH without providing any other proof of eligibility than the certificate from the MOOC course.

Please note that you are not guaranteed to be admitted to the above academic courses since the number of students in the courses is limited. Successful completion of the MOOC course will not make you eligible for any other course.

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Kunskapsrepresentation och resonerandePlanering och schemaläggningSamhället och AITillämpningar av AI

This course is about what you can do when everything around you seems to be moving due to digital change. It is about how to handle the disruptive process that tends to unfold in industry nowadays due to digitalisation and about understanding how the new business landscape is evolving and heading for a new position.

By taking this course, you will get a brief introduction about:

  • new business opportunities and the need for re-organization;
  • digitalisation effects on customers as well as on external and internal processes;
  • digital trends that change value creation; master strategies, methods and approaches that are directly applicable for you and your company when tackling the digital transition;
  • sorting mechanisms for better prioritisation.
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Kunskapsrepresentation och resonerandePlanering och schemaläggningSamhället och AI

This course is about what you can do when everything around you seems to be moving due to digital change. It is about how to handle the disruptive process that tends to unfold in industry nowadays due to digitalisation and about understanding how the new business landscape is evolving and heading for a new position.

By taking this course, you will learn about:

  • new business opportunities and the need for re-organization,
  • digitalisation effects on customers as well as on external and internal processes,
  • digital trends that change value creation,
  • master strategies, methods and approaches that are directly applicable for you and your company when tackling the digital transition,
  • sorting mechanisms for better prioritisation.
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Online

Societal Aspects of AIHuman-AI InteractionApplications of AI

Software, machine learning and artificial intelligence have changed our lives in the last two decades. Everything from the fundamental infrastructure to advanced applications use computers and software. Artificial intelligence and machine learning take advantages of the prevalence of software and data, providing us with new possibilities.

In this course, we problematize and discuss the challenges of using AI in different professions. We present how AI influences medicine, education, journalism, and law. We start the course with presenting the technology around AI – neural networks, data mining and visualization and legal aspects of using AI. Then, we move to modules that present the use of AI in professions.

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Societal Aspects of AIHuman-AI InteractionApplications of AI

AI, Business and the Future of Work is the second AI-related MOOC from Lund University. The course focuses on the challenges and opportunities that AI development entails for both business and professionals.

As the Organisation for Economic Co-operation and Development (OECD, 2016) reports 14% of jobs are expected to be automated whilst another 32% is predicted to see significant change due to automation, we are all witnessing how AI is impacting the way we work and organise business today.

With vast challenges and opportunities ahead, shaping the future of work and organisations will most likely depend on the way we choose to act today and in the coming years. But where should we start looking? Join this course to delve deeper into exciting and vital knowledge on this topic!

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Societal Aspects of AIHuman-AI InteractionApplications of AI

Artificial Intelligence: Ethics and Societal Challenges is the third AI-related MOOC from Lund University available on Coursera.org. This course explores ethical and societal aspects of the increasing use of AI technologies. The aim of the course is to raise awareness of ethical and societal aspects of AI and to stimulate reflection and discussion upon implications of the use of AI in society.

In the first module, we will discuss algorithmic bias and surveillance. AI in many ways makes surveillance more effective, but what does it mean to us if we are increasingly being watched in more and more sophisticated ways? Next, we will talk about the impact of AI on democracy. We discuss why democracy is important, and how AI could hamper public democratic discussion, but also how it can help improve democracy. A further ethical question concerns whether our treatment of AI could matter for the AIs themselves. What is the relationship between consciousness and intelligence? This is the topic of the third week of the course. In the fourth module we will talk about responsibility and control. If an autonomous car hits an autonomous robot, who is responsible? The last question of the course, and maybe also the ultimate question for our species, is how to control machines that are more intelligent than we are. Our intelligence has given us a lot of power over the world we live in. Shall we really give that power away to machines and if we do, how do we stay in charge?

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This online MOOC course will let you discover how artificial intelligence is set to shape the future of tourism, in this introductory tourism management course.

You will gain a broad understanding of how AI and machine learning work, and learn to distinguish fact from fiction. You will consider the latest trends and developments, considering real-life artificial intelligence use cases. You will also consider key questions around AI ethics, addressing the common and valid concerns that come with these new technologies.

With this introduction to AI, you will begin to understand the potential applications of AI in the tourism industry. This will empower you to shape its future.

This tourism management course does not require any prior technical knowledge of artificial intelligence or computer programming. It is aimed at tourism industry professionals, with a stake in the future of tourism.

It is designed and delivered by leading artificial intelligence experts at the Luleå University of Technology.

 

 

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Luleå

Societal Aspects of AIApplications of AI

Discover how artificial intelligence is set to shape the future of tourism, in this introductory tourism management course.

We are in the midst of what commentators are calling the Fourth Industrial Revolution, or Industry 4.0.

This describes the advent of new technologies that are set to irreversibly change working practices across sectors. Chief among these technologies are artificial intelligence and machine learning. These changes will almost certainly have a profound effect on the future of tourism.

This tourism management course offers an introduction to artificial intelligence, and considers how it will affect the tourism industry.

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Maskininlärning

In this course, we will explore Machine Learning and Neural Networks in particular. The objective is to reveal the simplicity at the core and cut through the jargon. Among other things, we will go deep into: What are Neural Networks and how are they trained? How do Neural Networks analyze images and text? How important is data? We will go under the hood to let you gain an intuition in the capabilities and constraints of this powerful toolbox.

Estimated effort: 4 hours
Requirements: It does not require any particular skills in math or coding.

  • We go under the hood of what Neural Networks are, what they do and how they do it. The course digs deep into the Fully Connected Network and visualizes the representation of the inner layers.
  • It goes further with a deeper intuition how such networks are trained and why it works.
  • You will understand the important concepts, such as Gradient Descent, Backpropagation and different Activation Functions. Common metrics are presented as well as problems, such as overfitting and underfitting.
  • Convolutional networks to analyze images are conceptually presented including the first classical LeNet-5 and AlexNet.
  • An introduction is given of how words and texts are represented and analyzed through Word Embeddings and the Recurrent Neural Network, as well touching upon Attention Models.
  • Interviews with some of the leading experts in Sweden are included throughout the course.
  • We aim to give you the knowledge to be able to communicate with developers in ML projects and the ability to identify potential application areas within your field of expertise.
  • Last but not least, we hope to build motivation for your own further learning.
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Online

Data ScienceKnowledge Representation and ReasoningMachine LearningApplications of AI

This course gives a basic overview of Artificial Intelligence (AI) and its applications. Specifically, it provides basic knowledge of machine learning and deep learning algorithms, robotics, reasoning, medical neuroscience, psychology, cognition, as well as design skills to structure experiments.

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Online

The course is designed to give participants a mix of theory and practice. Basic concepts in computer science are presented as a basis, as well as R-programming as one of the most important skills / tools that a computer scientist should have. The course also provides practical experience of using computer science tools and techniques.

Previous knowledge

Basic knowledge of differential equations, fluid and solid mechanics. Basic skills in programming and / or some form of experience in numerical calculation methods in MATLAB, MAPLE, MATHEMATICA or similar.

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Online

Computer ScienceMachine Learning

The rapid development of digital technologies and advances in communications have led to gigantic amounts of data with complex structures called ‘Big Data’ being produced every day at exponential growth. The aim of this course is to give the student insights in fundamental concepts of Machine Learning with Big Data as well as recent research trends in the domain. The student will learn about problems and industrial challenges through domain-based case studies. Furthermore, the student will learn to use tools to develop systems using machine-learning algorithms in big data. This course is possible to combine with a full-time employment.

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Online

The course is broken down into:

  • Basic Bayesian concepts
  • Selecting priors, deriving some equations
  • Bayesian inference, Parametric model estimation
  • Sampling based methods
  • Sequential inference (Kalman filters, particle filters)
  • Approximate inference, variational inference
  • Model selection (missing data)
  • Bayesian deep neural networks

Entry requirements

Degree of Bachelor of Science with a major in Computer Science and Engineering or Degree of Bachelor of Science in Engineering, Computer Science and Engineering or the equivalent of 180 Swedish credit points or 180 ECTS credits at an accredited university. Including 5 credits statistics and 5 credits machine learning. Applicants must have written and verbal command of the English language equivalent to English course 6 in Swedish Upper-Secondary School.

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Online

The aim of this course is that students will learn about the analysis, design, and programming of deep learning algorithms. 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.

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Online

Samhället och AISamverkan mellan människor och AITillämpningar av AI

Kursen ger en allmän kunskap på hög nivå om AI, maskininlärning och datavetenskap till chefer och ledare.

Kursen ingår i kurspaketet DIGIBUS (hh.se/digibus) där du som deltagare kan läsa hela kurspaketet eller enstaka kurser. Kursen är för yrkesverksamma och ges på distans på engelska. Anmälan är öppen så länge det finns möjlighet att bli antagen.

Behörighetskrav:

Kandidatexamen eller Högskoleingenjörsexamen.

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Online

Computer ScienceKnowledge Representation and ReasoningMachine Learning

The on-line 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 modelling. This course is possible to combine with a full-time employment.

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Online , kurs

Maskininlärning

För att ett system automatiskt ska kunna känna igen ett ansikte, avgöra den optimala tidpunkten för maskinunderhåll, sortera textdokument, ha fungerande taligenkänning, känna igen handskrivna tecken, urskilja mönster i stora datamängder – till exempel att identifiera kundgrupper eller olika beteenden – krävs förmågor som är svåra att programmera explicit. I den här kursen får du lära dig grunderna i hur ett system kan lära sig dessa förmågor utifrån datamängder istället för att blir programmerade. Här ingår de vanligaste algoritmerna för övervakad och oövervakad inlärning, såsom artificiella neurala nätverk, beslutsträd och k-medelvärdeskluster, vilka också utgör grunden för att förstå och diskutera de senaste teknikerna inom maskininlärning såsom djupinlärning.

Kursen riktar sig till dig som är yrkesverksam.

Kursen har tre obligatoriska halvdagsträffar.

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Online , kurs

Maskininlärning

Förstärkningslärande (Reinforcement learning – RL) är en metod för att lära sig att fatta ett optimalt beslut genom försök och misstag. Målet med RL är att uppnå en optimal policy för varje tillstånd i ett system. Kursen täcker den underliggande formalismen hos RL som kallas Markovska beslutsprocesser och grundläggande RL-algoritmer. Exempel är dynamisk programmering. Vi kommer att visa hur man modellerar ett problem som en Markovska-beslutsprocess och implementerar grundläggande RL-algoritmer för att lösa dem. Dessutom kommer vi att utforska olika sätt att jämföra och utvärdera prestanda för inlärningsmetoder.

Kursen riktar sig till dig som är yrkesverksam.

Kursen har tre obligatoriska halvdagsträffar.

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Online

Intelligenta agenter och multiagentsystem

Den verkliga världen är distribuerad. Distribuerad artificiell intelligens handlar om denna spridning av kunskap, kompetens och förmågor, över olika enheter och olika platser.

Kursen introducerar Multi-Agent Systems – huvudkonceptet och teknologin för distribuerad AI. Vi kommer att diskutera hur man bygger system som kan fungera som en del av ett Multi-agent System; hur man organiserar olika intelligenta enheter, hur man använder förhandling eller auktioner för att distribuera uppgifter till autonoma agenter och många fler ämnen från Swarm Intelligence till team av intelligenta robotar.

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Computer ScienceComputer VisionMachine Learning

This on-line course will teach you how to build convolutional neural networks. You will learn to design intelligent systems using deep learning for classification, annotation, and object recognition. This course is possible to combine with a full-time employment.

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Online

Machine LearningApplications of AI

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.

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Online

Artificial Intelligence (AI) is being increasingly implemented and used in society today. It has already proven to have an impact on the individual, organization and society, and this impact will most likely only increase. Therefore, it is important to understand the ethical issues that may arise from use of AI, as well as to adopt a critical stance to the technology’s impact.

The course introduces critical and ethical issues surrounding data and society, to train the student to problematize and reason about artificial intelligence (AI).

You are most likely a designer, innovator, or product manager that works with digital services and products.

 

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Online

Applications of AIHuman-AI Interaction

The course consists of three parts that introduce and explore the design of extended realities along different axes: a framing perspective, illustrating what XR is, how it has evolved, and how designing XR differs from traditional digital design practices; a methodological perspective, detailing those XR-specific theory and methods that address XR design issues; and a practical perspective, exploring best practices and concrete design activities through direct application of these to a case.

Each part consists of lectures, readings, supervision, and an assignment centered on the specific topics discussed in the part of the course.

Assignments are carried out by students individually and will be peer-reviewed first and then discussed with the teachers and the class using a design critique approach.

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Göteborg

Societal Aspects of AIHuman-AI InteractionApplications of AI

Data is drastically changing how we function, both as individuals and as societies. An abundance of data is produced in every sector of society. Data is a product of every human activity, from counting steps or calories on an individual level, to measuring societal aspects such as level of education and employment.

The fundamental impact of this development gives rise to the need to ask question like: How do we use this data? For what purpose, and who benefits from it? This course will teach you how to begin answering such questions.

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Online

Machine LearningApplications of AI

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.

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Tillämpningar av AI

Målet med kursen är att deltagarna ska få kunskap om principer och metoder för business intelligens inom ramen för ett affärssystem. Kursen ingår i kurspaketet DIGIBUS (hh.se/digibus) där du som deltagare kan läsa hela kurspaketet eller enstaka kurser. Kursen är för yrkesverksamma och ges på distans på engelska. Anmälan är öppen så länge det finns möjlighet att bli antagen.

Behörighetskrav:

Kandidatexamen eller Högskoleingenjörsexamen.

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Online

Machine Learning

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.

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