Students and professionals in science, design and technology have to develop and communicate concepts that are often difficult to comprehend for the public, their peers and even themselves.

IMAGE | ABILITY – Visualizing the Unimaginable, will help you enhance your communication and interpersonal skills and provide insight, tips and tricks to make such complex and seemingly unimaginable concepts and ideas imaginable.

After finishing this course you will be more skilled in finding the right visual language to convey your ideas, thoughts and vision. You will be able to illustrate units and quantities, concepts and themes and you will know how to unravel complexity by using diagrams and schemes.

Learn about the implementation and practical aspects of Artificial Intelligence and how to write a plan for applying AI in your own organization in a step-by-step manner.

This course is not about difficult algorithms and complex programming; it is a course for anyone interested in learning how to integrate AI into their own organization.

To understand how current Artificial Intelligence applications can be successfully integrated in organizations, we look at different examples. For instance, how ING uses reinforcement learning for personalized dialog management with its customers or how Radboud UMC uses diagnostic image analysis to discover early stages of infectious diseases.

As part of our two-course program ‘AI in Practice’, this course will guide you in the practical aspects of applying AI in your own organization. You will examine typical applications of AI in use already and learn from their experience. These include challenges of implementation, lifecycle aspects, as well as the maintenance and management of AI applications.

The course presents a variety of case studies from actual situations in public organizations and private enterprises in the healthcare, financial, retail and telecommunications sectors. These include Radboud UMC, the Municipality of Amsterdam, ING, Ahold Delhaize and KPN.

‘AI in Practice – Applying AI’ gives you the ammunition to understand the practical aspects required for the implementation of a variety of AI applications in your organization.

Learn the fundamentals and principal AI concepts about clustering, dimensionality reduction, reinforcement learning and deep learning to solve real-life problems.

Learn the fundamentals of machine learning to help you correctly apply various classification and regression machine learning algorithms to real-life problems.

A one-stop shop to get started on the key considerations about data for AI! Learn how crowdsourcing offers a viable means to leverage human intelligence at scale for data creation, enrichment and interpretation, demonstrating a great potential to improve both the performance of AI systems and their trustworthiness and increase the adoption of AI in general.

The course treats the following topics: - Relevant physical oceanography - Elements of marine geology (seafloor topography, acoustical properties of sediments and rocks) - Underwater sound propagation (ray acoustics, ocean noise) - Interaction of sound with the seafloor (reflection, scattering) - Principles of sonar (beamforming) - Underwater acoustic mapping systems (single beam echo sounding, multi-beam echo sounding, sidescan sonar) - Data analysis (refraction corrections, digital terrain modelling) - Applications (hydrographic survey planning and navigation, coastal engineering) - Current and future developments.

This course introduces the basic components of an airframe structure and discusses their use and limitations. The realities of composite design such as the effect of material scatter, environmental knockdowns, and damage knockdowns are discussed and guidelines accounting for these effects and leading to robust designs are presented.

The resulting design constraints and predictive tools are applied to real-life design problems in composite structures. A brief revision of lamination theory and failure criteria leads into the development of analytical solutions for typical failure modes for monolithic skins (layup strength, buckling under combined loads and for a variety of boundary conditions) and stiffeners (strength, column buckling under a variety of loads and boundary conditions, local buckling or crippling for one-edge and no-edge-free conditions). These are then combined into stiffened composite structures where additional failure modes such as skin-stiffener separation are considered. Analogous treatment of sandwich skins examines buckling, wrinkling, crimping, intra-cellular buckling failure modes. Once the basic analysis and design techniques have been presented, typical designs (e.g. flange layup, stiffness, taper requirements) are presented and a series of design guidelines (stiffness mismatch minimization, symmetric and balanced layups, 10% rule, etc.) addressing layup and geometry are discussed. On the metal side, the corresponding design practices and analysis methods are presented for the more important failure modes (buckling, crippling) and comparisons to composite designs are made. A design problem is given in the end as an application of the material in this Part of the course.

This course will focus for a large part on MOSFET and CMOS, but also on heterojunction BJT, and photonic devices.First non-ideal characteristics of MOSFETs will be discussed, like channel-length modulation and short-channel effects. We will also pay attention to threshold voltage modification by varying the dopant concentration. Further, MOS scaling will be discussed. A combination of an n-channel and p-channel MOSFET is used for CMOS devices that form the basis for current digital technology. The operation of a CMOS inverter will be explained. We will explain in more detail how the transfer characteristics relate to the CMOS design.

This course is about the electronic properties of materials and contains lectures about scattering, transport in metals, phonons and superconductivity.

This course is designed to introduce students who wish to specialize in stress analysis of thin-walled structures to more advanced topics such as the analysis of statically indeterminate structures, warping, constraint stresses, shear diffusion, and elements of plate bending.

How can you reduce the energy loss of your home? What is the underlying science of energy loss in pipes? Which heat and mass transfer problems do we have to tackle to make consumer products?

In this engineering course, you will learn about the engineering principles that play an important role in all of these and more phenomena. You will learn about microbalances, radiation, convection, diffusion and more and their applications in everyday life.

This advanced course is for engineers who want to refresh their knowledge, engineering students who are eager to learn more about heat/mass transport and for all who have fun in explaining the science of phenomena in nature.

Building on Complex Adaptive Systems theory and basic Agent Based Modeling knowledge presented in SPM4530, the Advanced course will focus on the model development process. The students are expected to conceptualize, develop and verify a model during the course, individually or in a group. The modeling tasks will be, as much as possible, based on real life research problems, formulated by various research groups from within and outside the faculty.
Study Goals The main goal of the course is to learn how to form a modeling question, perform a system decomposition, conceptualize and formalize the system elements, implement and verify the simulation and validate an Agent Based Model of a socio-technical system.

Our human society consists of many intertwined Large Scale Socio-Technical Systems (LSSTS), such as infrastructures, industrial networks, the financial systems etc. Environmental pressures created by these systems on Earth‰ŰŞs carrying capacity are leading to exhaustion of natural resources, loss of habitats and biodiversity, and are causing a resource and climate crisis. To avoid this sustainability crisis, we urgently need to transform our production and consumption patterns. Given that we, as inhabitants of this planet, are part of a complex and integrated global system, where and how should we begin this transformation? And how can we also ensure that our transformation efforts will lead to a sustainable world? LSSTS and the ecosystems that they are embedded in are known to be Complex Adaptive Systems (CAS). According to John Holland CAS are "...a dynamic network of many agents (which may represent cells, species, individuals, firms, nations) acting in parallel, constantly acting and reacting to what the other agents are doing. The control of a CAS tends to be highly dispersed and decentralized. If there is to be any coherent behavior in the system, it will have to to arise from competition and cooperation among the agents themselves. The overall behavior of the system is the result of a huge number of decisions made every moment" by many individual agents. Understanding Complex Adaptive Systems requires tools that themselves are complex to create and understand. Shalizi defines Agent Based Modeling as "An agent is a persistent thing which has some state we find worth representing, and which interacts with other agents, mutually modifying each other‰ŰŞs states. The components of an agent-based model are a collection of agents and their states, the rules governing the interactions of the agents and the environment within which they live." This course will explore the theory of CAS and their main properties. It will also teach you how to work with Agent Based Models in order to model and understand CAS.

This course treats various methods to design and analyze datastructures and algorithms for a wide range of problems. The most important new datastructure treated is the graph, and the general methods introduced are: greedy algorithms, divide and conquer, dynamic programming and network flow algorithms. These general methods are explained by a number of concrete examples, such as simple scheduling algorithms, Dijkstra, Ford-Fulkerson, minimum spanning tree, closest-pair-of-points, knapsack, and Bellman-Ford. Throughout this course there is significant attention to proving the correctness of the discussed algorithms. All material for this course is in English. The recorded lectures, however, are in Dutch.

An introductory course in analog circuit synthesis for microelectronic designers. Topics include: Review of analog design basics; linear and non-linear analog building blocks: harmonic oscillators, (static and dynamic) translinear circuits, wideband amplifiers, filters; physical layout for robust analog circuits; design of voltage sources ranging from simple voltage dividers to high-performance bandgaps, and current source implementations from a single resistor to high-quality references based on negative-feedback structures.

Software testing gets a bad rap for being difficult, time-consuming, redundant, and above all – boring. But in fact, it is a proven way to ensure that your software will work flawlessly and can meet release schedules.

In a two-course series, we will teach you automated software testing in an inspiring way. We will show you that testing is not as daunting a task as you might think, and how automated testing will make you a better developer who programs excellent software.

This second course builds upon the first course’s material. It covers more advanced tools and techniques and their applications, now utilizing more than just JUnit. Key topics include Test-Driven Development, state-based and web testing, combinatorial testing, mutation testing, static analysis tools, and property-based testing.

This is a highly practical course. Throughout the lessons, you will test various programs by means of different techniques. By the end, you will be able to choose the best testing strategies for different projects.

Have you ever wondered why ventilation helps to cool down your hot chocolate? Do you know why a surfing suit keeps you warm? Why iron feels cold, while wood feels warm at room temperature? Or how air is transferred into aqueous liquids in a water treatment plant? How can we sterilize milk with the least amount of energy? Or how do we design a new cooling tower of a power plant?

Transport Phenomena addresses questions like these and many more, exploring a wide variety of applications ranging from industrial processes to daily life problems and even to bioprocesses in our own body.

In Transport Phenomena, the transport and transfer of momentum, heat and mass are studied. To understand these processes which often take place simultaneously, the underlying concepts will be covered in this course.

Design of shoreline protection along rivers, canals and the sea; load on bed and shoreline by currents, wind waves and ship motion; stability of elements under current and wave conditions; stability of shore protection elements; design methods, construction methods. Flow: recapitulation of basics from fluid mechanics (flow, turbulence), stability of individual grains (sand, but also rock) in different type of flow conditions (weirs, jets), scour and erosion. Porous Media: basic equation, pressures and velocities on the stability on the boundary layer; groundwater flow with impermeable and semi-impermeable structures; granular filters and geotextiles. Waves: recapitulation of the basics of waves, focus on wave forces on the land-water boundary, specific aspects of ship induced waves, stability of elements under wave action (loose rock, placed blocks, impermeable layers) Design: overview of the various types of protections, construction and maintenance; design requirements, deterministic and probabilistic design; case studies, examples Materials and environment: overview of materials to be used, interaction with the aquatic environment, role of the land-water boundary as part of the ecosystem; environmentally sound shoreline design.

If you’re a coastal engineer, ecologist or planner, then this is the course for you. You already know that engineering and ecological principles are not enough to realize nature-friendly solutions in practice. You need people on your side!

In this course you will learn how to build a relevant coalition of stakeholders to support the design and implementation of ecosystem-based hydraulic infrastructures. After learning basic stakeholder mapping and game theory techniques, you will apply Social Design Principles to a Building with Nature ecosystem-based design case. This will equip you to identify promising collaborative arrangements for your engineering or planning practice.

The course builds on the previous Building with Nature MOOC, which explored the use of natural materials and ecological processes in achieving effective and sustainable hydraulic infrastructure designs, distilling Engineering and Ecological Design Principles. In this course, the missing element of Social Design Principles are developed and taught.

You’ll learn from renowned Dutch engineers and international environmental scientists, who work at the technical- governance interface. Iconic examples such as the Maasvlakte II expansion to Rotterdam Harbor and the Delfland Sand Engine Mega-nourishment serve as study material. The challenges in designing and implementing these nature-friendly hydraulic infrastructures are explored by the eminent professors who were responsible for their genesis.

Join us in becoming one of the new generation of engineers, ecologists and planners who see the Building with Nature integrated design approach as critical to hydraulic engineering, nature and society.

While big data infiltrates all walks of life, most firms have not changed sufficiently to meet the challenges that come with it. In this course, you will learn how to develop a big data strategy, transform your business model and your organization.

This course will enable professionals to take their organization and their own career to the next level, regardless of their background and position.

Professionals will learn how to be in charge of big data instead of being subject to it. In particular, they will become familiar with tools to:

assess their current situation regarding potential big data-induced changes of a disruptive nature,
identify their options for successfully integrating big data in their strategy, business model and organization, or if not possible, how to exit quickly with as little loss as possible, and
strengthen their own position and that of their organization in our digitalized knowledge economy
The course will build on the concepts of product life cycles, the business model canvas, organizational theory and digitalized management jobs (such as Chief Digital Officer or Chief Informatics Officer) to help you find the best way to deal with and benefit from big data induced changes.