There is no doubt that quantum computers and the quantum internet will have a great impact on our world. But we don’t yet know quite how. As with traditional computers – we will only see the effects in the decades to come.

This course will provide you with a basic understanding of quantum computing and the quantum internet. Together, we’ll peek into the fascinating world of quantum phenomena, such as qubits, superposition, and entanglement.

We’ll envision the potential impact of quantum computing and the quantum internet.

You’ll explore various application areas, such as quantum chemistry, quantum machine learning, encryption and secure communication, factorization, and blind quantum computation.

The course is aimed at a broad and diverse audience including policy-makers, people with a scientific or personal interest, business executives, and students at all levels.

We invite you on a journey beyond what is known to us now, and to envision a world with quantum technologies.

This journey will continue in a second course planned for May 2018, where we will expand from an understanding of the building blocks of Quantum Computers to look at further applications and possibilities.

This course is authored by experts from the QuTech research center at Delft University of Technology. In the center scientists and engineers work together to enhance research and development in quantum technology. QuTech Academy’s aim is to inspire, share and disseminate knowledge about the latest developments in quantum technology.

Studies how randomization can be used to make algorithms simpler and more efficient via random sampling, random selection of witnesses, symmetry breaking, and Markov chains. Models of randomized computation. Data structures: hash tables, and skip lists. Graph algorithms: minimum spanning trees, shortest paths, and minimum cuts. Geometric algorithms: convex hulls, linear programming in fixed or arbitrary dimension. Approximate counting; parallel algorithms; online algorithms; derandomization techniques; and tools for probabilistic analysis of algorithms.

"Requirements Engineering: A Modern Approach to the Requirements Engineering Body of Knowledge" provides an insight into the process of defining and documenting requirements in the engineering design process. The book provides a broad view of existing software standards, practices and methods and an insight into evaluating and critiquing requirements for consistency and technical feasibility.

In this seminar, students will design and perfect a digital environment to house the activities of large-scale organizations of people making bottom-up decisions, such as with citizen-government affairs, voting corporate shareholders or voting members of global non-profits and labor unions. A working Open Source prototype created last semester will be used as the starting point, featuring collaborative filtering and electronic agent technology pioneered at the Media Lab. This course focuses on development of online spaces as part of an interdependent human environment, including physical architectures, mapped work processes and social/political dimensions. A cross-disciplinary approach will be taken; students with background in architecture, urban planning, law, cognition, business, digital media and computer science are encouraged to participate. No prior technical knowledge is necessary, though a rudimentary understanding of web page creation is helpful.

Programming continues to be a an important skill in the modern world. Childhood is a great time start learning programming and to develop computational thinking creativity, and problem- solving skills!

This course teaches programming in Scratch through fun videos which explains programming in an inspiring and clear way. These are accompanied with assignments which let kids to practice programming and create programs they will like to use themselves!

On a weekly basis, we will be creating a game: a maze, an aquarium, a Flappy Bird Game and a Super Mario look-a-like. Every week, new programming blocks are taught and together we’re working on ways to improve your written code.

This course is an English version of a course that was used in primary schools in The Netherlands with great success. The material follows the educational curriculum for programming in primary education of The Netherlands.

Do you want to participate with more children? Create a personal account for every child or pupil in order for them to work at their own pace. Once they have fulfilled the entire course and were upgraded to the ID Verified track, a Scratch diploma with their names will be handed out.

Programming is becoming a more and more important skill to have. Childhood is a great time to start learning programming and to develop computational thinking, creativity, and problem- solving skills. In this course you will learn the basics of programming and how to teach it yourself as a primary or secondary school teacher.

This MOOC teaches programming in Scratch through fun videos which explain programming in an inspiring and clear way.

Every week you build a different Scratch project yourself: a flappy bird game, a virtual pet or a Mondriaan like artwork. Also weekly, new programming blocks are taught and together we’re working on ways to improve your written code. In addition, you will learn how you can integrate the same programming lessons in your class for both primary and secondary education.

Many programming principles covered in Scratch also apply to other programming languages such as JavaScript and Python. An introduction to Python as well as hardware such as robotics and a micro:bit are a part of this online course should you want to broaden your scope.

The content of this course is based on a course that was used in primary schools in The Netherlands with great success. The material follows the educational curriculum for programming in primary education of The Netherlands.

This course is an introduction to the theory that tries to explain how minds are made from collections of simpler processes. It treats such aspects of thinking as vision, language, learning, reasoning, memory, consciousness, ideals, emotions, and personality. It incorporates ideas from psychology, artificial intelligence, and computer science to resolve theoretical issues such as wholes vs. parts, structural vs. functional descriptions, declarative vs. procedural representations, symbolic vs. connectionist models, and logical vs. common-sense theories of learning.

This course presents software engineering concepts and principles in parallel with the software development life cycle. Topics addressed include the Software Development Life Cycle (SDLC), software modeling using Unified Modeling Language (UML), major phases of SDLC (Software Requirements and Analysis, Software Design, and Software Testing), and project management. Upon successful completion of this course, the student will be able to: demonstrate mastery of software engineering knowledge and skills, and professional issues necessary to practice software engineering; discuss principles of software engineering; describe software development life cycle models; learn principles of software modeling through UML as a modeling language; identify major activities and key deliverables in a software development life cycle during software requirements and analysis, software design, and software testing; apply the object-oriented methodology in software engineering to create UML artifacts for software analysis and requirements, software design, and software testing; apply project management concepts in a software engineering environment to manage project, people, and product; participate as an individual and as part of a team to deliver quality software systems. This free course may be completed online at any time. (Computer Science 302)

A reading and discussion subject on advanced topics in the engineering of software systems. Focus on software development. Topics differ but are chosen from: software process and lifecycle; requirements development, specification and analysis; design principles; testing, formal analysis, and reviews; quality management and assessment; product and process metrics; COTS and reuse; evolution and maintenance; team organization and people management; software engineering aspects of programming languages; and software psychology. Prerequisite is basic knowledge of programming and an introductory class in software engineering. The second prerequisite can be waived with permission of the instructor and additional background reading.

Spec is the default UI framework for Pharo. To build UI’s in Spec existing widgets or even complete UI’s are reused and configured to form a new UI.

This book first shows the basics of Spec and how it enables reuse of UIs. It then treats UI layout in detail before moving on to explaining the management of windows. Some of the more advanced widgets are also discussed as well as the dynamic features of Spec. Lastly, the book also contains a chapter with tips and tricks.

Survey of structural properties of natural languages, with special emphasis on the sound pattern. Representation of the lexicon. Physiology of speech production, articulatory phonetics. Acoustical theory of speech production; acoustical and articulatory descriptions of phonetic features and of prosodic aspects of speech. Perception of speech. Models of lexical access and of speech production and planning. Applications to recognition and generation of speech by machine, and to the study of speech disorders.

Squeak is a modern open-source development environment for the classic Smalltalk-80 programming language. Despite being the first purely object-oriented language and environment, Smalltalk is in many ways still far ahead of its successors in promoting a vision of an environment where everything is an object, and anything can change at run-time.

Fundamentals of detection and estimation for signal processing, communications, and control. Vector spaces of random variables. Bayesian and Neyman-Pearson hypothesis testing. Bayesian and nonrandom parameter estimation. Minimum-variance unbiased estimators and the Cramer-Rao bounds. Representations for stochastic processes; shaping and whitening filters; Karhunen-Loeve expansions. Detection and estimation from waveform observations. Advanced topics: linear prediction and spectral estimation; Wiener and Kalman filters.

Provides an integrated approach to understanding the practice of engineering in the real world. Students research the life cycle of a major engineering project, new technology, or startup company from multiple perspectives: technical, economic, political, cultural. Emphasis on analyzing engineering artifacts, understanding documentation, framing logical arguments, communicating effectively, and working in teams.

The disciplines of music history and music theory have been slow to embrace the digital revolutions that have transformed other fields' text-based scholarship (history and literature in particular). Computational musicology opens the door to the possibility of understanding - even if at a broad level - trends and norms of behavior of large repertories of music. This class presents the major approaches, results, and challenges of computational musicology through readings in the field, gaining familiarity with datasets, and hands on workshops and assignments on data analysis and "corpus" (i.e., repertory) studies. Class sessions alternate between discussion/lecture and labs on digital tools for studying music. A background in music theory and/or history is required, and experience in computer programming will be extremely helpful. Coursework culminates in an independent research project in quantitative or computational musicology that will be presented to the class as a whole.

The purpose of this course is to learn how to specify the behavior of embedded systems and to experience the design
of a provably correct system. In this course you will learn how to formally
specify requirements and to prove (or disprove) them on the behaviour. With a practical assignment
you will experience how to apply the techniques in practice.

Technical Project Management in Living and Geometric Order demonstrates that even the best-laid project plans can be undone by new technologies, financial upheavals, or resource scarcity, to name just a few disruptors. It encourages project managers to focus on learning throughout a project, with the understanding that what they learn could necessitate major changes in midstream. This adaptive, flexible, living-order approach is inspired by Lean in construction projects and Agile in software development. Technical Project Management in Living and Geometric Order explains how today’s projects unfold in dynamic environments in response to unexpected events. With its practical tips, detailed graphics, links to additional resources, and interviews with engineering professionals, it’s an accessible introduction to the living order for aspiring project managers.

A graduate-level introduction to artificial intelligence. Topics include: representation and inference in first-order logic; modern deterministic and decision-theoretic planning techniques; basic supervised learning methods; and Bayesian network inference and learning.