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Courseware
This is a graduate-level introduction to mathematics of information theory. We will cover both classical and modern topics, including information entropy, lossless data compression, binary hypothesis testing, channel coding, and lossy data compression.
- Subjects:
- Computing and Mathematics and Statistics
- Keywords:
- Information theory Information theory in mathematics
- Resource Type:
- Courseware
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Courseware
6.005 Software Construction introduces fundamental principles and techniques of software development, i.e., how to write software that is safe from bugs, easy to understand, and ready for change. The course includes problem sets and a final project. Important topics include specifications and invariants; testing; abstract data types; design patterns for object-oriented programming; concurrent programming and concurrency; and functional programming.
- Subjects:
- Computing
- Keywords:
- Computer programming Computer software -- Development
- Resource Type:
- Courseware
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Courseware
6.0002 is the continuation of 6.0001 Introduction to Computer Science and Programming in Python and is intended for students with little or no programming experience. It aims to provide students with an understanding of the role computation can play in solving problems and to help students, regardless of their major, feel justifiably confident of their ability to write small programs that allow them to accomplish useful goals. The class uses the Python 3.5 programming language.
- Subjects:
- Computing
- Keywords:
- Computer programming Computer science Python (Computer program language)
- Resource Type:
- Courseware
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Courseware
6.0001 Introduction to Computer Science and Programming in Python is intended for students with little or no programming experience. It aims to provide students with an understanding of the role computation can play in solving problems and to help students, regardless of their major, feel justifiably confident of their ability to write small programs that allow them to accomplish useful goals. The class uses the Python 3.5 programming language.
- Subjects:
- Computing
- Keywords:
- Computer programming Computer science Python (Computer program language)
- Resource Type:
- Courseware
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Courseware
This course is an introduction to the theory and practice of the process of designing games and playful experiences. Students are familiarized with methods, concepts, techniques, and literature used in the design of games. The strategy is process-oriented, focusing on aspects such as: Rapid prototyping, play testing, and design iteration using a player-centered approach.
- Subjects:
- Interactive and Digital Media and Computing
- Keywords:
- Games
- Resource Type:
- Courseware
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Courseware
With the growing availability and lowering costs of genotyping and personal genome sequencing, the focus has shifted from the ability to obtain the sequence to the ability to make sense of the resulting information. This course is aimed at exploring the computational challenges associated with interpreting how sequence differences between individuals lead to phenotypic differences in gene expression, disease predisposition, or response to treatment.
- Subjects:
- Computing and Biology
- Keywords:
- Genomics Genomes
- Resource Type:
- Courseware
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Courseware
This course is an introduction to principles and techniques of visual communication, and provides opportunities for science and engineering majors to acquire practical skills in the visual computer arts, in a studio environment. Students will learn how to create graphics for print and web, animations, and interactive media, and how to use these techniques to effectively communicate scientific and engineering concepts for learning and teaching. This class involves three hands-on creative projects, which will be presented in class.
- Subjects:
- Computing and Visualisation
- Keywords:
- Information visualization
- Resource Type:
- Courseware
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Courseware
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.
- Subjects:
- Computing
- Keywords:
- Algorithms Data structures (Computer science)
- Resource Type:
- Courseware
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Courseware
Computability Theory deals with one of the most fundamental questions in computer science: What is computing and what are the limits of what a computer can compute? Or, formulated differently: “What kind of problems can be algorithmically solved?” During the course this question will be studied. Firstly, the notion of algorithm or computing will be made precise by using the mathematical model of a Turing machine. Secondly, it will be shown that basic issues in computer science, like “Given a program P does it halt for any input x?” or “Given two program P and Q, are they equivalent?” cannot be solved by any Turing machine. This shows that there exist problems that are impossible to solve with a computer, the so-called “undecidable problems”. The book is in English, the recorded lectures and slides however, are in Dutch
- Subjects:
- Computing
- Keywords:
- Machine theory Computational complexity Computable functions
- Resource Type:
- Courseware
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Courseware
Are you ready to leave the sandbox and go for the real deal? Have you followed Data Analysis: Take It to the MAX() and Data Analysis: Visualization and Dashboard Design and are ready to carry out more robust data analysis? In this project-based course you will engage in a real data analysis project that simulates the complexity and challenges of data analysts at work. Testing, data wrangling, Pivot Tables, sparklines? Now that you have mastered them you are ready to apply them all and carry out an independent data analysis. For your project, you will pick one raw dataset out of several options, which you will turn into a dashboard. You will begin with a business question that is related to the dataset that you choose. The datasets will touch upon different business domains, such as revenue management, call-center management, investment, etc.
- Subjects:
- Computing
- Keywords:
- Visual analytics Information visualization Industrial management -- Data processing Dashboards (Management information systems)
- Resource Type:
- Courseware
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