Kibera, a poor community, in Nairobi, was a blank spot on the map until recently. This video from Penn State Public Broadcasting’s Geospatial Revolution shows how geospatial technology enabled residents to map resources to help their community.

These 20 Broad General Education lesson plans focus on the creative and collaborative aspects of computational thinking, programming and coding, building girls confidence and resilience by embedding these concepts through interdisciplinary learning into Literacy & English, health and wellbeing, mathematics, sciences, art & design, music, social subjects and physical education.

The resource packs comprise of lesson plans, PowerPoint presentations, video tutorials and website recommendations and provide a wealth of engaging and inspiring learning experiences for teachers to use with their class over a period of a week, a term or over the academic year.

This course provides a challenging introduction to some of the central ideas of theoretical computer science. It attempts to present a vision of "computer science beyond computers": that is, CS as a set of mathematical tools for understanding complex systems such as universes and minds. Beginning in antiquity--with Euclid's algorithm and other ancient examples of computational thinking--the course will progress rapidly through propositional logic, Turing machines and computability, finite automata, GĚŚdel's theorems, efficient algorithms and reducibility, NP-completeness, the P versus NP problem, decision trees and other concrete computational models, the power of randomness, cryptography and one-way functions, computational theories of learning, interactive proofs, and quantum computing and the physical limits of computation. Class participation is essential, as the class will include discussion and debate about the implications of many of these ideas.

6.776 covers circuit and system level design issues of high speed communication systems, with primary focus being placed on wireless and broadband data link applications. Specific circuit topics include transmission lines, high speed and low noise amplifiers, VCO's, and high speed digital circuits. Specific system topics include frequency synthesizers, clock and data recovery circuits, and GMSK transceivers. In addition to learning analysis skills for the above items, students will gain a significant amount of experience in simulating circuits in SPICE and systems in CppSim (a custom C++ simulator).

6.976 covers system level issues of high speed communication systems and their impact on circuit requirements, with primary focus being placed on wireless and broadband data link applications. Course topics include: transistor level design techniques for high speed amplifiers, mixers, VCO's, registers and gates, and phase locked loops, and the impact of transmission line effects on circuit designs for narrowband and broadband systems. Finally, behavioral level simulation techniques are presented for phase locked loops and other communication circuits.

The single most important skill for a computer scientist is problem solving. The goal of this book is to teach you to think like a computer scientist.

Python is a fun and extremely easy-to-use programming language that has steadily gained in popularity over the last few years. Developed over ten years ago by Guido van Rossum, Python's simple syntax and overall feel is largely derived from ABC, a teaching language that was developed in the 1980's. However, Python was also created to solve real problems and it borrows a wide variety of features from programming languages such as C++, Java, Modula-3, and Scheme. Because of this, one of Python's most remarkable features is its broad appeal to professional software developers, scientists, researchers, artists, and educators. 278 page pdf file.

The course is a comprehensive introduction to the theory, algorithms and applications of integer optimization and is organized in four parts: formulations and relaxations, algebra and geometry of integer optimization, algorithms for integer optimization, and extensions of integer optimization.

This course is intended to assist undergraduates with learning the basics of programming in general and programming MATLAB in particular.

Designed as a freshmen seminar course, faculty from various School of Engineering departments describe the research and educational opportunities specific to and offered by their departments. Background lectures by the 20.010J staff introduce students to the fundamental scientific basis for bioengineering. Specially produced videos provide additional background information that is supplemented with readings from newspaper and magazine articles. Bioengineering at MIT is represented by the diverse curricula offered by most Departments in the School of Engineering. This course samples the wide variety of bioengineering options for students who plan to major in one of the undergraduate Engineering degree programs. The beginning lectures describe the science basis for bioengineering with particular emphasis on molecular cell biology and systems biology. Bioengineering faculty will then describe the bioengineering options in a particular engineering course as well as the type of research conducted by faculty in the department.

This is a fast-paced introductory course to the C++ programming language. It is intended for those with little programming background, though prior programming experience will make it easier, and those with previous experience will still learn C++-specific constructs and concepts. This course is offered during the Independent Activities Period (IAP), which is a special 4-week term at MIT that runs from the first week of January until the end of the month.

Dear student! You are starting to learn about computation and its purpose. This course covers the same materials as an introductory class for undergraduate computer science majors. Its curriculum, which includes software, hardware and algorithms, resembles that of a one- or two-semester first-year college course or the high school Advanced Placement (AP) Computer Science. It does not require a formal computer science background.

This course presents the fundamentals of object-oriented software design and development, computational methods and sensing for engineering, and scientific and managerial applications. It cover topics, including design of classes, inheritance, graphical user interfaces, numerical methods, streams, threads, sensors, and data structures. Students use Java programming language to complete weekly software assignments. How is 1.00 different from other intro programming courses offered at MIT? 1.00 is a first course in programming. It assumes no prior experience, and it focuses on the use of computation to solve problems in engineering, science and management. The audience for 1.00 is non-computer science majors. 1.00 does not focus on writing compilers or parsers or computing tools where the computer is the system; it focuses on engineering problems where the computer is part of the system, or is used to model a physical or logical system. 1.00 teaches the Java programming language, and it focuses on the design and development of object-oriented software for technical problems. 1.00 is taught in an active learning style. Lecture segments alternating with laboratory exercises are used in every class to allow students to put concepts into practice immediately; this teaching style generates questions and feedback, and allows the teaching staff and students to interact when concepts are first introduced to ensure that core ideas are understood. Like many MIT classes, 1.00 has weekly assignments, which are programs based on actual engineering, science or management applications. The weekly assignments build on the class material from the previous week, and require students to put the concepts taught in the small in-class labs into a larger program that uses multiple elements of Java together.

This course aims to give students the tools and training to recognize convex optimization problems that arise in scientific and engineering applications, presenting the basic theory, and concentrating on modeling aspects and results that are useful in applications. Topics include convex sets, convex functions, optimization problems, least-squares, linear and quadratic programs, semidefinite programming, optimality conditions, and duality theory. Applications to signal processing, control, machine learning, finance, digital and analog circuit design, computational geometry, statistics, and mechanical engineering are presented. Students complete hands-on exercises using high-level numerical software. Acknowledgements The course materials were developed jointly by Prof. Stephen Boyd (Stanford), who was a visiting professor at MIT when this course was taught, and Prof. Lieven Vanderberghe (UCLA).

An introduction to several fundamental ideas in electrical engineering and computer science, using digital communication systems as the vehicle. The three parts of the course - bits, signals, and packets - cover three corresponding layers of abstraction that form the basis of communication systems like the Internet. The course teaches ideas that are useful in other parts of EECS: abstraction, probabilistic analysis, superposition, time and frequency-domain representations, system design principles and trade-offs, and centralized and distributed algorithms. The course emphasizes connections between theoretical concepts and practice using programming tasks and some experiments with real-world communication channels.

This course is an introduction to linear optimization and its extensions emphasizing the underlying mathematical structures, geometrical ideas, algorithms and solutions of practical problems. The topics covered include: formulations, the geometry of linear optimization, duality theory, the simplex method, sensitivity analysis, robust optimization, large scale optimization network flows, solving problems with an exponential number of constraints and the ellipsoid method, interior point methods, semidefinite optimization, solving real world problems problems with computer software, discrete optimization formulations and algorithms.

This subject provides an introduction to modeling and simulation, covering continuum methods, atomistic and molecular simulation, and quantum mechanics. Hands-on training is provided in the fundamentals and applications of these methods to key engineering problems. The lectures provide exposure to areas of application based on the scientific exploitation of the power of computation. We use web based applets for simulations, thus extensive programming skills are not required.

" This course is an introduction to software engineering, using the Java™ programming language. It covers concepts useful to 6.005. Students will learn the fundamentals of Java. The focus is on developing high quality, working software that solves real problems. The course is designed for students with some programming experience, but if you have none and are motivated you will do fine. Students who have taken 6.005 should not take this course. Each class is composed of one hour of lecture and one hour of assisted lab work. This course is offered during the Independent Activities Period (IAP), which is a special 4-week term at MIT that runs from the first week of January until the end of the month."

The aim of this video lesson is to teach students about the different topologies of computer networks and how they function. The approach that is used is highly correlated with common knowledge about weddings and the local Malay culture associated with weddings. Students should be able to relate the act of delivering food to a large crowd of people to the basic principles of network topologies and the method of data transfer within each type of topology. The lesson will begin in a classroom with students working in small groups, answering assigned questions. Teaching aids such as color cards will be used. One student from each group will be appointed as the wedding event manager, and she/he will have to discuss and act out with group members in order to answer more challenging questions. At the end of the lesson, students will be asked to come up with their own version of a hybrid computer network topology. The lesson concept taught here not only educates students on computer topologies, but also introduces students to an important cultural perspective of Malaysia. Above all, this video is designed to assist students with their study of Computer Literacy in schools. The lesson will take up to 60 minutes to complete. Materials needed include: 10 red cards representing waitresses; 10 green cards representing waiters; 10 blue cards representing tables in the hall; a sketch book; and classroom tables and chairs.

This course focuses on introducing the language, libraries, tools and concepts of Java®. The course is specifically targeted at students who intend to take 6.170 in the following term and feel they would struggle because they lack the necessary background. Topics include: Object-oriented programming, primitives, arrays, objects, inheritance, interfaces, polymorphism, hashing, data structures, collections, nested classes, floating point precision, defensive programming, and depth first search algorithm.