The Advanced Certificate and the Advanced Diploma in Applications of ICT in Libraries permit library staff to obtain accreditation for their skills in the use of ICT. Anyone can make use of the materials and assessment is available in variety of modes, including distance learning.
This course introduces students to the basic knowledge representation, problem solving, and learning methods of artificial intelligence. Upon completion of 6.034, students should be able to develop intelligent systems by assembling solutions to concrete computational problems, understand the role of knowledge representation, problem solving, and learning in intelligent-system engineering, and appreciate the role of problem solving, vision, and language in understanding human intelligence from a computational perspective.
This course provides a challenging introduction to some of the central ideas of theoretical computer science. Beginning in antiquity, the course will progress through finite automata, circuits and decision trees, Turing machines and computability, efficient algorithms and reducibility, the P versus NP problem, NP-completeness, the power of randomness, cryptography and one-way functions, computational learning theory, and quantum computing. It examines the classes of problems that can and cannot be solved by various kinds of machines. It tries to explain the key differences between computational models that affect their power.
The book presents a coherent theory of building information, focusing on its representation and management in the digital era. It addresses issues such as the information explosion and the structure of analogue building representations to propose a parsimonious approach to the deployment and utilization of symbolic digital technologies like BIM.
Students work in small collaborative design teams to propose, build, and document a semester-long project focused on mobile applications for cell phones. Additional assignments include creating several small mobile applications such as context-aware mobile media capture and games. Students document their work through a series of written and oral proposals, progress reports, and final reports. This course covers the basics of J2ME and explores mobile imaging and media creation, GPS location, user-centered design, usability testing, and prototyping. Java experience is recommended.
This course introduces programming languages and techniques used by physical scientists: FORTRAN, C, C++, MATLAB, and Mathematica. Emphasis is placed on program design, algorithm development and verification, and comparative advantages and disadvantages of different languages.
This course analyzes issues associated with the implementation of higher-level programming languages. Topics covered include: fundamental concepts, functions, and structures of compilers, the interaction of theory and practice, and using tools in building software. The course includes a multi-person project on compiler design and implementation.
This course will focus on fundamental subjects in convexity, duality, and convex optimization algorithms. The aim is to develop the core analytical and algorithmic issues of continuous optimization, duality, and saddle point theory using a handful of unifying principles that can be easily visualized and readily understood.
This course focuses on cyberspace and its implications for private and public, sub-national, national, and international actors and entities.
The MIT Libraries Data Management Group hosts a set of workshops during IAP and throughout the year to assist MIT faculty and researchers with data set control, maintenance, and sharing. This resource contains a selection of presentations from those workshops. Topics include an introduction to data management, details on data sharing and storage, data management using the DMPTool, file organization, version control, and an overview of the open data requirements of various funding sources.
This course relies on primary readings from the database community to introduce graduate students to the foundations of database systems, focusing on basics such as the relational algebra and data model, schema normalization, query optimization, and transactions. It is designed for students who have taken 6.033 (or equivalent); no prior database experience is assumed, though students who have taken an undergraduate course in databases are encouraged to attend.
This is a collection of all materials used in Health Information Technology by Dr. Chi Zhang at Kennesaw State University, including lecture slides, assignments, and assessments, including a question bank.
Topics covered include:
Clinical Financial Records
Patient Bedside Systems
Health Information Networks
HIPAA Privacy and Security
This course will provide a gentle, yet intense, introduction to programming using Python for highly motivated students with little or no prior experience in programming. The course will focus on planning and organizing programs, as well as the grammar of the Python programming language. The course is designed to help prepare students for 6.01 Introduction to EECS. 6.01 assumes some knowledge of Python upon entering; the course material for 6.189 has been specially designed to make sure that concepts important to 6.01 are covered. 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.
This course is a collaborative offering of Sana, Partners in Health, and the Institute for Healthcare Improvement (IHI). The goal of this course is the development of innovations in information systems for developing countries that will (1) translate into improvement in health outcomes, (2) strengthen the existing organizational infrastructure, and (3) create a collaborative ecosystem to maximize the value of these innovations. The course will be taught by guest speakers who are internationally recognized experts in the field and who, with their operational experiences, will outline the challenges they faced and detail how these were addressed.This OCW site combines resources from the initial Spring 2011 offering of the course (numbered HST.184) and the Spring 2012 offering (numbered HST.S14).
To be information literate, a person must be able to recognize when information is needed and have the ability to locate, evaluate, and use effectively the needed information. By the end of this unit you will be able to Define Information Literacy, Define the four domains that fall under Metaliterate Learners, Identify a lack of knowledge in a subject area, Identify a search topic/question and define it using simple terminology, Articulate current knowledge on a topic, Recognize a need for information and data to achieve a specific end and define limits to the information need, and Manage time effectively to complete a search.
This collection brings together scholarship and pedagogy from multiple perspectives and disciplines, offering nuanced and complex perspectives on Information Literacy in the second decade of the 21st century. Taking as a starting point the concerns that prompted the Association of Research Libraries (ACRL) to review the Information Literacy Standards for Higher Education and develop the Framework for Information Literacy for Higher Education (2015), the chapters in this collection consider six frameworks that place students in the role of both consumer and producer of information within today's collaborative information environments. Contributors respond directly or indirectly to the work of the ACRL, providing a bridge between past/current knowledge and the future and advancing the notion that faculty, librarians, administrators, and external stakeholders share responsibility and accountability for the teaching, learning, and research of Information Literacy.
Good researchers have a host of tools at their disposal that make navigating today’s complex information ecosystem much more manageable. Gaining the knowledge, abilities, and self-reflection necessary to be a good researcher helps not only in academic settings, but is invaluable in any career, and throughout one’s life. The Information Literacy User’s Guide will start you on this route to success.The Information Literacy User’s Guide is based on two current models in information literacy: The 2011 version of The Seven Pillars Model, developed by the Society of College, National and University Libraries in the United Kingdom and the conception of information literacy as a metaliteracy, a model developed by one of this book’s authors in conjunction with Thomas Mackey, Dean of the Center for Distance Learning at SUNY Empire State College. These core foundations ensure that the material will be relevant to today’s students.The Information Literacy User’s Guide introduces students to critical concepts of information literacy as defined for the information-infused and technology-rich environment in which they find themselves. This book helps students examine their roles as information creators and sharers and enables them to more effectively deploy related skills. This textbook includes relatable case studies and scenarios, many hands-on exercises, and interactive quizzes.
6.441 offers an introduction to the quantitative theory of information and its applications to reliable, efficient communication systems. Topics include mathematical definition and properties of information, source coding theorem, lossless compression of data, optimal lossless coding, noisy communication channels, channel coding theorem, the source channel separation theorem, multiple access channels, broadcast channels, Gaussian noise, and time-varying channels.
This course is intended to assist undergraduates with learning the basics of programming in general and programming MATLAB in particular.
This course provides an introduction to mathematical modeling of computational problems. It covers the common algorithms, algorithmic paradigms, and data structures used to solve these problems. The course emphasizes the relationship between algorithms and programming, and introduces basic performance measures and analysis techniques for these problems.