General James Clapper, former United States Director of National Intelligence and the National Geospatial-Intelligence Agency (NGA), once said \everything happens somewhere.\" He stressed that there are aspects of time and place to every intelligence problem. In this course, you will examine how time and place work with general intelligence techniques to create geospatial intelligence. You will learn and apply critical thinking skills, structured analytical techniques, and other intelligence methods in a geospatial context. You'll also learn how to reduce personal and organizational bias by conducting an Analysis of Competing Hypotheses, by R. Heuer, a 45-year veteran of the CIA. As a result, you will be better prepared for the world of geospatial intelligence analysis."

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 role of the school librarian is evolving from keeper of library materials to leader in school reform. The digital age has elevated information literacy from the mechanics of searching and finding to thinking and inquiry. To meet this challenge the library facility is reconceptualized as a learning environment and the collection as a dynamic process of curation and access. Library staff, including paraprofessionals, student peers, and parent volunteers are viewed as instructional support. Allocated budgets are supplemented by funding sources such as grants and donations. The school librarian, trained in Action Research, can realize the library as learning center as she systematically collects evidence, sets priorities, and constructs a Strategic Plan. This module brings together the processes of action research, including identifying a problem in practice, formulating a research question, collecting and analyzing data to conduct a Community Scan and School Library Needs Assessment. She will apply her findings to building a Strategic Plan that will transform the school library into a learning center, or improve its existing functions.

Developed as part of a Round 14 Textbook Transformation Mini-Grant, this D2L course export provides a set of support resources in teaching Blockchain and Smart Contracts including presentations and notes.

This special course is designed to equip students with core foundational knowledge and innovative concepts, techniques, and industrial-strength tools for perceiving and developing blockchain and smart contracts in an engineering-supported manner. The course introduces blockchain-related practices and shows how to apply these practices to build decentralized applications using hands-on programming and research-led projects.

This open course was developed as part of a Round 11 Affordable Learning Georgia Textbook Transformation Grant and revised as part of a Round 13 Mini-Grant for use with business intelligence courses. It introduces the concepts, practices, technologies and systems of business intelligence and analytics, which supports data driven insights generation and decision making. The complete process of BI is covered using modern BI tools, from data gathering, modeling, analysis, reporting, and visualization. Course features include:

Hands-on experiences with Microsoft BI solutions of Excel and Power BI.
Opportunities for students to explore their own interests and learn from the unique experience though research.

How would you like to travel to new places while collaborating on a geospatial data challenge with students from around the world? In this class, students collaborate on a global-scale geospatial analysis problem with a focus on data analytics and professional practice in Geographic Information Systems. Penn State MGIS students collaborate with graduate students from ITC - University of Twente in Enschede, Netherlands to develop solutions to analyze spatio-temporal patterns in refugee migration data. Students have the opportunity to present their work and develop new connections with EU geospatial professionals via site visits to European national mapping agencies. Students work in teams to use geospatial analytics to arrive at a solution to visualize patterns over space and time.

This course provides an introduction to the technology and policy context of public communications networks, through critical discussion of current issues in communications policy and their historical roots. The course focuses on underlying rationales and models for government involvement and the complex dynamics introduced by co-evolving technologies, industry structure, and public policy objectives. Cases drawn from cellular, fixed-line, and Internet applications include evolution of spectrum policy and current proposals for reform; the migration to broadband and implications for universal service policies; and property rights associated with digital content. The course lays a foundation for thesis research in this domain.

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.

In EARTH 801, you will develop skills in a programming language designed for visual arts and visualization while exploring Earth science topics. Specifically, you'll learn and practice digital graphics capabilities in order to render Earth science concepts that are otherwise difficult to visualize due to complicated space and time scales. Here, you will interact with large, open, freely-available data sets by collecting, plotting, and analyzing them using a variety of computational methods. You'll be ready to teach secondary school students a range of Next Generation Science Standard skills involving data collecting, manipulation, analysis, and plotting. You'll also read and discuss current research regarding the teaching, learning, and evaluation of visualization skills, as well as multiple external representations of science concepts.

This course is aimed at beginning to intermediate computer users. It teaches a range of computer skills from the basics of using Windows, to basic internet literacy, to creating projects using Microsoft Office. Assignments show step-by-step visuals to help students complete projects, and include integration across Microsoft Word, Excel, PowerPoint, and Access.

This course was developed by Lumen Learning in conjunction with Cerritos College, with contributing work from Sherri Pendelton, Shelli Carter, and Robert Danielson, as well as videos from multiple sources.

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 explores a variety of topics in computing, such as the following: the components of a computer, common computer terminology, an introduction to the Internet, computer security and privacy, computer troubleshooting techniques, and steps to maintain the life of your computer.

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.

The course covers the basic models and solution techniques for problems of sequential decision making under uncertainty (stochastic control). We will consider optimal control of a dynamical system over both a finite and an infinite number of stages. This includes systems with finite or infinite state spaces, as well as perfectly or imperfectly observed systems. We will also discuss approximation methods for problems involving large state spaces. Applications of dynamic programming in a variety of fields will be covered in recitations.

Increasingly volatile climate and weather; vulnerable drinking water supplies; shrinking wildlife habitats; widespread deforestation due to energy and food production. These are examples of environmental challenges that are of critical importance in our world, both in far away places and close to home, and are particularly well suited to inquiry using geographic information systems. In GEOG 487 you will explore topics like these and learn about data and spatial analysis techniques commonly employed in environmental applications. After taking this course you will be equipped with relevant analytical approaches and tools that you can readily apply to your own environmental contexts.