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Build a Small Radar System

July 23-27, 2018

Are you interested in learning about radar by building and testing your own imaging radar system?

MIT Professional Education is offering a course in the design, fabrication, and testing of a laptop-based radar sensor capable of measuring Doppler and range and forming synthetic aperture radar (SAR) imagery. Lectures will be presented on the topics of applied electromagnetics, antennas, RF design, analog circuits, and digital signal processing while simultaneously building your own radar system and performing field experiments. Each student will receive a radar kit designed by MIT Lincoln Laboratory staff and a course pack.

This course will appeal to those who want to learn how to develop radar systems or SAR imaging, use radar technology, or make components or sub-systems.

During the course you will bring your radar kit into the field and perform experiments such as measuring the speed of passing cars or plotting the range of moving targets. A SAR imaging competition will test your ability to form a SAR image of a target scene of your choice from around campus.

Who Should Attend

This course is targeted for engineers and scientists who plan to design radars; use radar systems in a product or as the final product; work on radar systems, components, or subsystems; or are interested in using radar systems for observation of physical phenomena. Students will learn how radar systems work by attending lectures, building their own radar set, and acquiring radar data in the field. Those who should attend include:

  • Developers of radar systems or components
  • Users of radar technology
  • Purchasers of radar technology such as automotive and government organizations
  • Commercial enterprises seeking to use or add radar technology to their product, or develop a radar-based product
  • Defense industry or government personnel who want to learn how radar and SAR imaging works
  • Defense industry or government supervisors seeking to quickly educate employees
  • Unmanned vehicle or robot developers seeking to use radar sensor packages
  • Scientists who are interested in using radar technology for the observation of nature

You do not have to be a radar engineer but it helps if you have at least a bachelor?s degree in electrical engineering or physics and are interested in any of the following: electronics, electromagnetics, signal processing, physics, or amateur radio. It is recommended that you have some familiarity with MATLAB. Each student is required to bring a laptop (with a stereo-audio input) with MATLAB, because this will be used for data acquisition and signal processing.

Crisis Management and Business Continuity

July 24-28, 2017

Preparing for a crisis is not a luxury; it is a necessity. You know the odds are high that your company will suffer a disaster or crisis at some point. You cannot say you weren't ready; today's extreme public and government scrutiny demand that you should have been prepared.

MIT's "Crisis Management & Business Continuity" will help prepare you for the inevitable.

This comprehensive course provides up-to-date assessments and knowledge on issues that affect you - terrorism, pandemic, cyber security, communications, news media - from the experts involved with these efforts. You will have the opportunity to interact with these lecturers and with peers from industry and government.

By the end of the course, you will have the tools, knowledge, and understanding to benchmark, assess, and improve your business continuity, disaster recovery, and crisis management program. This includes the Course Manual (print and/or e-files), templates, and current articles. You will gain valuable contacts, have plenty of networking opportunities, and acquire insights for immediate implementation.

WHO SHOULD ATTEND
This course is for the Business Continuity, Disaster Recovery, Emergency Management, and Crisis Management practitioner or responder as well as for the executive who oversees these disciplines. Other staff who would benefit from this course include corporate executives, directors, and staff from IT/MIS, Environment Health & Safety, Risk Management, Public Relations, Human Resources, and Security. This course is also suited for federal, state, and local government officials and Emergency Managers.

Both novices and experienced personnel will benefit greatly from this course. If you cannot go, tell your director/executive so he/she can attend to better understand your complex profession.

Crisis Management and Business Continuity

July 23-27, 2018

Preparing for a crisis is not a luxury; it is a necessity. You know the odds are high that your company will suffer a disaster or crisis at some point. You cannot say you weren't ready; today's extreme public and government scrutiny demand that you should have been prepared.

MIT's "Crisis Management & Business Continuity" will help prepare you for the inevitable.

This comprehensive course provides up-to-date assessments and knowledge on issues that affect you - terrorism, pandemic, cyber security, communications, news media - from the experts involved with these efforts. You will have the opportunity to interact with these lecturers and with peers from industry and government.

By the end of the course, you will have the tools, knowledge, and understanding to benchmark, assess, and improve your business continuity, disaster recovery, and crisis management program. This includes the Course Manual (print and/or e-files), templates, and current articles. You will gain valuable contacts, have plenty of networking opportunities, and acquire insights for immediate implementation.

WHO SHOULD ATTEND
This course is for the Business Continuity, Disaster Recovery, Emergency Management, and Crisis Management practitioner or responder as well as for the executive who oversees these disciplines. Other staff who would benefit from this course include corporate executives, directors, and staff from IT/MIS, Environment Health & Safety, Risk Management, Public Relations, Human Resources, and Security. This course is also suited for federal, state, and local government officials and Emergency Managers.

Both novices and experienced personnel will benefit greatly from this course. If you cannot go, tell your director/executive so he/she can attend to better understand your complex profession.

Fermentation Technology

July 23-27, 2018

Fermentation Technology is the longest-run course in the MIT Professional Education catalog, having been offered continuously for more than 40 years. This course emphasizes the application of biological and engineering principles to problems involving microbial, mammalian, and biological/biochemical systems. The aims of the course are to review fundamentals and provide an up-to-date account of current knowledge in biological and biochemical technology. The lectures will emphasize and place perspectives on biological systems with industrial practices.

This course has made some major additions, modifications, and revisions in the course topics and course contents over the past couple of years. In recognition of the increasing number of attendees from non-pharmaceutical industries, we are rebalancing the course to provide equal emphasis on mammalian and microbial technologies. More than half of the lecturers are currently working in industry or have industrial experience.

The course is intended for engineers, biologists, chemists, microbiologists, and biochemists who are interested in the areas of biological systems in prokaryotic and eukaryotic hosts. It is desirable that individuals enrolled be familiar with some of the general aspects of modern biology, genetics, biochemical engineering, and biochemistry. Some general knowledge of mathematics is also desirable for dealing with the engineering aspects of the course.

Modeling and Simulation of Transportation Networks

July 23-27, 2018

Modeling and simulation methods are essential elements in the design and operation of transportation systems. Congestion problems in cities worldwide have prompted at all levels of government and industry a proliferation of interest in Intelligent Transportation Systems (ITS) that include advanced supply and demand management techniques. Such techniques include real-time traffic control measures and real-time traveler information and guidance systems whose purpose is to assist travelers in making departure time, mode and route choice decisions. Transportation researchers have developed models and simulators for use in the planning, design and operations of such systems. This course draws heavily on the results of recent research and is sponsored by the Intelligent Transportation Systems Laboratory of the Massachusetts Institute of Technology.

The course studies theories and applications of transportation network demand and supply models and simulation techniques. It provides an in-depth study of the world's most sophisticated traffic simulation models, demand modeling methods, and related analytical techniques, including discrete choice models and their application to travel choices and driving behavior; origin-destination estimation; prediction of traffic congestion; traffic flow models and simulation methods (microscopic, mesoscopic and macroscopic); and alternative dynamic traffic assignment methods.

WHO SHOULD ATTEND
This program is intended for analysts, engineers, managers and planners, as well as industry, government and academic researchers who seek to understand, analyze and predict performance of transportation systems. Participants with backgrounds in diverse areas such as traffic engineering, systems engineering, transportation planning, operations management, operations research and control systems are welcome.

Understanding and Predicting Technological Innovation: New Data and Theory

July 23-27, 2018

This course on technological innovation will be organized around three modules on (1) Data, (2) Theory, and (3) Application. In the first module, we will analyze new, large data sets on technological improvement, many of which were collected by the instructor and are the most expansive of their kind. We will cover statistical analysis methods and decomposition models in order to extract useful insight on the determinants of technological innovation. Examples from energy conversion, transportation, chemicals, metals, information technology, and a range of other industries will be discussed. In the second module, we will cover theories, that have been developed in recent years and stretching back several decades, to explain technological innovation. We will cover the disciplinary origins of these theories, the empirical evidence for or against them, and the usefulness of these theories for practitioners from various fields including engineering, chemicals, private investment, and public policy. Building on this insight, in the third module we will focus on applying the data analysis methods and theories covered to inform decisions about technology investment and design. The third module will address questions of specific interest to the class. This module will demonstrate the utility of the material covered and how it can be extended to answer a wide range of important questions relating to investment, research and development, manufacturing, and public policy.

Designing Efficient Deep Learning Systems

July 23-24, 2018

Deep learning is widely used for many artificial intelligence (AI) applications including computer vision, speech recognition, robotics, etc. While deep learning delivers state-of-the-art accuracy on many AI tasks, it comes at the cost of high computational complexity. Accordingly, designing efficient hardware systems to support deep learning is an important step towards enabling its wide deployment, particularly for embedded applications such as mobile, Internet of Things (IOT), and drones.

Who Should Attend
This course is designed for research scientists, engineers, developers, project managers, startups and investors/venture capitalists who work with or develop artificial intelligence for hardware and systems, as well as mobile or embedded applications:

* For project managers and investors/venture capitalists whose work involves assessing the viability or potential impact of a deep learning system and selecting a research direction or acquisition, this course aims to provide an overview of the recent trends as well as methods to assess the technical benefits and drawbacks of each approach or solution based on a comprehensive set of metrics.
* For research scientists and engineers whose work involves designing and building deep learning systems, this course aims to provide an overview of the various state-of-the-art techniques that are being used to address the challenges of building efficient deep learning systems.
* For startups and developers whose work involves developing deep learning algorithms and solutions for embedded applications and systems, this course aims to provide the insights necessary to select the best platform for your goals and needs. It will also highlight techniques that can be applied at the algorithm level to improve the energy-efficiency and speed of your proposed solution.

Climate Change: From Science to Solutions

July 30 - August 3, 2018

The objective of this course is to provide participants with a thorough understanding of the scientific foundation behind anthropogenic climate change, its impacts on the Earth, and strategies to address it. The course introduces the fundamental physical processes that shape climate, focusing on the drivers of past, present, and future climate change. Impacts of climate change on the environment and human societies will be highlighted, including effects on temperature, precipitation, ocean acidity, sea level, severe storms, agriculture, biodiversity, and air quality. Mitigation approaches and adaptation strategies, including technology development, will be introduced, discussed, and critiqued. The course will conclude with an overview of policy and governance considerations in a changing climate. Non-lecture activities will comprise 25% of the course, and will address the contemporary science of climate measurements, models of climate change and impacts, and climate change policy and negotiations.

Who Should Attend:
This course is targeted to environmental scientists, engineers, and consultants who seek a deeper understanding of the science of climate change. Professionals in the energy, finance, insurance/risk mitigation, and food/beverage sectors as well as those working in government, NGOs, and education will also have an interest in this topic.

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