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Machine Learning for Healthcare

July 16-17, 2018

With massive amounts of data flowing from EMRs, wearables and countless other new sources, the potential for machine learning and AI to transform healthcare is perhaps more drastic and profound than any other industry. But there are unique challenges that exist in healthcare that make it difficult to apply new technologies in the industry, including patient privacy issues, the lack of interoperability, and the diversity of digital health data. In this course, you'll gain practical knowledge that will enable you to overcome these hurdles and apply the latest advances in healthcare AI tools and techniques to:

  • Automate medical discoveries
  • Predict patient outcomes
  • Model disease progression
  • Identify & manage high-risk patients
  • Implement patient health initiatives
  • Prevent high-cost care
    • You'll also come away with a strong understanding of important ethical and moral issues associated with the use of machine learning in healthcare, and learn how to develop fair and accountable algorithms that ensure unbiased care.

Modeling and Optimization for Machine Learning

July 16-20, 2018

Numerical modeling is the skill of reducing a messy engineering or computational problem to a mathematical form that can be solved by using standard algorithms and techniques. By recognizing mathematical patterns ?in the wild,? participants will develop an intuition for which problems are solvable using standard numerical modeling techniques and gain the knowledge and skills to then solve them. Computer science is experiencing a fundamental shift in its approach to modeling and problem solving. Early computer scientists primarily studied discrete mathematics, focusing on structures like databases and arrays composed of distinct pieces. With the introduction of modern applications in ?big data,? three-dimensional scanning, machine learning, and noisy sensor communications, practitioners now must design robust methods for processing real-valued data. The latest generation of programmers, computer scientists, and engineers must be able to reason about not just bits-and-bytes, but also calculus, linear algebra, and optimization. By the end of the course, participants will learn how to boil real-world challenges down to their computational essence to make a reasonable estimate of how difficult it would be to design a numerical method to solve them. We will cover a breadth of possible tools, from numerical linear algebra to convex programming and stochastic/deterministic gradient descent, in the context of practical problems drawn from emerging applications in vision, learning, and graphics. Coding and mathematical exercises will reinforce these ideas and expose participants to standard software packages for optimization.

Additive Manufacturing: From 3D Printing to the Factory Floor

July 23, 2018 to July 27, 2018

This course will build a comprehensive understanding of additive manufacturing (AM) processes and their implications for product development and manufacturing operations. Lectures will analyze AM fundamentals, materials, and process capabilities. This content will then be related to applications spanning industries including aerospace, medical devices, electronics, architecture, and consumer products. Lab sessions will provide hands-on experience with desktop 3D printers. Participants will design, fabricate, and measure components, and will identify future opportunities via case studies.

Additive manufacturing (AM) processes were first demonstrated more than twenty five years ago; however, only recently has broad industrial and consumer interest ignited, with potential implications ranging from ubiquitous personal fabrication to disruption of traditional supply chains. The goal of this course is to present a comprehensive overview of AM, spanning from fundamentals to applications and technology trends. Participants will learn the fundamentals of AM of polymers, metals, composites, and biomaterials, and will realize how process capabilities (rate, cost, quality) are determined by the material characteristics, process parameters, and machine designs. Application areas including aerospace components, electronics, medical devices, and consumer products will be discussed via detailed examples and case studies. Particular emphasis will be placed on emerging metal- and powder-based AM technologies, and related design principles and process standards. Lab sessions will provide hands-on experience with a variety of state-of-the-art desktop 3D printers and scanners. Participants will design, fabricate, and measure test parts, and will perform experiments to explore process limits. The course will conclude with a perspective on needs for future advancement of AM and major opportunities spanning many related business and technical domains.

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.

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