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Data and Models: Regression Analytics

July 10-14, 2017

This course aims to teach a suite of algorithms and concepts to a diverse set of participants interested in the general concept of fitting data to models. It starts with mostly simple linear algebra and computational methods, and introduces some more difficult mathematical concepts towards the end. This method also, by design, fits in with our approach of morning lectures and afternoon practice on personal computers. The combined teaching system provides opportunities for much hands-on learning and participants leave the course with practical knowledge of the basic algorithms.

The course is very broad and is primarily intended to cover the fundamentals of each technique we address. Consequently, the major gain is that we can cover many different approaches. Think of it this way: we cover the first chapter or two of a specialized "book" on a given method. We therefore get you through the many fundamentals, which then allow you to dig further through the book on your own. Another way of thinking of our approach is the analogy of a carpenter?s tools?the goal is for participants to understand the utility of each tool and not to become specialists in any one method. In that sense the course is introductory and general. The course taps into material from a very wide selection of literature in many disciplines involving computation, including but not limited to: statistics and applied mathematics, science, engineering, medicine and biomedicine, computer science, geosciences, system engineering, economics, insurance, finance, business, and aerospace engineering. More specific areas in which you might come across relevant books are: Regression, non-linear regression, linear and non-linear parameter estimation, inversion, system identification, econometrics, biometrics, etc. The diversity of the past participants and their fields has always provided many perspectives on our common interest in data and models. Please note that we do not specifically cover non-parametric statistics, principal component analysis, or Big Data.

Who Should Attend: Anyone who fits data to models. This course is truly broad-based and participants from vastly differing fields are envisioned and encouraged to attend. Some of these fields are engineering, business, natural sciences, geoscience, medicine, statistics, and economics. Familiarity with computing and statistics is desirable. A fair background in linear algebra is highly recommended. The course is a condensed version of a regular MIT class with the same title, taught by Professor Morgan. The course has also been given at NASA, the University of the West Indies in Barbados, Sakarya University in Turkey, Stanford University, University of Science and Technology of China,the Cyprus Institute, and Texas A&M University.

Innovation: Beyond the Buzzword

July 10-12, 2017

We live in an age of exponential change in which rapid innovation is disrupting and unseating incumbent products and industries, creating new technological frontiers, and challenging nearly everything we think we know about business. For instance, think Uber and the end of the medallion taxi industry. Think Airbnb in twice as many countries as Hilton in less than 5 percent of the time. Think Tesla. Think Oculus. But beyond using the "buzzword," can you really define innovation?

In this course, which is centered on the concept of Design Thinking, your answer to that question will come from actually involving yourself in the activity of innovating.

The course will include lectures from faculty and guests, discussions of case studies in innovation models and methods, and learning expeditions on and beyond the MIT campus. But it will also go beyond these traditional classroom activities to include hands-on experiences with some cutting-edge innovations as well as group work and a class hackathon to engage in genuine innovating ? and through that, to gain an understanding beyond the buzzword. Participants will emerge as more critical thinkers, knowledgeable about what innovation is (and is not), how it happens, how to discern meaningful trends in design and technology, and how to identify opportunities and propose innovative products, services, and experiences. Active class participation, a willingness to engage with others in a creative process, and a recognition that you might have a lot to learn about innovation are all prerequisites for the course.

Who Should Attend: To facilitate the cross-pollination of ideas, approaches, and critical thought, professionals from all industries are welcome. People from across the functional business spectrum will find the course valuable, including strategy leaders, directors of innovation and technology, product managers, engineers, marketers, and R&D personnel. All participants must come with a willingness and enthusiasm to engage and be ready to share their particular passions and expertise.

Mastering Innovation and Design-Thinking

July 10-12, 2017

Insanely successful companies, like Apple, Virgin, Toyota, and others, innovate continuously because of their culture of design-thinking. When done right, this thinking links inspiration and passion to execution and delivery—positively affecting every facet of the product and service.

For you to be successful at work, you need to know how to think like a designer when approaching an engineering task alone, but you especially need design-thinking skills when working within a team or leading a team. By applying a design-centered approach you’ll be able to conceive of radically innovative solutions, deeply understand who your real stakeholders are and what they care about, create vision that gets buy-in from senior management and colleagues, avoid hazards, and create solutions that people love both emotionally and intellectually.

Using a 10-step design process and a 3-step vision creation and communication process, you’ll experience the design process first hand in this interactive class that will expand your thinking and help you and your teams create more powerful solutions. You’ll learn how to create materials that align technical and non-technical audiences, understand the vital importance of the psychology behind how people interact with technology, how to manage creativity, and how to assess the effectiveness of your solutions.

WHO SHOULD ATTEND
This course is targeted for design engineers, research engineers, project engineers or managers, product engineers, members of the technical staff, applied scientists, and research scientists. The course would also be of interest to those who supervise early career professionals and those in academia (e.g. engineering and science graduate students, and post-docs).

Technology and Sustainability

July 10-12, 2017

The purpose of this class is to address the issue of sustainability from an engineering perspective. First we review the concept of sustainability from several points of view including economics, ecology, and engineering. This discussion includes the widely used “Triple Bottom Line” approach of industry. The current state of the “Science of Sustainability” will be reviewed. We then develop a resource accounting perspective in some detail with the emphasis in four areas:

1) energy resources analysis, energy flows, balances, efficiencies, primary energy use, energy return on investment, net energy analysis, renewable energy.

2) material resources analysis (including not only the materials used in the delivery of products and services, but also the effects on major material cycles such as carbon, water, and nitrogen). This approach will be expanded to aggregate both fuels and non-fuel materials by using an exergy analysis approach.

3) life cycle assessment of products and services (including variations on the method such as input-output models, hybrid models, and exergy models and a critique of the utility of LCA).

4) accounting for the role of ecosystem services in supporting industrial activities.

The class uses our new book Thermodynamics and the Destruction of Resources (Cambridge University Press, 2011) and builds these topics from a solid basis. Examples will be taken from diverse areas but with special attention to current and emerging chemical and manufacturing processes and product analysis. Participants are encouraged to bring sample cases for discussion, and class will include time for hands-on LCA for products and services of your choice.

Who Should Attend
This class is intended for engineers and managers from manufacturing, design, energy, and sustainability, as well as for academics (faculty, researchers, and graduate students).

Advances In Imaging: Emerging Devices and Visual Mining

July 17, 2017

The course provides an overview of computational imaging techniques, including novel imaging platforms to sample light in radically new ways and emerging topics in image analysis and exploitation. New cameras that can sample the high dynamic range (HDR), light field, or wide spectrum are emerging. In addition, ultra-fast optics for femto-photography and diffraction-beating technologies for microscopy are bringing unprecedented resolution in time and space. In this course, we will survey the landscape of imaging hardware, optics, sensors, and computational techniques. Participants will learn about and see hands-on demonstrations of high-end imaging devices. We will explore new emerging solutions that are opening up new research and commercial opportunities in immediate as well as future applications. Key topics include light fields, high dynamic range imaging, signal processing, applied optics, Fourier optics, ultrafast and multi-spectral imaging, compressive sensing, computer graphics and computer vision, and social photo collections.

WHO SHOULD ATTEND
The course is suitable for decision makers and planners for next generation of imaging solutions, engineers and designers of imaging systems, and anyone interested in review of existing and emerging solutions in optics, sensors, and image analysis. Application areas include consumer photography (including mobile phones), industrial machine vision, and scientific and medical imaging.

Build a Small Radar System

July 17-21, 2017

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.

Challenges of Leadership in Teams

July 17-21, 2017

The goal of this course is to prepare participants to handle the various challenges they will face in leading teams throughout their life cycle. The course supports self-reflection and skill development by creating changes in each participant's internal dialogue through interactive role-playing, self-assessment measures, group discussions, exercises, and interactive lectures. These activities will enhance each participant's development of their own unique leadership capabilities.

Leadership styles are uniquely individual and situational. Participants will learn to use their new capabilities in a team environment and to select the most effective management style for a specific situation. They will also learn the competency level required to improve task performance. As leaders, participants will learn to successfully support their teams by reducing uncertainty and to increase collaboration by providing structure and developing trust during the life cycle of a project.Individual leadership development plans will be prepared to enable participants to internalize improvements and become more effective without the stress of miscommunication and distrust. Once their development plan is enacted, each leader will be able to form teams that are quickly organized with individual team members who think collaboratively. Self-assessment, learning how to form a team, maintaining the team, reducing uncertainty, and becoming a good negotiator through using your emotional intelligence and leadership competencies are the focus of Challenges of Leadership in Teams.

Engineering Leadership for Emerging Leaders

July 17-21, 2017

Offered by the premier Gordon-MIT Engineering Leadership Program, this five-day course is designed to equip you with the skills and perspectives needed to lead yourself and others in today’s engineering and technology environments. You will improve your leadership skills by learning from the latest breakthroughs in the practice of leadership within a program that draws on a variety of teaching methods, especially hands-on learning. Like the practice of leadership itself, this program will be high-contact, high-energy, and consequential.

The transition to becoming an engineering leader is one of the most promising, yet challenging experiences that engineering professionals can face. The promise comes from becoming a new kind of professional; one who can mobilize sometimes-conflicting individuals around a shared vision, solve problems through “real” teamwork, and motivate people to deliver their best results. The challenge comes from learning to work in an entirely new way; from relying solely on oneself to deliver individual results to leading others to deliver collective results. Herein lies the nature of the delicate relationship between leadership and followership.
During our five-day program, you will:

  • Enhance your understanding of the nature of leadership and followership
  • Build a foundation of team-building skills
  • Develop and deliver an inspiring and shared vision
  • Discover new ways to lead and motivate others in technical environments
  • Gain support for your ideas in environments characterized by conflicting stakeholder needs
  • Learn to manage conflicts through negotiations and constructive dialogues

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