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Machine Learning for Big Data and Text Processing

June 12-16, 2017

Machine learning methods drive much of modern data analysis across engineering, sciences, and commercial applications. For example, search engines, recommender systems, advertisers, and financial institutions employ machine learning algorithms for content recommendation, predicting customer behavior, compliance, or risk. Much of today's data is available in primarily textual form, requiring effective tools for using unstructured and semi-structured text. This course examines a suite of key machine learning tools and their applications, including predictive analysis. We will discuss key insights underlying the tools, what kinds of problems they can/cannot solve, how they can be applied effectively, and what issues are likely to arise in practical applications.

The course is designed to operate simultaneously on two levels, intuitive and more formal, describing key concepts, formulations, algorithms, and practical examples for professionals whose work interfaces data analysis in different ways and on different levels.

  • At the managerial level, the course provides the vision and understanding of the many opportunities, costs, and likely performance hurdles in predictive modeling, especially as they pertain to large amounts of textual (or similar) data.
  • For professionals whose work involves data hands-on, the course aims to provide a deeper understanding and sharper intuitions about what is possible, what is not, and which methods to consider in what contexts.
  • For everyone, the course provides the ability to see problems as machine learning problems and be able to discuss ways to approach them.

Learning Objectives

  1. Understand broad opportunities for automation with machine learning
  2. Be able to formulate/set up problems as machine learning tasks
  3. Outline key aspects of practical problems that are likely to impact performance
  4. Assess which types of methods are likely to be useful for a given class of problems
  5. Understand strengths and weakness of "on-line" learning algorithms
  6. Be able to discuss scaling issues (amount of data, dimensionality, storage, and computation)
  7. See through the process of applying machine learning methods in practice, foresee likely hurdles and possible remedies
  8. Understand modern natural language processing tools, formulations, and problems
  9. Grasp what predictive analytics often does not provide
  10. Understand current machine learning trends and opportunities that they bring

Discrete Choice Analysis: Predicting Demand and Market Shares

June 12-16, 2017

This one-week program undertakes an in-depth study of discrete choice models (logit, nested logit, generalized extreme value, probit, logit mixtures), data collection, specification, estimation, statistical testing, forecasting, and application. The covered topics include analysis of revealed and stated preferences data, sampling, and simulation-based estimation, discrete panel data, Bayesian estimation, discrete-continuous models, menu choice, and models with latent variables. The course includes practical application sessions where participants will be provided with discrete choice software to learn how to estimate and test discrete choice models taught in lecture using real databases, and gain hands on experience in using new discrete choice techniques for practical applications. By examining actual case studies of discrete choice methods, students will be familiarized with problems of model formulation, testing, and forecasting.

Discrete choice models are widely used for the analysis of individual choice behavior and can be applied to choice problems in many fields such as economics, environmental management, urban planning, etc. For example, discrete choice modeling is used in marketing research to guide product positioning, pricing, product concept testing, and many other areas of strategic and tactical interest. Recent applications to predict changes in demand and market shares include areas such as choice of travel mode, coffee brand, telephone service, soft drinks and other foods, and choice of durables such as automobiles, air conditioners, and houses.

Who Should Attend

This program is intended for academics and professionals interested in learning new discrete choice techniques and how to predict choice and forecast demand. They will gain hands-on experience in applying discrete choice software in real-world case studies. Participants need only have a basic working knowledge of statistical methods.

Formulation and Stabilization of Biotherapeutics

June 12-14, 2017

Biotherapeutics, particularly antibodies, are currently the fastest growing pharmaceuticals. Ideally, they are formulated in aqueous solutions, often a great challenge due to physical and chemical stability issues. This course addresses those challenges across a range of topics from aggregation to oxidation, deamidation, and hydrolysis. It covers these topics from the basic to the advanced level with an emphasis on modeling. In addition, cutting-edge technologies are described and analyzed. The course as a whole focuses on giving you additional tools and knowledge to help streamline solutions to formulation and stability issues for biologics.

Who Should Attend

This course is targeted for scientists and engineers in biopharmaceutical development. It would also be of interest to those in biomanufacturing, in which stability issues perpetually arise. The course will be of particular benefit to those who wish to enhance their skill in efficiently and effectively addressing stability issues and formulation. Those who should attend include:

  • Formulation scientists from beginning to advanced
  • Scientists and engineers who are interested in or need to understand stability issues
  • Bioprocessing scientists and engineers
  • Scientists and engineers interested in physical and chemical processes that occur with biomolecules
  • Managers responsible for pharmaceutical development, manufacturing, and regulatory affairs

Multiscale Materials Design

June 12-16, 2017

As the demand for high-performance materials with superior properties, flexibility, and resilience grows, a new design paradigm from the molecular scale upwards has revolutionized our ability to create novel materials. This course covers the science, technology, and state-of-the-art in atomistic, molecular, and multiscale modeling, synthesis and characterization. Through lectures and hands-on labs, participants will learn how superior material properties in nature and biology can be mimicked in bioinspired materials for applications in new technology. Bridging multiple hierarchies of length- and time-scales, this course trains participants in applications to polymers, metals and ceramics as well as composites. The course also covers sustainable infrastructure materials such as concrete and asphalt.

This course will focus on practical problem-solving computational tools paired with a detailed discussion of experimental techniques to probe the ultimate structure of materials, emphasizing tools to predict key mechanical properties. Case studies of molecular mechanics, bio-inspired composites, and dynamic fracture of composites and polymers will be presented and carried out by participants in computational labs. Simulation codes, algorithms, and details of the implementations of different simulation technologies, including validation, will be presented, including practical issues such as supercomputing (hardware and software), parallelization, graphics processing computing (GPU), and others. Specific focus is on structural polymers and composites, including innovative material platforms such as carbon nanotubes, graphene, and protein materials for bio-inspired materials. Participants will learn state-of-the-art techniques, such as molecular dynamics and coarse-graining, used to cover a range of length- and time-scales.

Who Should Attend
This course will be of interest to scientists, engineers, managers, and policy makers working in the area of materials design, development, manufacturing, and testing. The program is of particular interest to industries where highly functional materials tailored for specific purposes are needed. The focus on mechanical properties includes domains such as biomaterials and implants, adhesives, construction materials, and structural materials for the aero-astro and automotive industries.

Quantitative Cardiorespiratory Physiology and Clinical Applications for Engineers

June 12-16, 2017

This course presents the functional anatomy, physiology, and pathophysiology of the cardiovascular and respiratory systems from an engineering perspective. The goal of the course is to enable engineers and managers from industry to understand the normal cardiorespiratory physiology at the systems level, to predict system behavior under normal operation and pathological stresses, and to understand what commonly monitored clinical signals reveal about the state of the system. Strong emphasis will be placed on describing the cardiovascular system quantitatively, drawing on physical principles and deriving models of cardiovascular and respiratory function that illuminate the organ systems’ operation. The course is structured into these major blocks:

  • Functional anatomy of the cardiovascular systems
  • Function of the heart and peripheral circulation
  • Function of the intact cardiovascular system
  • Control of the cardiovascular system
  • Physical basis of electrocardiography
  • Clinical electrocardiography
  • Functional anatomy of the respiratory system
  • Respiratory mechanics
  • Respiratory gas exchange

The course will be lecture-based, with breakout sessions in small groups to work on hands-on problems that consolidate the concepts presented during lectures. Presentations by clinicians will give insights into how technology is used in current clinical practice.

Radical Innovation

June 12-14, 2017

Less than 10 years ago, traditional players such as Nokia, Ericsson, Samsung, and Motorola dominated the mobile phone industry. Three years ago, the hottest phones were by Apple. Today, Samsung is considered an innovative company, Google has acquired the mobile phone division of Motorola, and Microsoft has acquired the mobile phone division of Nokia. Three elements of modern technology are making new ideas appear at such an extraordinary pace: the sheer rate of technical progress, the abundance of tools that are placing advanced technologies within the reach of new entrants, and the extraordinary opportunities created by convergence. Not all innovation needs to progress at this rate; however, there are lessons to be learned from these events and every company should be prepared to leverage opportunities from within or to ward off threats from the outside. The objective of this class is to cover some of the salient features of innovation in the modern world and to lay out the philosophy, tools, procedures, and incentives that an organization can adopt to drive innovation.

The course will cover a range of topics in innovation, and will begin with an understanding of what makes a successful innovative product and business: people, opportunity, context, and technology. The course will examine case studies in what we call radical innovation and will identify steps that companies can take towards encouraging innovations from within, ranging from brainstorming sessions to invention awards. Participants will also examine successful incubator strategies and critical success factors and some of the IP issues around invention. Next, the course will explore the role of venture funds inside and outside companies, and discuss spinouts, spin-ins, licensing, and acquisitions. Finally, participants in the course will consider the role of communities, standards bodies, and open-source models in innovation. There will also be breakout sessions in which smaller groups will engage in innovation exercises.

Who Should Attend

The course is taught from a technology viewpoint and is targeted at technical leaders, executives in charge of product or company strategy, and product managers. Typical titles will include: CTO, Head of Strategy, CIO, Head of R&D, Product Manager, Director of Lab, Group Leader, and so on.

Real Estate Finance: Fundamentals

June 12-13, 2017

The Real Estate Finance: Fundamentals course is a ?finance boot camp? for real estate developers, investors, lenders, lawyers, and other real estate professionals who need to analyze the financial feasibility of real estate development ventures. Participants will gain a comprehensive understanding of how investment returns are calculated and how income producing assets are valued. Designed for those without a financial background, this course integrates finance theory and taxation principles with conventional real estate practice.

Earn a Professional Certificate in Real Estate Finance and Development

This course is part of the Real Estate Finance and Development certificate program, offered jointly by MIT Professional Education and the MIT Center for Real Estate. 

Learn more about how you can earn a Professional Certificate when you take this and other real estate courses.

Cambridge, MA

Strategy in a Global World

June 13-14, 2017

This program is based on a new view of the world and how business at all levels must work in the context of a globalized world. The globalized world is no longer simply a source of new markets or cost factor savings; it is a source of innovation. Companies must develop a global business strategy that encompasses all aspects of being an organization capable of developing and delivering a proposition that takes advantage of global integration to create value from and for the world.


Why did global integration turn into a strategic imperative for so many industries and companies over the last couple of decades? Why is global integration so challenging for otherwise established multinational companies?


This program addresses how the current world makes a big difference for internationalization and a global strategy, and why incumbent multinationals and emergent multinationals have fared so differently in the dire straits of the new, globalized world. Strategy in a Global World provides a systemic approach to global business strategy and the relentless quest for discovering "why and how," not just "what."


Many participants attend this program along with Understanding Global Markets.

Participants in this program will learn how to think strategically in a globalized world. They will understand the value of global integration, the implications for business enterprise and management, and the keys to global performance. Participants will also learn how to reach new markets and harness human resources from beyond their existing borders.


Participants will gain pragmatic insights on how to:


  • Begin to assess how to develop business beyond their borders
  • Choose among three distinct options for how to grow their businesses
  • Creatively choose how to grow partnerships, networks, and more
  • Recognize and harness the value of having a global scope

After completing the program, participants will be prepared to:


  • Scrutinize their company advantage or lack thereof in order to make the fundamental choice of growing globally as a "national"? (the default choice in the past), a "national plus," or a "metanational"
  • Design a global strategy that is both for and from an interdependent world, allowing their company to turn the world into the most important source of capabilities and innovation, not just of markets or lower factor costs
  • Discover the managerial nature of global integration and profit from less visible forms of local differentiation

Many participants may leave the program realizing that the optimum policy for their companies now will be one that was not there before: being a local company with a global strategy.

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