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Courseware
This is an interdisciplinary, project-based course, centered around a design project in which small teams of students work closely with a person with a disability in the Cambridge area to design a device, piece of equipment, app, or other solution that helps them live more independently.
- Subjects:
- Biomedical Engineering, Mechanical Engineering, Rehabilitation Sciences, Computing, and Electrical Engineering
- Keywords:
- Self-help devices for people with disabilities
- Resource Type:
- Courseware
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Courseware
This course explores cutting-edge neurotechnology that is essential for advances in all aspects of neuroscience, including improvements in existing methods as well as the development, testing and discussion of completely new paradigms. Readings and in-class sessions cover the fields of electrophysiology, light microscopy, cellular engineering, optogenetics, electron microscopy, MRI / fMRI, and MEG / EEG.
- Subjects:
- Biomedical Engineering and Biology
- Keywords:
- Neurotechnology (Bioengineering)
- Resource Type:
- Courseware
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Courseware
This course presents the fundamentals of digital signal processing with particular emphasis on problems in biomedical research and clinical medicine. It covers principles and algorithms for processing both deterministic and random signals. Topics include data acquisition, imaging, filtering, coding, feature extraction, and modeling. The focus of the course is a series of labs that provide practical experience in processing physiological data, with examples from cardiology, speech processing, and medical imaging. The labs are done in MATLAB® during weekly lab sessions that take place in an electronic classroom. Lectures cover signal processing topics relevant to the lab exercises, as well as background on the biological signals processed in the labs.
- Subjects:
- Biomedical Engineering and Medical Imaging
- Keywords:
- Biomedical engineering Signal processing Image processing
- Resource Type:
- Courseware
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Courseware
This course develops and applies scaling laws and the methods of continuum and statistical mechanics to biomechanical phenomena over a range of length scales, from molecular to cellular to tissue or organ level.
- Subjects:
- Biomedical Engineering and Biology
- Keywords:
- Biomedical engineering Biomechanics
- Resource Type:
- Courseware
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Others
Geospatial artificial intelligence sometimes referred to as geoAI is recently receiving so much attention. From large-scale projects to smaller projects. GeoAI can be referred to as using artificial intelligence with Geographical information system to analyse and produce solution-based predictions.
- Subjects:
- Computing and Land Surveying and Geo-Informatics
- Keywords:
- Geospatial data Geographic information systems Artificial intelligence
- Resource Type:
- Others
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Others
Software developments is advancing the technological world today. This changes have far more reaching implications in I.T industries such as Big data, Artificial intelligence and Agile Software development methodologies. Competition in the software development ecosystem has made developers to build software that are quick and reliable and often referred to as Agile development. Agile transformation is real and requires rethinking the business management, recruitment process and data strategy in a bid to stimulate disruptive solutions from within in-house development and deployment. AI product development would require rapid transformational changes within any organization. This can be accomplished by establishing specific operating models that permit development teams with the freedom of technology choice. This publication highlights some operating models that can be adopted to improve the success of AI products using Agile software development methodologies.
- Subjects:
- Computing
- Keywords:
- Agile software development
- Resource Type:
- Others
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Courseware
This course provides a broad introduction to machine learning and statistical pattern recognition. Topics include: supervised learning (generative/discriminative learning, parametric/non-parametric learning, neural networks, support vector machines); unsupervised learning (clustering, dimensionality reduction, kernel methods); learning theory (bias/variance tradeoffs; VC theory; large margins); reinforcement learning and adaptive control. The course will also discuss recent applications of machine learning, such as to robotic control, data mining, autonomous navigation, bioinformatics, speech recognition, and text and web data processing.
- Subjects:
- Computing
- Keywords:
- Pattern perception -- Statistical methods Machine learning
- Resource Type:
- Courseware
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Courseware
The purpose of this course is to introduce you to basics of modeling, design, planning, and control of robot systems. In essence, the material treated in this course is a brief survey of relevant results from geometry, kinematics, statics, dynamics, and control. The course is presented in a standard format of lectures, readings and problem sets.
- Subjects:
- Mechanical Engineering
- Keywords:
- Robotics
- Resource Type:
- Courseware
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Courseware
This course examines human-computer interaction in the context of graphical user interfaces. The course covers human capabilities, design principles, prototyping techniques, evaluation techniques, and the implementation of graphical user interfaces. Deliverables include short programming assignments and a semester-long group project. Students taking the graduate version also have readings from current literature and additional assignments.
- Subjects:
- Computing
- Keywords:
- Human-computer interaction User interfaces (Computer systems)
- Resource Type:
- Courseware
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Courseware
This is an intermediate algorithms course with an emphasis on teaching techniques for the design and analysis of efficient algorithms, emphasizing methods of application. Topics include divide-and-conquer, randomization, dynamic programming, greedy algorithms, incremental improvement, complexity, and cryptography.
- Subjects:
- Computing
- Keywords:
- Algorithms
- Resource Type:
- Courseware