MIT 1.00/1.001: Engineering Computation and Data Science

Presents fundamentals of computing and programming in an engineering context with an emphasis on data science. Introduces basics of web computing, data structures, and techniques for data analysis. Includes filtering, linear regression, simple machine learning (clustering and classifiers), and visualization. Surveys techniques for ingesting, processing, analyzing, and visualizing engineering data from a range of fields, including geo-spatial, environment, infrastructure, city dynamics, and numerical experiments. Students use JavaScript and HTML5 programming language to complete weekly assignments. Students taking graduate version complete additional assignments.

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MIT 1.125: Applied Blockchain - Architecture & Engineering Software Systems

Software architecting and design of software-intensive systems. Targeted at future CTOs who must understand both the business and technical issues involved in architecting global-scale systems. Introduces blockchain systems, consensus, scalability, governance, and the Ethereum platform. Presents modern tools and libraries for distributed computing, basic cryptography, including hashing, PKI, encryption and distributed apps. Use of cloud service APIs, containers, testing and synchronization techniques. Data cleaning and filtering, linear regression, basic machine learning algorithms such as clustering, classifiers, decision trees. Students learn problem solving in an active learning lab setting, completing in-class exercises and weekly assignments leading to a group project in blockchain. By the end of the class, students will be able to build practical blockchain applications and understand the limitations and opportunities of the technology.

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MIT Professional Education: Digital Transformation

This online program takes you through the fundamentals of digital technologies transforming our world today. Led by MIT faculty at the forefront of data science, participants will learn the history and application of transformative technologies such as blockchain, artificial intelligence, cloud computing, IoT, and cybersecurity as well as the implications of employing—or ignoring—digitalization.

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