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Science & Math5667 Engineering4225 Mathematics2318 Social Sciences2143 Data Science, Analytics & Computer Technology2067 Physics1776 Computer Science1714 Humanities1550 Business & Management1464 Systems Engineering919 Literature861 Art, Design & Architecture798 Electrical Engineering796 Biology785 Chemistry696 Economics683 Energy, Climate & Sustainability658 Communication603 Health & Medicine587 AI563 Education & Teaching541 Algorithms and Data Structures493 Mechanical Engineering458 Materials Science and Engineering455 Software Design and Engineering449 Machine Learning427 Management420 Chemical Engineering366 Energy365 Policy and Administration347 Cognitive Science345 Operations335 Pedagogy and Curriculum331 Digital Learning328 Digital Business & IT326 History307 Media Studies306 Sociology304 Biomedical Technologies295 Organizations & Leadership279 Earth Science278 Urban Studies273 Visual Arts252 Programming & Coding250 Climate Science232 Biological Engineering207 Public Health205 Philosophy196 Systems Thinking186 Political Science185 Innovation & Entrepreneurship184 Educational Technology180 Psychology180 Adaptation and Resilience171 Anthropology171 Aerospace Engineering162 Finance & Accounting159 Language159 Architecture153 Game Design149 Climate and Energy Policy143 Visualization143 Networks and Security142 Strategy & Innovation142 Data Science138 Environmental Engineering129 Pathology and Pathophysiology124 Music121 Entrepreneurship118 Linguistics108 International Development104 Supply Chain96 Civil Engineering90 Nuclear Engineering87 Startups/New Enterprises86 Imaging71 Mental Health69 Faculty Leadership67 Ocean Engineering65 Gender Studies60 User Experience58 Environmental Design51 Immunology42 Built Environment41 Health Care Management35 Manufacturing35 Performing Arts34 Product Innovation34 Geography30 Marketing28 Sustainable Business28 Education Policy26 Innovation Process26 Law24 Real Estate24 Corporate Innovation22 Ecosystems22 Business Analytics21 Art History17 AR/VR/MR/XR12 Religion11 CyberSecurity6 Blockchain4 Natural Systems4 Negotiation & Communication4 Inventions & Patents3 Environmental and Climate Justice1 Innovation Ecosystems1

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MIT: Professional Certificate in Cybersecurity

Professional Certificate in Cybersecurity

Advance Your Career as a Cybersecurity EngineerCyberattacks are becoming more frequent, complex, and targeted, collectively costing organizations billions of dollars every year. This is why cybersecurity is one of the fastest growing industries in the U.S. as every year more companies and government agencies are seeking to hire cybersecurity engineers with the specialized technical skills needed to defend mission-critical computer systems, networks, cloud applications, and more against cyberattacks.Developed in collaboration with Emeritus.

Fra 7750 USDDiplom

MIT: Blockchain and Money

Blockchain and Money

This course is for students wishing to explore blockchain technology’s potential use—by entrepreneurs and incumbents—to change the world of money and finance. The course begins with a review of Bitcoin and an understanding of the commercial, technical, and public policy fundamentals of blockchain technology, distributed ledgers, and smart contracts. The class then continues on to current and potential blockchain applications in the financial sector.

MIT: High Speed Communication Circuits

High Speed Communication Circuits

6.776 covers circuit level design issues of high speed communication systems, with primary focus being placed on wireless and broadband data link applications. Specific circuit topics include transmission lines, high speed and low noise amplifiers, VCO’s, mixers, power amps, high speed digital circuits, and frequency synthesizers. In addition to learning analysis skills for the above items, students will gain a significant amount of experience in simulating RF circuits in SPICE and also building RF circuits within a lab project.

MIT: Networks

Networks

This course will highlight common principles that permeate the functioning of networks and how the same issues related to robustness, fragility and interlinkages arise in several different types of networks. It will both introduce conceptual tools from dynamical systems, random graph models, optimization and game theory, and cover a wide variety of applications.

MIT: Computer Networks

Computer Networks

How does the global network infrastructure work and what are the design principles on which it is based? In what ways are these design principles compromised in practice? How do we make it work better in today’s world? How do we ensure that it will work well in the future in the face of rapidly growing scale and heterogeneity? And how should Internet applications be written, so they can obtain the best possible performance both for themselves and for others using the infrastructure? These are some issues that are grappled with in this course. The course will focus on the design, implementation, analysis, and evaluation of large-scale networked systems. Topics include internetworking philosophies, unicast and multicast routing, congestion control, network quality of service, mobile networking, router architectures, network-aware applications, content dissemination systems, network security, and performance issues. Material for the course will be drawn from research papers, industry white papers, and Internet RFCs.

MIT: Communication System Design

Communication System Design

This course presents a top-down approach to communications system design. The course will cover communication theory, algorithms and implementation architectures for essential blocks in modern physical-layer communication systems (coders and decoders, filters, multi-tone modulation, synchronization sub-systems). The course is hands-on, with a project component serving as a vehicle for study of different communication techniques, architectures and implementations. This year, the project is focused on WLAN transceivers. At the end of the course, students will have gone through the complete WLAN System-On-a-Chip design process, from communication theory, through algorithm and architecture all the way to the synthesized standard-cell RTL chip representation.

MIT: High Speed Communication Circuits and Systems

High Speed Communication Circuits and Systems

6.976 covers circuit and system level design issues of high speed communication systems, with primary focus being placed on wireless and broadband data link applications. Specific circuit topics include transmission lines, high speed and low noise amplifiers, VCO’s, and high speed digital circuits. Specific system topics include frequency synthesizers, clock and data recovery circuits, and GMSK transceivers. In addition to learning analysis skills for the above items, students will gain a significant amount of experience in simulating circuits in SPICE and systems in CppSim (a custom C++ simulator).

MIT: Topics in Theoretical Computer Science : Internet Research Problems

Topics in Theoretical Computer Science : Internet Research Problems

We will discuss numerous research problems that are related to the internet. Sample topics include: routing algorithms such as BGP, communication protocols such as TCP, algorithms for intelligently selecting a resource in the face of uncertainty, bandwidth sensing tools, load balancing algorithms, streaming protocols, determining the structure of the internet, cost optimization, DNS-related problems, visualization, and large-scale data processing. The seminar is intended for students who are ready to work on challenging research problems. Each lecture will discuss: methods used today issues and problems formulation of concrete problems potential new lines of research A modest amount of background information will be provided so that the importance and context of the problems can be understood. No previous study of the internet is required, but experience with algorithms and/or theoretical computer science at the graduate/research level is needed.

MIT: Data Communication Networks

Data Communication Networks

6.263J / 16.37J focuses on the fundamentals of data communication networks. One goal is to give some insight into the rationale of why networks are structured the way they are today and to understand the issues facing the designers of next-generation data networks. Much of the course focuses on network algorithms and their performance. Students are expected to have a strong mathematical background and an understanding of probability theory. Topics discussed include: layered network architecture, Link Layer protocols, high-speed packet switching, queueing theory, Local Area Networks, and Wide Area Networking issues, including routing and flow control.

MIT: Communication Systems Engineering

Communication Systems Engineering

This course will cover fundamentals of digital communications and networking. We will study the basics of information theory, sampling and quantization, coding, modulation, signal detection and system performance in the presence of noise. The study of data networking will include multiple access, reliable packet transmission, routing and protocols of the internet. The concepts taught in class will be discussed in the context of aerospace communication systems: aircraft communications, satellite communications, and deep space communications.

MIT: Introduction to Computational Thinking with Julia, with Applications to Modeling the COVID-19 Pandemic

Introduction to Computational Thinking with Julia, with Applications to Modeling the COVID-19 Pandemic

This half-semester course introduces computational thinking through applications of data science, artificial intelligence, and mathematical models using the Julia programming language. This Spring 2020 version is a fast-tracked curriculum adaptation to focus on applications to COVID-19 responses. See the MIT News article Computational Thinking Class Enables Students to Engage in Covid-19 Response

MIT: Introduction to EECS II: Digital Communication Systems

Introduction to EECS II: Digital Communication Systems

An introduction to several fundamental ideas in electrical engineering and computer science, using digital communication systems as the vehicle. The three parts of the course—bits, signals, and packets—cover three corresponding layers of abstraction that form the basis of communication systems like the Internet. The course teaches ideas that are useful in other parts of EECS: abstraction, probabilistic analysis, superposition, time and frequency-domain representations, system design principles and trade-offs, and centralized and distributed algorithms. The course emphasizes connections between theoretical concepts and practice using programming tasks and some experiments with real-world communication channels.

MIT: Quantum Information Science II

Quantum Information Science II

This three-module sequence of courses covers advanced topics in quantum computation and quantum information, including quantum error correction code techniques; efficient quantum computation principles, including fault-tolerance; and quantum complexity theory and quantum information theory. Prior knowledge of quantum circuits and elementary quantum algorithms is assumed. These courses are the second part in a sequence of two quantum information science subjects at MIT. The three modules comprise: 8.371.1x: Quantum states, noise and error correction 8.371.2x: Efficient quantum computing—fault tolerance and algorithms 8.371.3x: Quantum complexity theory and information theory This course was organized as a three-part series on MITx by MIT’s Department of Physics and is now archived on the Open Learning Library, which is free to use. You have the option to sign up and enroll in each module if you want to track your progress, or you can view and use all the materials without enrolling.

MIT: Software Construction

Software Construction

6.005 Software Construction introduces fundamental principles and techniques of software development, i.e., how to write software that is safe from bugs, easy to understand, and ready for change. The course includes problem sets and a final project. Important topics include specifications and invariants; testing; abstract data types; design patterns for object-oriented programming; concurrent programming and concurrency; and functional programming. The 6.005 website homepage from Spring 2016, along with all course materials, is available to OpenCourseWare users.

MIT: Gödel, Escher, Bach

Gödel, Escher, Bach

How are math, art, music, and language intertwined? How does intelligent behavior arise from its component parts? Can computers think? Can brains compute? Douglas Hofstadter probes very cleverly at these questions and more in his Pulitzer Prize winning book, “Gödel, Escher, Bach”. In this seminar, we will read and discuss the book in depth, taking the time to solve its puzzles, appreciate the Bach pieces that inspired its dialogues, and discover its hidden tricks along the way.

MIT: Advanced Topics in Cryptography

Advanced Topics in Cryptography

The topics covered in this course include interactive proofs, zero-knowledge proofs, zero-knowledge proofs of knowledge, non-interactive zero-knowledge proofs, secure protocols, two-party secure computation, multiparty secure computation, and chosen-ciphertext security.

MIT: Information Technology I

Information Technology I

Information Technology I helps students understand technical concepts underlying current and future developments in information technology. There will be a special emphasis on networks and distributed computing. Students will also gain some hands-on exposure to powerful, high-level tools for making computers do amazing things, without the need for conventional programming languages. Since 15.564 is an introductory course, no knowledge of how computers work or are programmed is assumed.

MIT: Quantum Information Science I

Quantum Information Science I

This course is a three-course series that provides an introduction to the theory and practice of quantum computation. The three-course series comprises: 8.370.1x: Foundations of Quantum and Classical computing—quantum mechanics, reversible computation, and quantum measurement 8.370.2x: Simple Quantum Protocols and Algorithms—teleportation and superdense coding, the Deutsch-Jozsa and Simon’s algorithm, Grover’s quantum search algorithm, and Shor’s quantum factoring algorithm 8.370.3x: Foundations of Quantum communication—noise and quantum channels, and quantum key distribution Prior knowledge of quantum mechanics is helpful but not required. It is best if you know some linear algebra. This course was organized as a three-part series on MITx by MIT’s Department of Physics and is now archived on the Open Learning Library, which is free to use. You have the option to sign up and enroll in each module if you want to track your progress, or you can view and use all the materials without enrolling.

MIT: Introduction to Computational Thinking

Introduction to Computational Thinking

This class uses revolutionary programmable interactivity to combine material from three fields – Computer Science + Mathematics + Applications – creating an engaging, efficient learning solution to prepare students to be sophisticated and intuitive thinkers, programmers, and solution providers for the modern interconnected online world. Upon completion, students are well trained to be scientific “trilinguals,” seeing and experimenting with mathematics interactively as math is meant to be seen, and ready to participate and contribute to open source development of large projects and ecosystems.

MIT: Design and Analysis of Algorithms

Design and Analysis of Algorithms

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.

MIT: Selected Topics in Cryptography

Selected Topics in Cryptography

This course covers a number of advanced “selected topics” in the field of cryptography. The first part of the course tackles the foundational question of how to define security of cryptographic protocols in a way that is appropriate for modern computer networks, and how to construct protocols that satisfy these security definitions. For this purpose, the framework of “universally composable security” is studied and used. The second part of the course concentrates on the many challenges involved in building secure electronic voting systems, from both theoretical and practical points of view. In the third part, an introduction to cryptographic constructions based on bilinear pairings is given.

MIT: Distributed Computer Systems Engineering

Distributed Computer Systems Engineering

This course covers abstractions and implementation techniques for the design of distributed systems. Topics include: server design, network programming, naming, storage systems, security, and fault tolerance. The assigned readings for the course are from current literature. This course is worth 6 Engineering Design Points.

MIT: Introduction to Computational Thinking

Introduction to Computational Thinking

This is an introductory course on computational thinking. We use the Julia programming language to approach real-world problems in varied areas, applying data analysis and computational and mathematical modeling. In this class you will learn computer science, software, algorithms, applications, and mathematics as an integrated whole. Topics include image analysis, particle dynamics and ray tracing, epidemic propagation, and climate modeling.

MIT: Network Optimization

Network Optimization

15.082J/6.855J/ESD.78J is a graduate subject in the theory and practice of network flows and its extensions. Network flow problems form a subclass of linear programming problems with applications to transportation, logistics, manufacturing, computer science, project management, and finance, as well as a number of other domains. This subject will survey some of the applications of network flows and focus on key special cases of network flow problems including the following: the shortest path problem, the maximum flow problem, the minimum cost flow problem, and the multi-commodity flow problem. We will also consider other extensions of network flow problems.

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4225

Mathematics2318

Social Sciences2143

Data Science, Analytics & Computer Technology2067

Computer Science1714

Business & Management1464

Systems Engineering919

Art, Design & Architecture798

Electrical Engineering796

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