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Fundamentals of Neuroscience, Part 1: The Electrical Properties of the Neuron
Organic Chemistry 1
Mountains 101
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Massachusetts Institute of Technology (MIT) is a world-renowned research university renowned for its interdisciplinary curriculum, innovative research and groundbreaking discoveries.
Master fundamental principles of modern finance, covering valuation models, risk analysis, derivative instruments, and investment management strategies.
Experience the world at the molecular-level! Learn about spontaneity, equilibrium, and mechanisms and rates of reactions. Applications include the energy problem, acid/base chemistry, electrochemistry and batteries, climate science, catalysis, and more.
The goal of this course is to illustrate the spectroscopy of small molecules in the gas phase
This course examines the history of MIT through the lens of the broader history of science and technology, and vice versa.
Learn computational thinking and Python programming to solve real-world problems. Covers algorithms, data structures, and analytical techniques for beginners and aspiring computer scientists.
Financial derivatives are ubiquitous in global capital markets. Students will obtain a sophisticated understanding of valuation methods; tools for quantifying, hedging, and speculating on risk; and a basic familiarity with major markets and instruments.
Learn how to evaluate technologies within a global development context from the perspective of suitability, scalability and sustainability.
Learn and Play: An interactive course focusing on the rhythms of Bali
Explore the human brain's perceptual and cognitive abilities, their neural implementation, and cutting-edge research methods in cognitive neuroscience through lectures and discussions.
Explore the intersection of psychology and economics, covering topics like time and risk preferences, social behavior, attention, beliefs, and policy implications for real-world decision-making.
Exploring deep reinforcement learning for autonomous control systems, from fusion plasma to robotics, with a focus on data-efficient methods for real-world applications.
CSE.0002x is an introduction to using computing to solve problems in engineering and science including simulation of time-dependent phenomena; optimization of systems; and quantification of uncertainty.
Comprehensive exploration of digital signal processing fundamentals, covering analysis, representation, and design of discrete-time systems, digital filters, and Fourier transform algorithms for engineers and scientists.
Master facilitative leadership skills for public sector professionals through a four-part series covering concepts, theories, hypotheticals, microskills, and self-assessment.
Topics covered in this course include the general formalism of quantum mechanics, harmonic oscillator, quantum mechanics in three-dimensions, angular momentum, spin, and addition of angular momentum.
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