MIT 8.323 Relativistic Quantum Field Theory I

Instructor: Hong Liu
This course is a one-term self-contained subject in quantum field theory. Concepts and basic techniques are developed through applications in elementary particle physics and condensed matter physics.

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MIT 8.333 Statistical Mechanics I: Statistical Mechanics of Particles

Instructor: Mehran Kardar
Statistical Mechanics is a probabilistic approach to equilibrium properties of large numbers of degrees of freedom. In this two-semester course, basic principles are examined. Topics…

MIT 6.046J / 18.410J Introduction to Algorithms (SMA 5503)

This course teaches techniques for the design and analysis of efficient algorithms, emphasizing methods useful in practice. Topics covered include: sorting; search trees, heaps, and hashing; divide-and-conquer; dynamic…

MIT 5.111 Principles of Chemical Science

Instructor: Catherine Drennan
An introduction to the chemistry of biological, inorganic, and organic molecules with emphasis on basic principles of atomic and molecular electronic structure, thermodynamics, acid-base and redox equilibria,…

MIT 18.085 Computational Science & Engineering

This course provides a review of linear algebra, including® applications to networks, structures, and estimation, Lagrange multipliers. Also covered are: differential equations of equilibrium; Laplace's equation and potential flow;…

MIT 3.091 Introduction to Solid State Chemistry
This course covers basic chemistry principles for engineering. It includes topics like electronic structure, chemical bonding, and arrangements in solids. It also looks at industrial applications, environmental impacts, energy…

MIT 7.016 Introductory Biology
#Biology #Genetics #Cancer #CellBiology

Instructors: Barbara Imperiali, Adam Martin, Diviya Ray
7.016 Introductory Biology provides an introduction to fundamental principles of biochemistry, molecular biology and genetics for understanding the…

MIT 18.065 Matrix Methods in Data Analysis, Signal Processing, and Machine Learning by the greatest math teacher in the world #math #MachineLearning

Lecture 1: The Column Space of A Contains All Vectors Ax
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Lecture 2: Multiplying and Factoring Matrices…

MIT RES.6.007 Signals and Systems
this material is over 40 years old, yet it is still the best on you tube so far...

Lecture 1, Introduction
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Lecture 2, Signals and Systems: Part 1
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Lecture 3, Signals and Systems: Part II…

MIT 6.858 Computer Systems Security

Instructor: Nickolai Zeldovich
This is a class on the design and implementation of secure computer systems, focusing on threat models, attacks that compromise security, and techniques for achieving security.

1. Introduction, Threat Models…

MIT 14.73 The Challenge of World Poverty #poverty

1. Introduction (14.73 The Challenge of World Poverty)
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2. What is a Poverty Trap?
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3. Social Experiments: Why and How?
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5. Is There a Nutrition-Based…

MIT 6.01SC Introduction to EECS I -- This course provides an integrated introduction to electrical engineering and computer science, including modern software engineering, linear systems analysis, electronic circuits, and decision-making.

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MIT 15.S50 Poker Theory and Analysis

1. Introduction to Poker Theory
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2. Analytical Techniques
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3. Basic Strategy
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4. Preflop Analysis
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5. Tournament Play
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6.…

MIT 6.001 Structure and Interpretation

This course introduces students to the principles of computation. Upon completion of 6.001, students should be able to explain and apply the basic methods from programming languages to analyze computational systems, and to generate…

MIT 5.60 Thermodynamics & Kinetics:
This subject deals primarily with equilibrium properties of macroscopic systems, basic thermodynamics, chemical equilibrium of reactions in gas and solution phase, and rates of chemical reactions.

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Build Abstractions Not Illusions • Gregor Hohpe(AWS Senior Principal Evangelist)
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This talk reflects on two decades of building complex distributed systems, highlighting where abstractions helped and where illusions led to major disappointments.

Introduction to Computer Science - Harvard's CS50
#python #programming #developer

1. Computational Thinking & Scratch
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2. C Programming Language
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3. Arrays and Sorting Algorithms
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4. Memory…

Round 2 for Sam Altman: OpenAI, GPT-5, Sora, Board Saga, Elon Musk, Ilya, Power & AGI | Lex Fridman Podcast #419
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MIT 18.650 Statistics for Applications #Statistics

Instructor: Philippe Rigollet
This course offers an in-depth the theoretical foundations for statistical methods that are useful in many applications.
The goal is to understand the role of mathematics in the research and…

MIT 6.006 Introduction to Algorithms #Algorithms

Instructor: Prof. Erik Demaine, Dr. Jason Ku, Prof. Justin Solomon
This course is an introduction to mathematical modeling of computational problems, as well as common algorithms, algorithmic paradigms, and data structures used…