Institution: MIT
Lecturer: Prof. Norvin A. Richards
University Course Code: MIT 24.900
Subject: #linguistics
Description: This class provides some answers to basic questions about the nature of human language. Throughout the course, we examine a number of ways in which human language is a complex but law-governed mental system. Much of the class is devoted to studying some core aspects of this system in detail; we also spend individual classes discussing a number of other issues, including how language is acquired, how languages change over time, language endangerment, and others.

Institution: Yale
Lecturer: Paul H. Fry
University Course Code: ENGL 300
Subject: #lit #literature
Description: This is a survey of the main trends in twentieth-century literary theory. Lectures will provide background for the readings and explicate them where appropriate, while attempting to develop a coherent overall context that incorporates philosophical and social perspectives on the recurrent questions: what is literature, how is it produced, how can it be understood, and what is its purpose?

Institution: DeepMind x UCL
Lecturer: Hado van Hasselt
University Course Code: na
Subject: #machinelearning #ml

Institution: Yale
Lecturer: Ron Smith
University Course Code: GG 140
Subject: #climate #earthscience
Description: This course explores the physical processes that control Earth's atmosphere, ocean, and climate. Quantitative methods for constructing mass and energy budgets. Topics include clouds, rain, severe storms, regional climate, the ozone layer, air pollution, ocean currents and productivity, the seasons, El Niño, the history of Earth's climate, global warming, energy, and water resources.

Institution: MIT
Lecturer: many
University Course Code: MIT 6.S191
Subject: #machinelearning #ml #deeplearning
Description: MIT's introductory program on deep learning methods with applications to computer vision, natural language processing, biology, and more! Students will gain foundational knowledge of deep learning algorithms and get practical experience in building neural networks in TensorFlow. Program concludes with a project proposal competition with feedback from staff and panel of industry sponsors. Prerequisites assume calculus (i.e. taking derivatives) and linear algebra (i.e. matrix multiplication), we'll try to explain everything else along the way! Experience in Python is helpful but not necessary. Listeners are welcome!

Institution: Yale
Lecturer: Ben Polak
University Course Code: Econ 159
Subject: #econ #economics
Description: This course is an introduction to game theory and strategic thinking. Ideas such as dominance, backward induction, Nash equilibrium, evolutionary stability, commitment, credibility, asymmetric information, adverse selection, and signaling are discussed and applied to games played in class and to examples drawn from economics, politics, the movies, and elsewhere.

Institution: Stanford
Lecturer: Fei-Fei Li, Justin Johnson, Serena Yeund
University Course Code: CS 231
Subject: #computervision #machinelearning

Description: Computer Vision has become ubiquitous in our society, with applications in search, image understanding, apps, mapping, medicine, drones, and self-driving cars. Core to many of these applications are visual recognition tasks such as image classification, localization and detection. Recent developments in neural network (aka “deep learning”) approaches have greatly advanced the performance of these state-of-the-art visual recognition systems. This lecture collection is a deep dive into details of the deep learning architectures with a focus on learning end-to-end models for these tasks, particularly image classification. From this lecture collection, students will learn to implement, train and debug their own neural networks and gain a detailed understanding of cutting-edge research in computer vision.

Institution: UCLA

Lecturer: Professor Courtenay Raia

University Course Code: HIST 2D

Subject: #history #science #religion #magic #antiquity #modernity

Year: 2009

Description: Professor Courtenay Raia lectures on science and religion as historical phenomena that have evolved over time. Examines the earlier mind-set before 1700 when into science fitted elements that came eventually to be seen as magical. The course also question how Western cosmologies became "disenchanted." Magical tradition transformed into modern mysticisms is also examined as well as the political implications of these movements. Includes discussion concerning science in totalitarian settings as well as "big science" during the Cold War.

cross-posted from: https://lemmy.ml/post/14647640

Not sure if this is allowed here, and it's not my playlist, but I thought I'd post these tutorials since I've found them helpful for learning the basics.

• Institution: Socratica
• Subject: #python
• Description (copied from Socratica's YT channel): Our Python Tutorials will help you learn Python quickly and thoroughly. We start with "Hello World" and then move on to data structures (sets, lists, tuples and dictionaries). Next we'll cover classes, and give a variety of in-depth examples and applications.