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Open Course Lectures
!autodidact@slrpnk.net @autodidact@slrpnk.net This new community is intended to act as a more traditional discussion and link based companion to this one. This has the advantage of keeping this community [searchable](https://slrpnk.net/post/6350862), while also allowing for the sorts of resources that don't fit well in this community. There is also a new [matrix chat](https://matrix.to/#/#autodidact:matrix.org) meant to supplement both communities. This is a great place to request resources or find a study buddy!
[Click here or in the sidebar to search](https://slrpnk.net/search?type=All&communityId=137197) Try searching for a particular subject by using hashtags. For example, [this is what happens when you look for #math](https://slrpnk.net/search?q=%23math&type=All&listingType=All&communityId=137197&page=1&sort=TopAll). We can leverage full-text search to build functional repositories for resources, in contrast to the more traditional discussion based structure (check !autodidact@slrpnk.net for discussion).
## Post Template: >**Institution:** School U **Lecturer:** Professor Professerson **University Course Code:** Subject 101 **Subject:** #tag #tagtheory **Year:** 1902 **Description:** Lorem ipsum dolor sit amet, consectetur adipiscing elit. Quisque orci elit, hendrerit in odio eu, ullamcorper mollis lectus. Nulla imperdiet elit lacus. Nunc molestie tristique eros, vitae egestas libero dapibus in. Praesent mollis rhoncus finibus. Nunc vel sodales odio, vel maximus elit. Aliquam vitae velit ut arcu sagittis luctus eleifend in purus. Vestibulum ultrices, ligula nec consectetur pulvinar, sem magna ultricies dolor, eget hendrerit justo arcu vel est. In in imperdiet libero. ----- **A note on the subject field:** At this time, I believe this field is best used for search purposes and so is most suited to hashtags. Please include as many tags as are relevant and be open to suggestions from the comments.
Institution: Yale Lecturer: Professor Shelly Kagan University Course Code: PHIL 176 Subject: #philosophy #death #metaphysics #valuetheory Year: Spring 2007 Description: There is one thing I can be sure of: I am going to die. But what am I to make of that fact? This course will examine a number of issues that arise once we begin to reflect on our mortality. The possibility that death may not actually be the end is considered. Are we, in some sense, immortal? Would immortality be desirable? Also a clearer notion of what it is to die is examined. What does it mean to say that a person has died? What kind of fact is that? And, finally, different attitudes to death are evaluated. Is death an evil? How? Why? Is suicide morally permissible? Is it rational? How should the knowledge that I am going to die affect the way I live my life? Course materials can be found on the [Open Yale Courses](https://oyc.yale.edu/death/phil-176) website.
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.
www.youtube.com
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 post of my post from elsewhere. I was told y'all might appreciate this.
en.wikiversity.org
**Institution:** Wikiversity **Lecturer:** Boud Roukema **Subject:** #physics #specialrelativity #generalrelativity **Description:** Special relativity and steps towards general relativity is a one-semester Wikiversity course that uses the geometrical approach to understanding special relativity and presents a few elements towards general relativity. The course may be used in a traditional university, within the conditions of the free licensing terms indicated at the bottom of this Wikiversity web page. It may be modified and redistributed according to the same conditions, for example, via the Wikiversity and Wikimedia Commons web sites.
Do you post your full lectures online? Please consider sharing them to [@opencourselectures](https://slrpnk.net/c/opencourselectures). A community dedicated to collecting and discussing freely available full length lecture series for autodidacts and personal development! I believe the distribution of knowledge is by far the most important function of the internet and I need your help to bring some of that functionality to the fediverse. Please boost for visibility! [@academicchatter](https://a.gup.pe/u/academicchatter)
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: 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.
www.youtube.com
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: 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:** DeepMind x UCL **Lecturer:** Hado van Hasselt **University Course Code:** na **Subject:** #machinelearning #ml
**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: Knauss School of Business University of San Diego Lecturer: Fred Freundlich (professor at Mondragon University) Subject: [#modragon](https://kbin.social/tag/modragon) [#coops](https://kbin.social/tag/coops) Year: 2014 Description: Mondragon is one of the leading international examples of cooperative ownership of enterprise and inter-firm collaboration. Mondragon has not only made these characteristics its foundational values, but it also uses them strategically, to complete around the world in advanced manufacturing, retail, finance and knowledge. This presentation introduces Mondragon, its special features and its particular international challenges.
www.youtube.com
Professor Ian Hodder is the Dunlevie Family Professor in the department of anthropology at Stanford University. He also led the Çatalhöyük Research Project, directing an international team of archaeologists in excavating Çatalhöyük, a 9,000-year-old site in Turkey and one of the world’s first urban centers. His work contributes to our understanding of the development of one of the world’s earliest societies, the social and economic organization of the settlement, and the transformation from hunting and gathering to agriculture and civilization.
www.youtube.com
**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.
Just started a new Lemmy community for sharing freely available full-length college courses and lectures. You can follow from Mastodon at [@opencourselectures](https://slrpnk.net/c/opencourselectures) [\#lemmy](https://hachyderm.io/tags/lemmy) [#fediverse](https://hachyderm.io/tags/fediverse) [#academia](https://hachyderm.io/tags/academia) [#selfstudy](https://hachyderm.io/tags/selfstudy) [#learning](https://hachyderm.io/tags/learning)
**Institution:** Yale **Lecturer:** John Geanakoplos **University Course Code:** ECON 251 **Subject:** #economics #finance **Description:** This course attempts to explain the role and the importance of the financial system in the global economy. Rather than separating off the financial world from the rest of the economy, financial equilibrium is studied as an extension of economic equilibrium. The course also gives a picture of the kind of thinking and analysis done by hedge funds.
www.youtube.com
**Institution:** MIT **Lecturer:** Dr. Casey Rodriguez **Course Code:** MIT 18.100A **Subject:** #math **Description:** This course covers the fundamentals of mathematical analysis: convergence of sequences and series, continuity, differentiability, Riemann integral, sequences and series of functions, uniformity, and the interchange of limit operations. It shows the utility of abstract concepts through a study of real numbers, and teaches an understanding and construction of proofs.
**Institution:** MIT **Lecturer:** Paige Bright **University Course Code:** MIT 18.S190 **Subject:** #math #metricspaces **Description:** How do we go from real analysis on Euclidean space to more general settings? We use metric spaces! In this six-lecture course we develop the general theory of metric spaces, including compact sets, complete metric spaces, and much more.
www.youtube.com
**Institution:** MIT **Lecturer:** Esther Duflo **University Course Code:** MIT 14.771 **Subject:** #econ **Description:** This course provides rigorous introduction to core microeconomic issues in economic development, focusing on both key theoretical contributions and empirical applications to understand both why some countries are poor and on how markets function differently in poor economies. Topics include human capital (education and health); labor markets; credit markets; land markets; firms; and the role of the public sector.
ocw.mit.edu
cross-posted from: https://feddit.de/post/4236874 > Anyone interested in game design and would like to learn more, I can only recommend this free MIT course.
www.youtube.com
**Institution:** Yale. **Lecturer:** Robert Shiller. **University Course Code:** ECON 252. **Subject:** #econ #economics #finance. **Description:** An overview of the ideas, methods, and institutions that permit human society to manage risks and foster enterprise. Description of practices today and analysis of prospects for the future. Introduction to risk management and behavioral finance principles to understand the functioning of securities, insurance, and banking industries.
**Institution:** Cambridge **Lecturer:** Petar Velickovic **University Course Code:** seminar **Subject:** #math #machinelearning #neuralnetworks **Description:** Deriving graph neural networks (GNNs) from first principles, motivating their use, and explaining how they have emerged along several related research lines.
www.youtube.com
**Institution:** Personal Project **Lecturer:** N J Wildberger **University Course Code:** na **Subject:** #stats **Description:** A brief introduction to Probability and Statistics. This short course will be aimed at advanced first year undergraduates, with good algebraic skills and some knowledge of calculus. We will discuss probabilities and odds, random variables, probability distributions (both discrete and continuous), for example the Binomial, Poisson and normal distributions, mean and variance and mention the Central Limit Theorem.
**Institution:** Yale **Lecturer:** Prof. Donald Kagan **University Course Code:** CLCV 205 **Subject:** #history #ancientgreece **Description:** This is an introductory course in Greek history tracing the development of Greek civilization as manifested in political, intellectual, and creative achievements from the Bronze Age to the end of the classical period. Students read original sources in translation as well as the works of modern scholars.
**Institution:** MIT **Lecturer:** Prof. David Hsu **University Course Code:** MIT 11.165 **Subject:** #climate #polisci #politicalscience **Description:** This class is about figuring out together what cities and users can do to reduce their energy use and carbon emissions. Many other classes at MIT focus on policies, technologies, and systems, often at the national or international level, but this course focuses on the scale of cities and users. It is designed for any students interested in learning how to intervene in the energy use of cities using policy, technology, economics, and urban planning.
**Institution**: Berkeley **Lecturer**: Richard E Borcherds **University Course Code**: Math 250A **Subject**: #math #grouptheory **Description**: This is an experimental online course on mathematical group theory, corresponding to about the first third of the Berkeley course 250A (introductory graduate algebra). The level is for first year graduate students or advanced undergraduates. The topics covered are roughly the parts of group theory that a mathematician not specializing in groups might find useful.
www.youtube.com
**Institution**: Harvard **Lecturer**: Benedict Gross **University Course Code**: Math E-222 **Subject**: #math #abstractalgebra **Description**: Algebra is the language of modern mathematics. This course introduces students to that language through a study of groups, group actions, vector spaces, linear algebra, and the theory of fields.
www.youtube.com
**Institution**: MIT **Lecturer**: Prof. Manolis Kellis **University Course Code**: MIT 6.047 **Subject**: #biology #computationalbiology #machinelearning
A Series of lectures from Professor G. William Domhoff, from the University of California. It covers how the corporate rich came to become the dominant power in America, as well as how they function, communicate, and form their networks with one another.
www.youtube.com
- Institution: Missouri State Outreach - Lecturer: Dr. David M. Mitchell - University Course Code: Eco 155 - Subject: Principles of Macroeconomics - Pre-requisite Knowledge: ? - Permalink/Archived Resources: ? I haven't watched the full list yet and I'm not an expert (that's why I'm watching a course on fundamentals), so I'm not sure how good it is. Videos of classes 7, 9, 22, 25 and 30 are missing.
youtube.com
[Recorded Office Hours](https://www.youtube.com/playlist?list=PLh9mgdi4rNewXXh3Yej7icrFY35qDmGT5)
I have found the European Graduate School to be the best source of free video lectures on Philosophy I have found. They of course slant towards Continental philosophy. You get in person lectures and sometimes lecture series from the contemporary greats from Slavoj Žižek, Derrida, Baudrillard, Butler, and many others. [https://youtube.com/@egsvideo?si=qqeB6s3msY6ivXsi](https://youtube.com/@egsvideo?si=qqeB6s3msY6ivXsi)
Based on the outcome of this discussion I would like to put together an easily fillable template that folks will use when they submit. What information do y'all think should be included in each post? In the same vein, what information should be in the title versus the post body? Some things that immediately come to mind: * Institution * Lecturer * University Course Code (e.g. BIO 101) * Subject * Pre-requisite Knowledge * Permalink/Archived Resources
www.youtube.com
ocw.mit.edu
A little dated, unfortunately, but I love this course. I've watched it through at least four times over the years. Maybe I'm weird, but the subject matter is just fascinating to me.