2.160 Identification, Estimation, and Learning (MIT)
This course provides a broad theoretical basis for system identification, estimation, and learning. Students will study least squares estimation and its convergence properties, Kalman filters, noise dynamics and system representation, function approximation theory, neural nets, radial basis functions, wavelets, Volterra expansions, informative data sets, persistent excitation, asymptotic variance, central limit theorems, model structure selection, system order estimate, maximum likelihood, unbia
9.520 Statistical Learning Theory and Applications (MIT)
This course is for upper-level graduate students who are planning careers in computational neuroscience. This course focuses on the problem of supervised learning from the perspective of modern statistical learning theory starting with the theory of multivariate function approximation from sparse data. It develops basic tools such as Regularization including Support Vector Machines for regression and classification. It derives generalization bounds using both stability and VC theory. It also dis
Multiplication: Learning Times Tables for 8s and 2s
Math times table created from fun patterns as a way to learn
multiplication tables for Eights and Twos. This video also teaches place value. This video has the student create worksheets where they can learn the times tables. This is useful for teaching math in a classroom, at home, as part of homeschool or as fun homework. Right Brain Math can teach Elementary Students. Curriculum Review magazine calls it a revolutionary approach to introducing math. It is also very effective for remedia
11.965 Reflective Practice: An Approach for Expanding Your Learning Frontiers (MIT)
The course is an introduction to the approach of Reflective Practice developed by Donald Schön. It is an approach that enables professionals to understand how they use their knowledge in practical situations and how they can combine practice and learning in a more effective way. Through greater awareness of how they deploy their knowledge in practical situations, professionals can increase their capacities of learning in a more timely way. Understanding how they frame situations and ideas h
18.465 Topics in Statistics: Statistical Learning Theory (MIT)
The main goal of this course is to study the generalization ability of a number of popular machine learning algorithms such as boosting, support vector machines and neural networks. Topics include Vapnik-Chervonenkis theory, concentration inequalities in product spaces, and other elements of empirical process theory.
6.867 Machine Learning (MIT)
6.867 is an introductory course on machine learning which gives an overview of many concepts, techniques, and algorithms in machine learning, beginning with topics such as classification and linear regression and ending up with more recent topics such as boosting, support vector machines, hidden Markov models, and Bayesian networks. The course will give the student the basic ideas and intuition behind modern machine learning methods as well as a bit more formal understanding of how, why, and whe
9.03 Neural Basis of Learning and Memory (MIT)
This course highlights the interplay between cellular and molecular storage mechanisms and the cognitive neuroscience of memory, with an emphasis on human and animal models of hippocampal mechanisms and function. Class sessions include lectures and discussion of papers.
SP.291 Learning Seminar: Experiments in Education (MIT)
This seminar explores experiments in education and discusses how education and learning might be done, through reading and discussion. This seminar is not a survey of experiments in education, but rather, its goal is to determine how learning should happen and what kinds of contexts allow it to happen.
11.941 Learning by Comparison: First World/Third World Cities (MIT)
The primary purpose of this seminar is to enable students to craft approaches to so-called "First World"/ "Third World" city comparisons that are theoretically sophisticated, methodologically rigorous, contextually grounded, and significantly beneficial. Since there exists very little literature and very few projects which compare "First World" and "Third World" cities in a sophisticated and genuinely useful manner, the seminar is structured around a series of readings, case studies, and discuss
SP.693 Gender, Race, and the Complexities of Science and Technology: A Problem-Based Learning Experi
What can we learn about science and technology–and what can we do with that knowledge? Who are "we" in these questions?–whose knowledge and expertise gets made into public policy, new medicines, topics of cultural and political discourse, science education, and so on? How can expertise and lay knowledge about science and technology be reconciled in a democratic society? How can we make sense of the interactions of living and non-living, humans and non-humans, individual and
21L.016 Learning from the Past: Drama, Science, Performance (MIT)
This class explores the creation (and creativity) of the modern scientific and cultural world through study of western Europe in the 17th century, the age of Descartes and Newton, Shakespeare, Milton and Ford. It compares period thinking to present-day debates about the scientific method, art, religion, and society. This team-taught, interdisciplinary subject draws on a wide range of literary, dramatic, historical, and scientific texts and images, and involves theatrical experimentation as well
MAS.714J Technologies for Creative Learning (MIT)
This course explores the design of innovative educational technologies and creative learning environments, drawing on specific case studies such as the LEGO® Programmable Brick, Scratch software and Computer Clubhouse after-school learning centers. Includes activities with new educational technologies, reflections on learning experiences, and discussion of strategies and principles underlying the design of new tools and activities.
7.340 Learning and Memory: Activity-Controlled Gene Expression in the Nervous System (MIT)
The mammalian brain easily outperforms any computer. It adapts and changes constantly. Most importantly, the brain enables us to continuously learn and remember. What are the molecular mechanisms that lead to learning and memory? What are the cellular roles that activity-regulated gene products play to implement changes in the brain?How do nerve cells, their connections (synapses), and brain circuits change over time to store information? We will discuss the molecular mechanisms of neuronal plas
Rate-Time-Distance, Problem 3
The instructor solves this word problem using uniform motion rt=d formula: A 555-mile, 5-hour trip on the Autobahn was driven at two speeds. The average speed of the car was 105 mph on the first part of the trip, and the average speed was 115 mph for the second part. How long did the car drive at each speed? Answer: 105 mph for 2 hours and 115 mph for 3 hours.
Rate-Time-Distance, Problem 1
The solves this word problem using uniform motion rt=d formula: Two cyclists start at the same corner and ride in opposite directions. One cyclist rides twice as fast as the other. In 3 hours, they are 81 miles apart. Find the rate of each cyclist. Answer: 9 mph and 18 mph
Rate-Time-Distance, Problem 2
The instructor solves this word problem using uniform motion rt=d formula: A jogger started running at an average speed of 6 mph. Half an hour later, another runner started running after him starting from the same place at an average speed of 7 mph. How long will it take for the runner to catch up to the jogger? Answer: 3 hours
Rate-Time-Distance, Problem 4
The insructor solves this word problem using uniform motion rt=d formula: Andy and Beth are at opposite ends of a 18-mile country road with plans to leave at the same time running toward each other to meet. Andy runs 7 mph while Beth runs 5 mph. How long after they begin will they meet? Answer: 1.5 hours
Rate-Time-Distance, Problem 5
The instructor solves this word problem using uniform motion rt=d formula: A car and a bus set out at 2 pm from the same spot, headed in the same direction. The average speed of the car is twice the average speed of the bus. After 2 hours, the car is 68 miles ahead of the bus. Find the rate of the bus and the car. Answer: Bus speed: 34 mph; Car speed: 68 mph
Rate-Time-Distance, Problem 6
The instructor solves this word problem using uniform motion rt=d formula: A pilot flew from one city to another city averaging 150 mph. Later, it flew back to the first city averaging 100 mph. The total flying time was 5 hours. How far apart are the cities? Answer: 300 miles
Learning the Alphabet
This educational video provides a great way to learn the alphabet. It
includes the sounds that each letter makes, and has pictures of
different items to go along with each letter. It’s a great and fun way
for children to learn the alphabet.