Awesome free online courses starting this April at Coursera and EDX, and there is still time for you to pick your favorite online course from top universities and colleges across the country and get started. Have you ever wished to take a course from a top ranked university…for FREE? Here is your chance. Look through the list below and if you find an online course that interests you, I think that you should take it if you have the time. There are many online courses being offered and no matter your background you should be able to find something that will interest you or someone you know. Spread the word, taking advantage of a free online course from a top university is a great way to occupy your “free” time and expand your horizons.
Understanding Einstein: The Special Theory of Relativity
Instructor: Larry Randles Lagerstrom
Institution: Stanford
Course Location: Coursera
Duration and Workload: 8 weeks long @ 5-7 hours/week
Start Date: Monday, April 29, 2013
Prerequisites: None
Course Description: This course offers you the opportunity to gain a deeper understanding of the life and work of the young Albert Einstein and especially his mind-bending special theory of relativity.
Medical Neuroscience
Instructor:Leonard E. White
Institution: Duke University School Of Medicine
Course Location: Coursera
Duration and Workload: 8 weeks long @ 5-7 hours/week
Start Date: Monday, April 29, 2013
Prerequisites: College-level background in cellular and molecular biology and general knowledge of systems physiology and human anatomy
Course Description: Explore the structure and function of the human central nervous system. Learn why knowledge of human neuroanatomy, neurophysiology, neural plasticity, and new discovery in the brain sciences matters for clinical practice.
Probabilistic Graphical Models
Instructor: Daphne Koller
Institution: Stanford
Location: Coursera
Duration and Workload: 8 weeks long @ 5-7 hours/week
Start Date: Monday, April 29, 2013
Prerequisites: Knowledge of a Programming Language and Exposure to Discrete Probability Theory
Course Description: In this class, you will learn the basics of the PGM representation and how to construct them, using both human knowledge and machine learning techniques.
Microeconomics Principles
Instructor:José J. Vázquez-Cognet
Institution: University of Illinois at Urbana-Champaign
Location: Coursera
Duration and Workload: 8 weeks long @ 5-7 hours/week
Start Date: Monday, April 29, 2013
Prerequisites: Elementary Algebra
Course Description: Introduction to the functions of individual decision-makers, both consumers and producers, within the larger economic system. Primary emphasis on the nature and functions of product markets, the theory of the firm under varying conditions of competition and monopoly, and the role of government in promoting efficiency in the economy.
The Hardware/Software Interface
Instructor: Luis Ceze and Gaetano Borriello
Institution: University of Washington
Location: Coursera
Duration and Workload: 8 weeks long @ 5-7 hours/week
Start Date: Monday, April 29, 2013
Prerequisites: None
Course Description: Examines key computational abstraction levels below modern high-level languages. From Java/C to assembly programming, to basic processor and system organization.
An Introduction to Interactive Programming in Python
Instructors: Joe Warren, Scott Rixner, Stephen Wong and John Greiner
Institution: Rice University
Location: Coursera
Duration and Workload: 8 weeks long @ 5-7 hours/week
Start Date: Monday, April 29, 2013
Prerequisites: High school Math
Course Description:
This course is designed to be a fun introduction to the basics of programming in Python. Our main focus will be on building simple interactive games such as Pong, Blackjack and Asteroids. I am sure that this online IT course offered by Rice University will be fun and useful at the same time.
An Introduction to Operations Management
Instructor:Christian Terwiesch
Institution: University of Pennsylvania
Location:Coursera
Duration and Workload: 8 weeks long @ 5-7 hours/week
Start Date: Monday, April 29, 2013
Prerequisites: High school Math
Course Description:
This course will teach you how to analyze and improve business processes, be it in services or in manufacturing. You will learn how to improve productivity, how to provide more choice to customers, how to reduce response times, and how to improve quality.
Grow to Greatness: Smart Growth for Private Businesses, Part II
Instructor: Edward D. Hess
Institution: University of Virginia Darden School of Business
Location:Coursera
Duration and Workload: 4 weeks long @ 4-6 hours/week
Start Date: Monday, April 29, 2013
Prerequisites: None
Course Description: This course focuses on the common human resource (“people”) challenges faced by existing private businesses when they attempt to grow substantially. PART 1 OF THE GROW TO GREATNESS COURSE IS NOT A PREREQUISITE FOR TAKING THIS COURSE.
Sports and Society
Instructor: Orin Starn
Institution: Duke University
Location:Coursera
Duration and Workload: 7 weeks long @ 5-7 hours/week
Start Date: Apr 30th 2013
Prerequisites: None
Course Description: This course explores the role of sports around the world, and how the games we watch and play shape identity, culture, and society.
Writing II: Rhetorical Composing
Instructors:Susan Delagrange, Cynthia Selfe, Kay Halasek, Ben McCorkle and Scott Lloyd DeWitt
Institution: The Ohio State University
Location:Coursera
Duration and Workload: 10 weeks long @ 6-10 hours/week
Start Date: Apr 22nd 2013
Prerequisites: None
Course Description: Rhetorical Composing engages you in a series of interactive reading, research, and composing activities along with assignments designed to help you become more effective consumers and producers of alphabetic, visual and multimodal texts. Join us to become more effective writers… and better citizens.
Community Change in Public Health
Instructor:William Brieger
Institution: Johns Hopkins University
Location:Coursera
Duration and Workload: 6 weeks long @ 5-8 hours/week
Start Date: Apr 22nd 2013
Prerequisites: None
Course Description: This course examines the community context of the changes needed to promote the public’s health.
Drug Discovery, Development & Commercialization
Instructors: Williams S. Ettouati and Joseph D. Ma
Institution: Johns Hopkins University
Location:Coursera
Duration and Workload: 9 weeks long @ 3-4 hours/week
Start Date: Apr 19th 2013
Prerequisites: None
Course Description: Students will learn the process of drug discovery and development through specific examples of case studies to better understand the issues facing the challenges of delivering a new drug on the market. At the completion of this course you will be able to have a better understanding of how a small or large molecule becomes a pharmaceutical drug.
Machine Learning
Instructor:Andrew Ng
Institution: Stanford University
Location:Coursera
Duration and Workload: 10 weeks long @ 5-7 hours/week
Start Date: Apr 22nd 2013
Prerequisites: None
Course Description: Learn about the most effective machine learning techniques, and gain practice implementing them and getting them to work for yourself.
Computational Neuroscience
Instructors:Rajesh P. N. Rao and Adrienne Fairhall
Institution: University of Washington
Location:Coursera
Duration and Workload: 8 weeks long @ 4-6 hours/week
Start Date: Apr 19th 2013
Prerequisites: None
Course Description: Understanding how the brain works is one of the fundamental challenges in science today. This course will introduce you to basic computational techniques for analyzing, modeling, and understanding the behavior of cells and circuits in the brain. You do not need to have any prior background in neuroscience to take this course.
Mathematical Biostatistics Boot Camp
Instructor: Brian Caffo
Institution: Johns Hopkins University
Location:Coursera
Duration and Workload: 7 weeks long @ 3-5 hours/week
Start Date: Apr 16th 2013
Prerequisites: High School Math
Course Description: This class presents the fundamental probability and statistical concepts used in elementary data analysis. It will be taught at an introductory level for students with junior or senior college-level mathematical training including a working knowledge of calculus. A small amount of linear algebra and programming are useful for the class, but not required.
Healthcare Innovation and Entrepreneurship
Instructors: Marilyn M. Lombardi and Bob Barnes
Institution: Duke University
Location:Coursera
Duration and Workload: 6 weeks long @ 5-7 hours/week
Start Date: Apr 15th 2013
Prerequisites: None
Course Description: This interdisciplinary course focuses on sustainable innovation, introducing entrepreneurial students to the realities of problem identification and solution design within the complex world of healthcare.
Probabilistic Graphical Models
Instructor:Daphne Koller
Institution: Stanford
Location:Coursera
Duration and Workload: 11 weeks long @ 15-20 hours/week
Start Date: Apr 8th 2013
Prerequisites: None
Course Description: In this class, you will learn the basics of the PGM representation and how to construct them, using both human knowledge and machine learning techniques.
Introduction to Guitar
Instructor: Thaddeus Hogarth
Institution: Berkley School of Music
Location:Coursera
Duration and Workload: 6 weeks long @ 6-8 hours/week
Start Date: Apr 22nd 2013
Prerequisites: None
Course Description: Grasp the essentials needed to begin playing acoustic or electric guitar. You’ll learn an easy approach to get you playing quickly, through a combination of exploring the instrument, performance technique, and basic music theory.
Introduction to Improvisation
Instructor: Gary Burton
Institution: Berkley School of Music
Location:Coursera
Duration and Workload: 5 weeks long @ 6-8 hours/week
Start Date: Apr 22nd 2013
Prerequisites: None
Course Description: Learn the basic concepts of improvisation from Gary Burton, one of the most renowned improvisers in the jazz world, including the mental, melodic, and harmonic processes that contribute to the instinctive skills that an improviser puts to use when taking a solo.
2.01x: Elements of Structures
Instructors: Simona Socrate, Alexie M. Kolpak, Sandeep Kumar and Kun Qian
Institution: MIT
Location:EDX
Duration and Workload: 13 weeks long @ 12 hours/ week
Start Date: Apr 15, 2013
Prerequisites: Classical mechanics and calculus
Course Description: 2.01x is a first course on the mechanical behavior of deformable structural elements. It introduces principles of structural analysis in applications to essential load-bearing elements, such as bars in axial loading, axisymmetric shafts in torsion, and symmetric beams in bending. The course covers fundamental concepts of continuum mechanics, including internal forces, displacement fields, stresses, and strains. The students will learn to predict linear elastic structural behavior, and prevent failure, by relying on the notions of equilibrium, geometric compatibility, and constitutive material response.
Stat2.2x: Introduction to Statistics: Probability
Instructors: Ani Adhikari, Philip B. Stark, Paul Matsiras and Gordon A. Heaton
Institution: Berkeley
Location:EDX
Duration and Workload: 6 weeks long
Start Date: Apr 12, 2013
Prerequisites: High School Math
Course Description: Statistics 2 at Berkeley is an introductory class taken by about 1000 students each year. Stat2.2x is the second of three five-week courses that make up Stat2x, the online equivalent of Berkeley’s Stat 2.
The focus of Stat2.2x is on probability theory: exactly what is a random sample, and how does randomness work? If you buy 10 lottery tickets instead of 1, does your chance of winning go up by a factor of 10? What is the law of averages? How can polls make accurate predictions based on data from small fractions of the population? What should you expect to happen “just by chance”? These are some of the questions we will address in the course.
We will start with exact calculations of chances when the experiments are small enough that exact calculations are feasible and interesting. Then we will step back from all the details and try to identify features of large random samples that will help us approximate probabilities that are hard to compute exactly. We will study sums and averages of large random samples, discuss the factors that affect their accuracy, and use the normal approximation for their probability distributions.
Be warned: by the end of Stat2.2x you will not want to gamble. Ever. (Unless you’re really good at counting cards, in which case you could try blackjack, but perhaps after taking all these edX courses you’ll find other ways of earning money.)
As Stat2.2x is part of a series, the basic prerequisites are the same as those for Stat2.1x: high school arithmetic and good comprehension of English. In addition, you are expected to know the material of Stat2.1x, with particular emphasis on histograms, averages, SDs, and the normal curve.
The fundamental approach of the series was provided in the description of Stat2.1x and appears here again: There will be no mindless memorization of formulas and methods. Throughout the course, the emphasis will be on understanding the reasoning behind the calculations, the assumptions under which they are valid, and the correct interpretation of results.
Which of these courses will you be taking?
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