Stanford's University, World-renowned Stanford University provides online learning to people around the world free of cost high-quality educational experiences by unleashing creativity and innovation in online learning. Stanford's free online courses are taught by regular Stanford faculty and are highly interactive. Interested candidates can refer this post for more details and apply. For more details click on read more.
Enrolls do not get Stanford credit for their work, but they do receive a statement of accomplishment if they successfully complete a course. The classes are delivered on a number of different platforms.
Stanford Online will undertake Study online learning through a series of creative and innovative experiments formulated by teaching faculty. These experiments may involve new uses of technology or new teaching models supported by technology.
The following courses are scheduled to begin soon. Introduction to Mathematical Thinking
Course begins on September 17, 2012
This course will help you learn how to think the way mathematicians do - a powerful cognitive process developed over thousands of years.
Session: 17 September 2012 (7 weeks long)
Workload: 8-10 hrs/week hours/week
About the Course
The goal of the course is to help you develop a valuable mental ability – a powerful way of thinking that our ancestors have developed over three thousand years.
The primary audience is first-year students at college or university who are thinking of majoring in mathematics or a mathematically-dependent subject, or high school seniors who have such a college career in mind.
They will need mathematical thinking to succeed in their major. Because mathematical thinking is a valuable life skill, however, anyone over the age of 17 could benefit from taking the course.
Course Syllabus
Instructor’s welcome and introduction
1. Introductory material
2. Analysis of language – the logical combinators
3. Analysis of language – implication
4. Analysis of language – equivalence
5. Analysis of language – quantifiers
6. Working with quantifiers
7. Proofs
8. Proofs involving quantifiers
9. Elements of number theory
10. Beginning real analysis
Recommended Background
Recommended Background is high school mathematics. The course does not carry Stanford credit. If you finish the course, you will get a Certificate of Completion, and for those who do well on the coursework and the final exam the certificate will indicate Completion with Distinction.
Human-Computer Interaction
Course begins on September 24, 2012
This course will help you to build human-centered design skills, so that you have the principles and methods to create excellent interfaces with any technology.
Session: 24 September 2012 (5 weeks long)
Workload: 8-10 hours/week
About the Course
In this course, you will learn how to design technologies that bring people joy, rather than frustration. You'll learn several techniques for rapidly prototyping and evaluating multiple interface alternatives -- and why rapid prototyping and comparative evaluation are essential to excellent interaction design.
Introduction to Logic
Course begins on September 24, 2012
In this course, you will learn how to formalize information and reason systematically to produce logical conclusions. We will also examine logic technology and its applications - in mathematics, science, engineering, business, law, and so forth.
Session: 24 September 2012 (7 weeks long)
Workload: 5-7 hours/week
About the Course
Logic is one of the oldest intellectual disciplines in human history. It dates back to the times of Aristotle; it has been studied through the centuries; and it is still a subject of active investigation today.
This course is a basic introduction to Logic. It shows how to formalize information in form of logical sentences. It shows how to reason systematically with this information to produce all logical conclusions and only logical conclusions. And it examines logic technology and its applications - in mathematics, science, engineering, business, law, and so forth.
The course differs from other introductory courses in Logic in two important ways. First of all, it teaches a novel theory of logic that improves accessibility while preserving rigor. Second, the material is laced with interactive demonstrations and exercises that suggest the many practical applications of the field.
Probabilistic Graphical Models
Course begins on September 24, 2012
Probability theory gives us the basic foundation to model our beliefs about the different possible states of the world. In this class, you'll learn the basics of the PGM representation and how to construct them, using both human knowledge and machine learning techniques. You will also learn algorithms for using a PGM to reach conclusions and make good decisions under uncertainty.
Session: 24 September 2012 (11 weeks long)
Workload: 8-10 hours/week
Course Syllabus
Topics covered include:
1. The Bayesian network and Markov network representation, including extensions for reasoning over domains that change over time and over domains with a variable number of entities
2. Reasoning and inference methods, including exact inference (variable elimination, clique trees) and approximate inference (belief propagation message passing, Markov chain Monte Carlo methods)
3. Learning parameters and structure in PGMs
4. Using a PGM for decision making under uncertainty.
Organizational Analysis
Course begins on September 24, 2012
In this introductory course, you will learn multiple theories of organizational behavior and apply them to
actual cases of organizational change.
About the Course
Through this course, students will consider cases describing various organizational struggles: school systems and politicians attempting to implement education reforms; government administrators dealing with an international crisis; technology firms trying to create a company ethos that sustains worker commitment; and even two universities trying to gain international standing by performing a merger.
Course Syllabus
Week 1: Introduction
Week 2: Decisions by rational and rule-based procedures
Week 3: Decisions by dominant coalitions
Week 4: Decisions in organized anarchies
Week 5: Developing organizational learning and intelligence
Week 6: Developing an organizational culture
Week 7: Managing resource dependencies
Week 8: Network forms of organization
Week 9: Institutions and organizational legitimacy
Week 10: Summary
Algorithms: Design and Analysis, Part 2
Course begins on October, 2012
In this course you will learn several fundamental principles of advanced algorithm design: greedy algorithms and applications; dynamic programming and applications; NP-completeness and what it means for the algorithm designer; the design and analysis of heuristics
Session: October 2012 (6 weeks long)
Workload: 5-7 hours/week
About the Course
In this course you will learn several fundamental principles of advanced algorithm design. You'll learn the greedy algorithm design paradigm, with applications to computing good network backbones (i.e., spanning trees) and good codes for data compression. You'll learn the tricky yet widely applicable dynamic programming algorithm design paradigm, with applications to routing in the Internet and sequencing genome fragments.
Recommended Background
This course builds off Algo 1.How to program in at least one programming language (like C, Java, or Python); and familiarity with proofs, including proofs by induction and by contradiction.
Cryptography II
Course begins on January 21, 2013
This course will help you Learn about the inner workings of cryptographic primitives and protocols and how to apply this knowledge in real-world applications.
Session: 21 January 2013 (6 weeks long)
Workload: 6-8 hours/week
About the Course
Cryptography is an indispensable tool for protecting information in computer systems. This course is a continuation of Crypto 1 and explains the inner workings of public-key systems and cryptographic protocols. Students will learn how to reason about the security of cryptographic constructions and how to apply this knowledge to real-world applications.
The course begins with constructions for digital signatures and their applications. We will then discuss protocols for user authentication and zero-knowledge protocols.
Next we will turn to privacy applications of cryptography supporting anonymous credentials and private database lookup.
We will conclude with more advanced topics including multi-party computation and elliptic curve cryptography. Throughout the course students will be exposed to many exciting open problems in the field.
The course will include written homeworks and optional programming labs. The material is self-contained, but the course assumes knowledge of the topics covered in Crypto 1 as well as a basic understanding of discrete probability theory.
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