Introduction to Mathematical Thinking – Stanford University | Coursera

Introduction to Mathematical Thinking – Stanford University | Coursera

English | Size: 1.77 GB (1,902,737,093 Bytes)
Category: CBTs


Learn how to think the way mathematicians do – a powerful cognitive process developed over thousands of years.

The goal of the course is to help you develop a valuable mental ability – a powerful way of thinking that our ancests have developed over three thousand years.
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Quantum Mechanics for Scientists and Engineers (Stanford, 2015)

Quantum Mechanics for Scientists and Engineers (Stanford, 2015)

English | Size: 6.59 GB (7,073,526,180 Bytes)
Category: CBTs


Complete course:
– videos;
– subs (separate files);
– slides (separate pdf files);
– quizzes;
– answers for quizzes;
– reference.
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Coursera – Stanford – Algorithms, Design and Analysis, Part 2 [104 Webrips (mp4)]

Coursera – Stanford – Algorithms, Design and Analysis, Part 2 [104 Webrips (mp4)]
English | Size: 1.60 GB (1,720,984,198 bytes)
Category: Theory / Reference / Doc


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. You’ll learn what NP-completeness and the famous “P vs. NP” problem mean for the algorithm designer. Finally, we’ll study several strategies for dealing with hard (i.e., NP-complete problems), including the design and analysis of heuristics. Learn how shortest-path algorithms from the 1950s (i.e., pre-ARPANET!) govern the way that your Internet traffic gets routed today; why efficient algorithms are fundamental to modern genomics; and how to make a million bucks in prize money by “just” solving a math problem!
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Coursera – Stanford – Algorithms, Design and Analysis, Part 1 [82 Webrips (mp4)]

Coursera – Stanford – Algorithms, Design and Analysis, Part 1 [82 Webrips (mp4)]
English | Size: 1.34 GB (1,439,999,036 bytes)
Category: Theory / Reference / Doc


In this course you will learn several fundamental principles of algorithm design. You’ll learn the divide-and-conquer design paradigm, with applications to fast sorting, searching, and multiplication. You’ll learn several blazingly fast primitives for computing on graphs, such as how to compute connectivity information and shortest paths. Finally, we’ll study how allowing the computer to “flip coins” can lead to elegant and practical algorithms and data structures. Learn the answers to questions such as: How do data structures like heaps, hash tables, bloom filters, and balanced search trees actually work, anyway? How come QuickSort runs so fast? What can graph algorithms tell us about the structure of the Web and social networks? Did my 3rd-grade teacher explain only a suboptimal algorithm for multiplying two numbers?
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