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离散数学概论 Discrete Mathematics Generality
by 陈斌- 4.7
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Approx. 27 hours to complete
离散数学是计算机科学的基础理论，离散结构的基础知识和逻辑思维的形式化是信息技术类学生的基本功，离散数学的基本概念是理科专业学生进行信息类课程学习的重要基础。 本课程介绍计算机科学和信息技术理论基础的概念和思想方法，介绍数理逻辑、集合论、图论、抽象代数和形式语言与自动机等各部分的基本概念，介绍离散数学基本概念和空间信息技术之间的联系与结合，培养学生理解和掌握离散数学基本概念，采用形式化方法分析问题，并能自觉运用逻辑分析、结构层次分析和同构类比等思想方法解决问题的能力。 数理逻辑：基本概念 01-课程介绍 02-正式内容之前：形式化及其极限 03-正式内容之前：悖论、版画、卡农 04-数理逻辑介绍 05-什么是命题 06-排中律 07-命题符号化 08-逻辑联结词（上） 09-逻辑联结词（下） 10-命题公式 11-真值函数 12-命题形式化 课件 测验#1 数理逻辑：命题逻辑及形式系统 13-重言式 14-逻辑等价式和逻辑蕴涵式 15-代入原理和替换原理 16-证明逻辑等价式和逻辑蕴涵式 17-范式及基本术语 18-求范式的一般步骤 19-主范式 20-联结词集完备性 21-形式系统和证明、演绎 22-命题演算形式系统PC 23-PC中的定理证明 24-三个元定理 25-定理判定问题 课件 测验#2 数理逻辑：谓词逻辑及形式系统 26-数理逻辑-个体、谓词和量词 27-数理逻辑-谓词公式 28-数理逻辑-谓词公式永真式 29-数理逻辑-谓词演算形式系统FC 30-数理逻辑-全称引入规则及存在消除规则 31-数理逻辑-自然推理系统 32-数理逻辑-ND中的定理证明 课件 测验#3 集合论：集合代数 33-集合论与无限 34-集合基本概念 35-子集合 36-集合基本运算 37-集合族及运算 38-归纳定义 39-自然数的定义...
Квантовые вычисления (Quantum computing)
by Сысоев Сергей Сергеевич- 0.0
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Approx. 14 hours to complete
Квантовые вычисления — это технологии будущего, в которых остро нуждаются уже в современном мире. Потребность в специалистах технологии будущего подтверждает актуальность данного курса сегодня. В течение курса учащиеся поймут где точки соприкосновения физики и информатики, знакомятся с алгоритмами для квантового компьютера, алгоритмами Шора и алгоритмами Гровера. Введение О чем этот курс?...
Algorithms on Strings
by Alexander S. Kulikov , Michael Levin , Pavel Pevzner , Neil Rhodes- 4.5
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Approx. 18 hours to complete
World and internet is full of textual information. We search for information using textual queries, we read websites, books, e-mails. All those are strings from the point of view of computer science. To make sense of all that information and make search efficient, search engines use many string algorithms. Suffix Trees...
Overview of Advanced Methods of Reinforcement Learning in Finance
by Igor Halperin- 3.8
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Approx. 13 hours to complete
In the last course of our specialization, Overview of Advanced Methods of Reinforcement Learning in Finance, we will take a deeper look into topics discussed in our third course, Reinforcement Learning in Finance. Finally, we will overview trending and potential applications of Reinforcement Learning for high-frequency trading, cryptocurrencies, peer-to-peer lending, and more....
Artificial Intelligence Data Fairness and Bias
by Brent Summers- 4.9
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Approx. 6 hours to complete
In this course, we will explore fundamental issues of fairness and bias in machine learning. As predictive models begin making important decisions, from college admission to loan decisions, it becomes paramount to keep models from making unfair predictions. From human bias to dataset awareness, we will explore many aspects of building more ethical models....
VLSI CAD Part II: Layout
by Rob A. Rutenbar- 4.8
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Approx. 24 hours to complete
You should complete the VLSI CAD Part I: Logic course before beginning this course. A modern VLSI chip is a remarkably complex beast: billions of transistors, millions of logic gates deployed for computation and control, big blocks of memory, embedded blocks of pre-designed functions designed by third parties (called “intellectual property” or IP blocks)....
Geometric Algorithms
by Kevin Buchin- 0.0
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Approx. 18 hours to complete
Course Information: In many areas of computer science such as robotics, computer graphics, virtual reality, and geographic information systems, it is necessary to store, analyze, and create or manipulate spatial data. This course deals with the algorithmic aspects of these tasks: we study techniques and concepts needed for the design and analysis of geometric algorithms and data structures....
Delivery Problem
by Alexander S. Kulikov- 4.7
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Approx. 14 hours to complete
We’ll implement (in Python) together efficient programs for a problem needed by delivery companies all over the world millions times per day — the travelling salesman problem. The goal in this problem is to visit all the given places as quickly as possible. How to find an optimal solution to this problem quickly?...
Advanced Algorithms and Complexity
by Alexander S. Kulikov , Michael Levin , Daniel M Kane , Neil Rhodes- 4.6
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Approx. 27 hours to complete
You've learned the basic algorithms now and are ready to step into the area of more complex problems and algorithms to solve them. Advanced algorithms build upon basic ones and use new ideas. We then proceed to linear programming with applications in optimizing budget allocation, portfolio optimization, finding the cheapest diet satisfying all requirements and many others....
Genome Assembly Programming Challenge
by Alexander S. Kulikov , Michael Levin , Pavel Pevzner , Neil Rhodes- 4.5
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Approx. 18 hours to complete
In Spring 2011, thousands of people in Germany were hospitalized with a deadly disease that started as food poisoning with bloody diarrhea and often led to kidney failure. It was the beginning of the deadliest outbreak in recent history, caused by a mysterious bacterial strain that we will refer to as E....
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