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Big Data, Artificial Intelligence, and Ethics
by Martin Hilbert- 4.6
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Approx. 12 hours to complete
This course gives you context and first-hand experience with the two major catalyzers of the computational science revolution: big data and artificial intelligence. Ethical Computational Social Science...
Digital Signal Processing 2: Filtering
by Paolo Prandoni , Martin Vetterli- 4.7
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Approx. 18 hours to complete
By reworking the principles of electronics, telecommunication and computer science into a unifying paradigm, DSP is a the heart of the digital revolution that brought us CDs, DVDs, MP3 players, mobile phones and countless other devices....
Digital Signal Processing 4: Applications
by Paolo Prandoni , Martin Vetterli- 0.0
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Approx. 14 hours to complete
By reworking the principles of electronics, telecommunication and computer science into a unifying paradigm, DSP is a the heart of the digital revolution that brought us CDs, DVDs, MP3 players, mobile phones and countless other devices....
Principles of Computing (Part 2)
by Scott Rixner , Joe Warren , Luay Nakhleh- 4.8
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Approx. 16 hours to complete
This two-part course introduces the basic mathematical and programming principles that underlie much of Computer Science. Understanding these principles is crucial to the process of creating efficient and well-structured solutions for computational problems. To get hands-on experience working with these concepts, we will use the Python programming language. Searching and Data Structures...
Digital Signal Processing 3: Analog vs Digital
by Paolo Prandoni , Martin Vetterli- 4.8
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Approx. 16 hours to complete
By reworking the principles of electronics, telecommunication and computer science into a unifying paradigm, DSP is a the heart of the digital revolution that brought us CDs, DVDs, MP3 players, mobile phones and countless other devices....
Computational Thinking for K-12 Educators: Abstraction, Methods, and Lists
by Beth Simon- 0.0
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Approx. 9 hours to complete
Culturally Responsive Teaching & Computer Science Classrooms...
Fitting Statistical Models to Data with Python
by Brenda Gunderson , Brady T. West , Kerby Shedden- 4.4
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Approx. 15 hours to complete
In this course, we will expand our exploration of statistical inference techniques by focusing on the science and art of fitting statistical models to data....
Causal Inference
by Michael E. Sobel- 3.3
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Approx. 12 hours to complete
This course offers a rigorous mathematical survey of causal inference at the Master’s level. Inferences about causation are of great importance in science, medicine, policy, and business. We will study methods for collecting data to estimate causal relationships. Students will learn how to distinguish between relationships that are causal and non-causal; this is not always obvious....
Дискретная математика: подсчеты, графы, случайные блуждания
by Владимир Подольский- 0.0
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Approx. 37 hours to complete
Основная цель курса — дать введение в разделы дискретной математики, важные для анализа данных. Мы начнем с краткого введения в комбинаторику, раздел математики, изучающий подсчеты. Основы комбинаторики критически важны для всех, кто работает в анализе данных или в Computer Science. После этого мы используем наши знания в комбинаторике в изучении дискретной вероятности....
First Steps in Linear Algebra for Machine Learning
by Dmitri Piontkovski , Vsevolod L. Chernyshev- 4.1
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Approx. 21 hours to complete
This Course is part of HSE University Master of Data Science degree program....
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