Search result for Master of science in computer engineering Online Courses & Certifications
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Introduction to Genomic Technologies
by Steven Salzberg, PhD , Jeff Leek, PhD- 4.6
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Approx. 6 hours to complete
You'll also get an introduction to the key concepts in computing and data science that you'll need to understand how data from next-generation sequencing experiments are generated and analyzed. This is the first course in the Genomic Data Science Specialization. Applications of Sequencing What Is Computer Science? Software Engineering Data Science Technology...
Fatigue Failure in Different Fields of Engineering
by Kazem Reza Kashyzadeh- 0.0
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Approx. 23 hours to complete
In recent years, owing to global competition and greater need of customers for safety, durability, and reliability of products, there has been a considerable tendency to improve quality in various industries. Introduction to Fatigue Failures in Different Fields of Engineering Real examples of fatigue failure in various industries, including Mechanical engineering Real examples in various fields of engineering...
Teaching Impacts of Technology: Relationships
by Beth Simon- 0.0
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Approx. 11 hours to complete
Impacts (Keep me connected in a mobile society):, personal relationships, facebook, circle of friends In terms of CSTA K-12 computer science standards, we’ll primarily cover learning objectives within the “impacts of computing” concept, while also including some within the “networks and the Internet” concepts and the “data and analysis” concept. K-12 CSTA Computer Science Standards...
Convex Optimization
by Stephen Boyd , Henryk Blasinski- 0.0
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8 Weeks
Candidate in Computer Science at Stanford University. , summa cum laude, in Mathematics and Computer Science from the University of Pennsylvania and an M. in Computer Science from Stanford University. Ernest Ryu is a PhD candidate in Computational and Mathematical Engineering at Stanford University. Madeleine Udell is a PhD candidate in Computational and Mathematical Engineering at Stanford University....
Convex Optimization
by Stephen Boyd , Henryk Blasinski- 0.0
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8 Weeks
Candidate in Computer Science at Stanford University. , summa cum laude, in Mathematics and Computer Science from the University of Pennsylvania and an M. in Computer Science from Stanford University. Ernest Ryu is a PhD candidate in Computational and Mathematical Engineering at Stanford University. Madeleine Udell is a PhD candidate in Computational and Mathematical Engineering at Stanford University....
Machine Learning with Python: from Linear Models to Deep Learning
by Regina Barzilay , Tommi Jaakkola , Karene Chu- 0.0
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15 Weeks
You will complete this course and three others from MITx, at a similar pace and level of rigor as an on-campus course at MIT, and then take a virtually-proctored exam to earn your MicroMasters, an academic credential that will demonstrate your proficiency in data science or accelerate your path towards an MIT PhD or a Master's at other universities....
$300
LEARNING PATH: R: Advanced Deep Learning with R
by Packt Publishing- 3.3
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6.5 hours on-demand video
You’ll be able to master the intricacies of R deep learning packages such as TensorFlow. He is also the PhD students' representative at the Department of Computer Science of Engineering (DISI) and teaching assistant of the courses “Machine Learning” and “Computer Architectures” in the same department. He gained his second PhD in Engineering at the University of Warwick, UK....
$9.99
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Operations Research (1): Models and Applications
by 孔令傑 (Ling-Chieh Kung)- 4.8
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Approx. 11 hours to complete
Operations Research (OR) is a field in which people use mathematical and engineering methods to study optimization problems in Business and Management, Economics, Computer Science, Civil Engineering, Industrial Engineering, etc. This course introduces frameworks and ideas about various types of optimization problems in the business world. 2-2: Elements of a mathematical program (1)....
Learn to Program in Java
by Kasey Champion- 0.0
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4 Weeks
In this course, which was developed through a combination of academic and industry perspectives, learn not only how to code in Java but also how to break down problems and implement their solutions using some of the most fundamental computer science tools. Get plenty of hands-on Java coding experience with methods, logic, loops, variables, parameters, returns, and recursion....
$99
Compilers
by Alex Aiken- 0.0
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10 Weeks
COOL has the essential features of a realistic programming language, but is small and simple enough that it can be implemented in a few thousand lines of code. Designing and implementing a programming language turns out to be difficult; some of the best minds in computer science have thought about the problems involved and contributed beautiful and deep results....
$199
