Tags:
Data science is increasingly becoming an integral part of our daily lives from recommender systems to speech recognition, generation and self driving cars. This course offers a gentle technical introduction to data science using Python and discusses the most popular entry level machine learning algorithms for different problem spaces. By the end of the course students will have a fundamental understanding of what it means for a machine to “learn” and how different data problems can be investigated, modeled, and solved.
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LevelIntermediate
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Duration2 hours
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Last UpdatedMarch 20, 2024
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CertificateCertificate of completion
What I will learn?
- Data Science
- Supervised Learning Algorithms
- Unsupervised Learning Algorithms
- GPU & Distributed Computing
Course Curriculum
What is Data Science and Machine Learning?
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What is Data Science and Machine Learning?
16:54 -
What is Data Science and Machine Learning? Readings
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What is Data Science and Machine Learning?
What Does it Mean for a Machine to “Learn”?
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What Does it Mean for a Machine to “Learn”?
20:31 -
What Does it Mean for a Machine to “Learn”? Readings
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What Does it Mean for a Machine to “Learn”? Quiz
Basic Supervised Learning
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Basic Supervised Learning
13:12 -
Basic Supervised Learning Readings
Basic Unsupervised Learning
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Basic Unsupervised Learning
14:20 -
Basic Unsupervised Learning Readings
Data is Everything
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Data is Everything
17:20 -
Data is Everything Readings
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Data is Everything Quiz
GPU & Distributed Computing
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GPU & Distributed Computing
09:34 -
GPU & Distributed Computing Readings
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GPU & Distributed Computing Quiz
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Description
Data science is increasingly becoming an integral part of our daily lives from recommender systems to speech recognition, generation and self driving cars. This course offers a gentle technical introduction to data science using Python and discusses the most popular entry level machine learning algorithms for different problem spaces. By the end of the course students will have a fundamental understanding of what it means for a machine to “learn” and how different data problems can be investigated, modeled, and solved.