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[title] => Data Science with R: Data Analysis and Visualization
[excerpt] => This course is a 35-hour program designed to provide a comprehensive introduction to R. You’ll learn how to load, save, and transform data as well as how to write functions, generate graphs, and fit basic statistical models with data. In addition to a theoretical framework in which you will learn the process of data analysis, this course focuses on the practical tools needed in data analysis and visualization. By the end of the course, you will have mastered the essential skills of processing, manipulating and analyzing data of various types, creating advanced visualizations, generating reports, and documenting your codes.
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[title] => Data Science with Python: Machine Learning
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[title] => Data Science with Python: Data Analysis and Visualization
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[title] => Introductory Python
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[title] => Designing and Implementing Production Machine Learning Systems (MLOps)
[excerpt] => This course is an introduction to ML systems in production that will demonstrate and give students exposure to how real production ML systems operate. Using Python, Docker, Kubernetes, Google Cloud and various open-source tools, students will bring the different components of an ML system to life and setup real, automated infrastructure.
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[title] => Data Science with R: Data Analysis and Visualization
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[title] => Data Science with Python: Machine Learning
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[title] => Data Science with Python: Data Analysis and Visualization
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[title] => Introductory Python
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[title] => Data Science with R: Data Analysis and Visualization
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[title] => Data Science with Python: Machine Learning
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[title] => Data Science with Python: Data Analysis and Visualization
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