Jupyter Notebooks

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Introduction to Statistics for Data Science using Python (edX)

Self Paced
Introduction to Statistics for Data Science using Python (edX)
Course Auditing
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This Statistics for Data Science course is designed to introduce you to the basic principles of statistical methods and procedures used for data analysis. This Statistics for Data Science course is designed to introduce you to the basic principles of statistical methods and procedures used for data analysis. After [...]
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Visualizing & Communicating Results in Python with Jupyter (Coursera)

Sep 20th 2021
Visualizing & Communicating Results in Python with Jupyter (Coursera)
Course Auditing
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Code and run your first Python program in minutes without installing anything! This course is designed for learners with limited coding experience, providing a foundation for presenting data using visualization tools in Jupyter Notebook. This course helps learners describe and make inferences from data, and better communicate and present [...]
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Tools for Data Science (Coursera)

What are some of the most popular data science tools, how do you use them, and what are their features? In this course, you'll learn about Jupyter Notebooks, RStudio IDE, Apache Zeppelin and Data Science Experience. You will learn about what each tool is used for, what programming languages [...]
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Julia Scientific Programming (Coursera)

This four-module course introduces users to Julia as a first language. Julia is a high-level, high-performance dynamic programming language developed specifically for scientific computing. This language will be particularly useful for applications in physics, chemistry, astronomy, engineering, data science, bioinformatics and many more. [...]
1
Average: 1 ( 3 votes )

Big Data Analytics Using Spark (edX)

Learn how to analyze large datasets using Jupyter notebooks, MapReduce and Spark as a platform. In data science, data is called “big” if it cannot fit into the memory of a single standard laptop or workstation. The analysis of big datasets requires using a cluster of tens, hundreds or [...]
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Python for Data Science (edX)

Learn to use powerful, open-source, Python tools, including Pandas, Git and Matplotlib, to manipulate, analyze, and visualize complex datasets. In the information age, data is all around us. Within this data are answers to compelling questions across many societal domains (politics, business, science, etc.). But if you had access [...]
9
Average: 9 ( 3 votes )

R Programming Basics for Data Science (edX)

Self Paced
R Programming Basics for Data Science (edX)
Course Auditing
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This course introduces you to R language fundamentals and covers common data structures, programming techniques, and how to manipulate data all with the help of the R programming language. The R language plays a critical role in data analysis and a common programming language when working in the field [...]
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Data Science Tools (edX)

Self Paced
Data Science Tools (edX)
Course Auditing
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Learn about the most popular data science tools, including how to use them and what their features are. In this course, you'll learn about Data Science tools like Jupyter Notebooks, RStudio IDE, and Watson Studio. You will learn what each tool is used for, what programming languages they can [...]
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Getting Started with Jupyter Notebook (Manning Publications)

In this liveProject, you’ll get hands-on experience using Jupyter Notebook in a real-world data science project. You’ll train a simple KNN classifier and use Jupyter, IPython, and the easy-to-use Markdown markup language to document and share your work. Your challenges will include customizing your notebooks, incorporating your notebooks into [...]
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Python for Data Engineering Project (edX)

Self Paced
Python for Data Engineering Project (edX)
Course Auditing
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An opportunity to apply your foundational Python skills via a project, using various techniques to collect and work with data. Journey into the realm of becoming a Data Engineer and apply your basic Python knowledge of working with data. You will exercise various techniques in Python to extract data [...]
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