Learning Path: Jupyter: Interactive Computing with Jupyter

Learning Path: Jupyter: Interactive Computing with Jupyter, available at $19.99, has an average rating of 3.4, with 57 lectures, based on 37 reviews, and has 294 subscribers.

You will learn about Install and run the Jupyter Notebook system on your machine Implement programming languages such as R, Python, Julia, and JavaScript with the Jupyter Notebook Use interactive widgets to manipulate and visualize data in real time Share your Notebook with colleagues Invite your colleagues to work with you in the same Notebook Perform scientific application development by leveraging Big Data tools such as Spark This course is ideal for individuals who are This Learning Path caters to all developers, students, and educators who want to execute code, see the output, and comment all in the same document, the browser or Data science professionals will also find this Learning Path very useful in performing technical and scientific computing in a graphical, agile manner It is particularly useful for This Learning Path caters to all developers, students, and educators who want to execute code, see the output, and comment all in the same document, the browser or Data science professionals will also find this Learning Path very useful in performing technical and scientific computing in a graphical, agile manner.

Enroll now: Learning Path: Jupyter: Interactive Computing with Jupyter

Summary

Title: Learning Path: Jupyter: Interactive Computing with Jupyter

Price: $19.99

Average Rating: 3.4

Number of Lectures: 57

Number of Published Lectures: 57

Number of Curriculum Items: 57

Number of Published Curriculum Objects: 57

Original Price: $199.99

Quality Status: approved

Status: Live

What You Will Learn

Install and run the Jupyter Notebook system on your machine
Implement programming languages such as R, Python, Julia, and JavaScript with the Jupyter Notebook
Use interactive widgets to manipulate and visualize data in real time
Share your Notebook with colleagues
Invite your colleagues to work with you in the same Notebook
Perform scientific application development by leveraging Big Data tools such as Spark

Who Should Attend

This Learning Path caters to all developers, students, and educators who want to execute code, see the output, and comment all in the same document, the browser
Data science professionals will also find this Learning Path very useful in performing technical and scientific computing in a graphical, agile manner

Target Audiences

This Learning Path caters to all developers, students, and educators who want to execute code, see the output, and comment all in the same document, the browser
Data science professionals will also find this Learning Path very useful in performing technical and scientific computing in a graphical, agile manner

Are you looking forward to write, execute, and comment your live code and formulae all under one roof? Or do you want an application that will let you forget your worries in scientific application development? If yes, then this Learning Path will surely help you out by provide all that you need to know to work with the Jupyter Notebook — a console-based approach to interactive computing!�

Packt’s Video Learning Paths are a series of individual video products put together in a logical and stepwise manner such that each video builds on the skills learned in the video before it.

The Jupyter Notebook is an open-source web application that supports more than 40 programming languages including those popular in data science such as Python, R, Julia, and Scala. This Learning Path is a one-stop solution for all you want to know about the Jupyter Notebook. It will teach you everything you need to know to perform scientific computation with ease.�

This Learning Path starts with a brief introduction to Jupyter Notebook and its installation in different environments. Next, you will see how to integrate the Jupyter system with different programming languages such as R, Python, JavaScript, and Julia. Moving ahead, you will master interactive widgets, namespaces, and working with Jupyter in the multiuser mode. You will also see how to share your Notebook with colleagues. Finally, you will learn to access Big Data using Jupyter.�

By the end of the Learning Path, you will be able to write code, compute mathematical formulae, create graphics, and view the output, all in a single document and web browser, using the Jupyter Notebook.

About the Author:

For this course, we have combined the best works of this esteemed author:

Dan Toomey has been developing applications for over 20 years. He has worked in a variety of industries and companies in roles from the sole contributor to VP/CTO level. For the last 10 years or so, he has been contracting to companies in the eastern Massachusetts area. Dan has been contracting under Dan Toomey Software Corporation again as a contractor developer in the area.

Course Curriculum

Chapter 1: Jupyter Notebook for All – Part I

Lecture 1: The Course Overview

Lecture 2: First Look at Jupyter

Lecture 3: Installing Jupyter on Windows

Lecture 4: Installing Jupyter on Mac

Lecture 5: Notebook Structure, Workflow, andBasic Operations

Lecture 6: Security and Configuration Operations in Jupyter

Lecture 7: Basic Python in Jupyter

Lecture 8: Python Data Access in Jupyter

Lecture 9: Python pandas in Jupyter

Lecture 10: Python Graphics in Jupyter

Lecture 11: Python Random Numbers in Jupyter

Lecture 12: Adding R Scripting to Your Installation

Lecture 13: Basic R in Jupyter

Lecture 14: R Dataset Access and Visualization in Jupyter

Lecture 15: R Cluster Analysis and Forecasting

Lecture 16: Adding Julia Scripting to Your Installation

Lecture 17: Basic Julia in Jupyter

Lecture 18: Julia Limitations and Standard Capabilities

Lecture 19: Julia Visualizations in Jupyter

Lecture 20: Julia Vega Plotting and Parallel Processing

Lecture 21: Julia Control Flow, Regular Expressions, and Unit Testing

Lecture 22: Adding JavaScript Scripting to Your Installation

Lecture 23: JavaScript Hello World Jupyter Notebook

Lecture 24: Basic JavaScript in Jupyter

Lecture 25: Node.js stats-analysis Package and JSON Handling

Lecture 26: Node.js plotly Package

Lecture 27: Node.js Asynchronous Threads

Lecture 28: Node.js decision-tree Package

Chapter 2: Jupyter Notebook for All – Part II

Lecture 1: The Course Overview

Lecture 2: Installing Widgets and Widget Basics

Lecture 3: Interact Widget

Lecture 4: Interactive Widget

Lecture 5: Widgets

Lecture 6: Widget Properties

Lecture 7: Sharing Notebooks on a Notebook

Lecture 8: Sharing Notebooks on a Web Server and Docker

Lecture 9: Sharing Notebooks on a Public Server

Lecture 10: Converting Notebooks

Lecture 11: Sample Interactive Notebook

Lecture 12: JupyterHub

Lecture 13: JupyterHub – Operation

Lecture 14: Docker and Its Installation

Lecture 15: Building Your JupyterImage for Docker

Lecture 16: Installing the Scala Kernel

Lecture 17: Scala Data Access in Jupyter

Lecture 18: Scala Array Operations

Lecture 19: Scala Random Numbers in Jupyter

Lecture 20: Scala Closures andHigher Order Definitions

Lecture 21: Scala Pattern Matching andCase Classes

Lecture 22: Scala Immutability

Lecture 23: Scala Collections and Named Arguments

Lecture 24: Scala Traits

Lecture 25: Apache Spark

Lecture 26: Our First Spark Script and Word Count

Lecture 27: Estimate Pi andLog File Examination

Lecture 28: Spark Primes andText File Analysis

Lecture 29: Spark – Evaluating History Data

Instructors

Packt Publishing
Tech Knowledge in Motion

Rating Distribution

1 stars: 2 votes
2 stars: 4 votes
3 stars: 11 votes
4 stars: 12 votes
5 stars: 8 votes

Frequently Asked Questions

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You can view and review the lecture materials indefinitely, like an on-demand channel.

Can I take my courses with me wherever I go?

Definitely! If you have an internet connection, courses on Udemy are available on any device at any time. If you don’t have an internet connection, some instructors also let their students download course lectures. That’s up to the instructor though, so make sure you get on their good side!

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