Jupyter Notebooks and iPython for Data Science

Jupyter Notebooks and iPython for Data Science

Jupyter Notebooks and iPython for Data Science

Learn Jupyter Notebook and iPython and its use in cloud computing, deploying graphs and Data Science

Language: english

Note: 0/5 (0 notes) 381 students  New course 

Instructor(s): EDUCBA Bridging the Gap

Last update: None

What you’ll learn

  • In this IPython/Jupyter Notebook Course, we have tried to cover all the topics that fall under Jupyter and iPython
  • After finishing this course, you will be able to use the Jupyter environment very efficiently.
  • Learn how to bring python in use when it comes to developing the complex application that demands high computing power or needs some complex functionality
  • You will be able to solve the real-life problems that need an application for a solution.

 

Requirements

  • There are some of the technologies that you should be aware of to learn this Jupyter Notebook Course in the best way. As there is an immense use of python required while working with this tool, you will be supposed to have an idea about the python fundamentals. If you have hands-on experience in python, you will find it very easy to learn this. But in case if you are new to python, it is recommended that you should go through python before jumping to this IPython course. The next important thing is, you should be flexible to learn different tools. It usually happens that once we make ourselves comfortable using one tool, we find it tough to switch to the next. You should be able to be flexible in this can and have to be ready to explore this tool in-depth as every function of this tool has been introduced to help in some way. There are two important things that you should be aware of so that you can find it easy to learn this Jupyter Notebook Course.

 

Description

The first IPython/Jupyter Notebook Course is going to be a six hours continuous tutorial that has been introduced to help you in getting started with Jupyter-iPython. At the beginning, of the course, you will get a brief introduction to IPython and Jupyter. We have tried to cover every topic with some real-life or actual scenarios to make you understand things much better. After the introduction part, you will be learning about the requirement and implementation of Jupyter and iPython. Later on, we have included some best examples to show you how things work. The video will make you aware of the Jupyter environment so that you can understand things when the educator will show you how to work on this tool. We have captured the screen and shown things practically just to ensure that you are getting an in-depth idea about the tool as you will be supposed to be familiar with this tool by the end of this unit.

IPython and Jupyter collectively can be defined as the development environment that facilitates the efficient development of the application. The iPython is an interactive shell that lets the different languages interact with it and make the programming a bit easier and convenient. The Jupyter environment provides the best way to perform highly complex computations, can be used for graphical representation of data, and much more. It is mainly used in the development environment to develop an enterprise application. It also provides pre-defined functionalities that can help the program to be developed in a very short period. Though it reduces the load of too much manual coding, it is a bit complex to use but its outcome is very fruitful and it also helps the development team to save a lot of time. In the currently implemented framework called agile which demands the completion of work in very less time, it can be proved very much useful.

In this IPython/Jupyter Notebook Course, we have tried to cover all the topics that fall under Jupyter and iPython. Which means that it welcomes all kinds of an audience to enhance their skills. After finishing this course, you will be able to use the Jupyter environment very efficiently. You will be able to contribute to the development and will learn how to develop a program in less time. You will be learning how to use python or how to bring python in use when it comes to developing the complex application that demands high computing power or needs some complex functionality to be added to it. As the iPython has been developed by the Python programming language, you will also get an efficient exposure to python. You will be able to solve the real-life problems that need an application for a solution. One will also learn how to deploy this tool in the real work environment so that it could be leveraged to solve problems in the organization.

 

Who this course is for

  • This Jupyter Notebook course mainly focuses on working professionals, students, and trainers. There are several IT professional who is either looking to change their stream or to learn deep in their stream. This Jupyter Notebook Course suits them perfectly. The folks who are already working in Python and want to learn about this tool so that they can sever their organization well, can opt for this course. The students who are having studies at an advanced level and need something to deliver can choose this Jupyter Notebook Course to improve their development approach. It will not only enhance their skills but will also keep them on highlight when it comes to the list of best developers. The trainer can also choose this Jupyter Notebook Course to enlarge the domain of their training. It will help them attract more trannies who are looking to get trained in this tool.

 

Course content

  • Introduction
    • Introduction Jupyter or IPython Notebook
  • Environment
    • Environment Setup
  • Installation and Configuring
    • Installation of Ipython Notebook
    • Configuring Jupyter Notebook
  • Notebook Walkthrough
    • IPython Notebook
    • More on IPython Notebook
    • Simple Arithmetic Calculations
    • Working on Arithmetic Calculation Continues
    • Basic Definitions
    • Markdown Cells
    • Matplot Library
  • Plotting Graphs
    • Line Plots
    • Scatter Plots
    • Histograms
    • Writing Plots to File
    • Numpy Arange
    • Numpy Arange Continues
    • Numpy Arrays
    • A Complete Graph
  • Advanced Charts
    • Color Control
    • Formatting Markers
    • Histograms in Detail
    • Histograms in Detail Continues
    • Bar Charts
    • Pie Charts
    • Scatter Charts
    • Polar Charts
    • Annotations and Texts
    • Decorating Arrows
  • Advanced Matplotlib with Jupyter
    • Ipython Pylab
    • PLotting Multiple Axes
    • Logarithmic Axes
    • Shared Axes
    • Date Formatting with Matplotlib
    • Date Formatting with Matplotlib Continues
    • Date and Days Formatting
    • Mathtext Module
    • LaTex Renderers
    • Contour Plotting
    • Image Plotting

 

Jupyter Notebooks and iPython for Data Science

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