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What you'll learn?
- Install Python, setup windows new terminal, install Jupyter notebook and create Jupyter notebook, create working directory and access it from the terminal
- Create, display and run .py file, run external IPython files, formating text with Markdown and HTML， run R and Javascript in Jupyter notebook
- Create, insert equations, embed images, audios and videos into Jupyter notebook and align them in Jupyter notebook
- Change themes, use widely used shortcuts, smart code completion plugin, multi-line cursors, popular magic commands , install packages directly in Jupyter notebook
- Create basic plots, interactive plots and interactive plot widget in Jupyter notebook
- Create a content table for a single or multiple notebooks, and convert notebook to a instant and live slideshow and a standalone web application
- Solve unavailable problem of Built-in terminal of Jupyter notebook on Windows, Solve problem of R unable to install packages on onedrive on Widows
Course Overview
This course consists of 7 sections, including 30 lectures, which cover the core of the Jupyter Notebook from the basic concepts, operations to detailed applications. It includes
(1) install Python, setup windows new terminal, install Jupyter notebook and create Jupyter notebook, create working directory and access it from Windows terminal;
(2) create, display and run .py file, run external IPython files, formating text with Markdown and HTML in Jupyter notebook;
(3) create tables, insert equations, embed images, audios and videos into Jupyter notebook and align them using Markdown, HTML, Magics, IPython functions, etc.
(4) change themes, use widely used shortcuts, smart code completion plugin, multi-line cursors, popular magic commands , install packages directly in Jupyter notebook, as well as use the built-in terminal;
(5) create basic plotting, interactive plotting and Interactive plot widget in Jupyter notebook;
(6) make a content table for an inside Jupyter notebook and for multiple notebooks , convert notebook to a presentation slideshow, and transfer a notebook to a web application.
This course uses practical examples to help you understand and grasp the Jupyter Notebook from a beginner to an expert in an easy and quick way. This one course is enough for you to grasp almost all aspect of the Jupyter notebook
Pre-requisites
- Basic knowledge of Python, or other programming knowledge would be advantage to grasp the skills more quickly.
Target Audience
- Programmers, business analysts, data analysts, statisticians, and data scientists, who want to learn how to use Jupyter notebook for code writing, data analysis and machine learning
- It is also helpful to students and academic faculties, who are learning and teaching Python, data analysis and modelling, and machine learning.
- But it can be for anyone who loves Python and Jupyter notebook for his/her projects.
Curriculum 30 Lectures 02:31:36
-
Section 1 : Introduction
- Lecture 2 :
- How to Use and Download the Notebook Files
-
Section 2 : Setting Up Development Environment
- Lecture 1 :
- Installing Python
- Lecture 2 :
- Setting up Windows Terminal
- Lecture 3 :
- installing Jupyter Notebook
- Lecture 4 :
- Starting Jupyter Notebook App
- Lecture 5 :
- Creating Working Directory
- Lecture 6 :
- Creating a Jupyter Notebook
-
Section 3 : Basic Application
- Lecture 1 :
- Python Programming
- Lecture 2 :
- Text Formation with Markdown
- Lecture 3 :
- Creating Table
- Lecture 4 :
- Inserting Math Equations and Symbols
- Lecture 5 :
- Embedding Images
- Lecture 6 :
- Embedding Audios and Videos
- Lecture 7 :
- Text Formation with HTML
- Lecture 8 :
- Running Other Programming Languages
-
Section 4 : Advanced Features
- Lecture 1 :
- Change Themes
- Lecture 2 :
- Multi-line Cursor
- Lecture 3 :
- Frequently Used Shortcuts
- Lecture 4 :
- Smart Code Auto-Completion
- Lecture 5 :
- Magic Commands and Alternatives
- Lecture 6 :
- Buit-in Terminal
-
Section 5 : Data Visualization
- Lecture 1 :
- Basic Plots
- Lecture 2 :
- Interactive Plots
- Lecture 3 :
- Interactive Plot Widgets
-
Section 6 : Notebooks Organizing and Displaying
- Lecture 1 :
- Creating Table of Content
- Lecture 2 :
- Coverting Notebook into Live Slideshow
- Lecture 3 :
- Converting Notebook into Standalone Web Application
-
Section 7 : Appendix
- Lecture 1 :
- How to Solve Unavailable Built-in Terminal Problem on Windows
- Lecture 2 :
- How to Solve Problem of R Unabling to Install Packages in Onedrive on Windows
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Instructor
9737 Course Views
1 Courses
Professor Dr. Shouke Wei. Nearly 20 years of teaching and research experience and 10 years of entrepreneur and management experience in computer modelling and simulation, big data analysis, machine learning algorithms; Ph.D. in Environment and Resource Management; Postdoctoral scientist, and Ph.D. supervisor in Environmental System Modelling; Research associate and Visiting scientist in Forest Hydrological Ecosystem Modelling; Industrial Professor, Adjunct Professor teaching AI and machine learning courses and Postgraduate supervisor in Deep reinforcement learning and Computer vision; Senior Research in R&D of real time monitoring and early warning system platform for water protection, human safety and health; Participated in or hodeling 12 international research projects; Participated as an invited key speaker in 12 scientific conferences and workshops; Having 27 software copyrights, 4 patents and over 40 pulications.
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