Description
Jupyter Notebook for Data Science, the Jupyter Notebook for Data Science training course is published by Udemy Academy. This course will help you get familiar with Jupyter Notebook and all its features for performing various data science tasks in Python. Jupyter Notebook is a powerful tool for interactive data exploration and visualization and has become a standard tool among data scientists. In this course, we’ll start with the basics of data analysis in Jupyter Notebook and then move on to learn some common scientific Python tools like Pandas, Matplotlib, and Python. We will work with real data sets such as crime and traffic accidents in New York City to explore common issues such as data cleansing and scraping. We will create rich visualizations that represent temporal and spatial data.
By the end of the course, you will be able to easily work with a new dataset, clean it, review and analyze it in Jupyter Notebook to extract useful information in the form of interactive reports and dense data visualizations of information. Madras is a developer, data analyst and founder of Punk Rock Dev, an indie web development studio. Since 2009, he has been professionally building web applications and performing data analysis in Python, JavaScript and other technologies. In the past, the lecturer worked as a research assistant and has a PhD in computer science at the Vienna University of Technology. There he studied the energy efficiency of geographically distributed data centers and worked on optimizing VM scheduling based on real electricity prices and weather conditions.
What you will learn
- You will learn how to effectively use Jupyter Notebook to manipulate and visualize data
- Performing interactive data analysis and visualization using Jupyter Notebook on real data
- Time series data analysis using Pandas
- Create interactive widgets where non-technical users can participate in data review using the notebooks you create.
- Prepare websites to build datasets and deal with common challenges such as unstructured or missing data.
- Combine different data sets into a single graph so people can visually compare them and gain new insights.
- Analyze and visualize geographic datasets to create stunning information-rich maps
Who is this course suitable for?
- This course is for developers who have a basic understanding of Python and Jupyter Notebook.
Jupyter Notebook for Data Science course specifications
- Publisher: Udemy
- teacher : Pact Publishing
- English language
- Education level: Intermediate
- Number of courses: 20
- Training duration: 3 hours and 11 minutes
Chapters of the Jupyter Notebook for Data Science course
Course prerequisites
- Basic understanding of Python and Jupyter Notebook is required. A basic understanding of math and statistics will come in handy.
Pictures
Sample video
Installation guide
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Quality: 720p
download link
File(s) password: www.downloadly.ir
Size
825 MB
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