English | MP4 | AVC 1920×1080 | AAC 48KHz 2ch | 3h 11m | 826 MB
The easier way to do data science.
This video course will help you get familiar with Jupyter Notebook and all of its features to perform various data science tasks in Python. Jupyter Notebook is a powerful tool for interactive data exploration and visualization and has become the standard tool among data scientists. In the course, we will start from basic data analysis tasks in Jupyter Notebook and work our way up to learn some common scientific Python tools such as pandas, matplotlib, and plotly. We will work with real datasets, such as crime and traffic accidents in New York City, to explore common issues such as data scraping and cleaning. We will create insightful visualizations, showing time-stamped and spatial data.
By the end of the course, you will feel confident about approaching a new dataset, cleaning it up, exploring it, and analyzing it in Jupyter Notebook to extract useful information in the form of interactive reports and information-dense data visualizations.
In this course you won’t just work with sterile Hello world examples; instead, we’ll analyze real datasets available online. This way, you will learn how to deal with typical problems that pop up in daily data science work.
What You Will Learn
- Learn how to efficiently use Jupyter Notebook for data manipulation and visualisation
- Perform interactive data analysis and visualisation using Jupyter Notebook on real data
- Analyse time series data using Pandas
- Create interactive widgets where non-technical users can also get involved in the data exploration using the notebooks you create
- Scrape websites to build datasets and deal with common challenges like unstructured or missing data
- Combine different datasets in a single graph to enable people to compare them visually and gain new insights
- Analyse and visualise geographic datasets to create stunning information-rich maps
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