Course Information
Registration period
Year-round Recruitment
Course Level
Study Mode
Duration
3 Hour(s) 11 Minute(s)
Language
English
Taught by
Packt Publishing
Rating
2 views
Course Overview
Collaborate, create interactive visualizations, and manipulate big data in the language of your choice.
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.
This course uses Jupyter 5.4.1, while not the latest version available, it provides relevant and informative content for data science enthusiasts.
About the Author
Dražen Lucanin is a developer, data analyst, and the founder of Punk Rock Dev, an indie web development studio. He's been building web applications and doing data analysis in Python, JavaScript, and other technologies professionally since 2009. In the past, Dražen worked as a research assistant and did a PhD in computer science at the Vienna University of Technology. There he studied the energy efficiency of geographically distributed datacenters and worked on optimizing VM scheduling based on real-time electricity prices and weather conditions. He also worked as an external associate at the Ruder Boškovic Institute, researching machine learning methods for forecasting financial crises. During Dražen's scientific work Python, Jupyter Notebook (back then still IPython Notebook), Matplotlib, and Pandas were his best friends over many nights of interactive manipulation of all sorts of time series and spatial data. Dražen also did a Master's degree in computer science at the University of Zagreb.
Course Content
- 5 section(s)
- 20 lecture(s)
- Section 1 Jupyter Notebook Introduction
- Section 2 Data Analysis Using Pandas
- Section 3 Scraping Data
- Section 4 Advanced Visualization
- Section 5 Analyzing Geographic Data
What You’ll 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
Skills covered in this course
Reviews
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AAndrei
This is so old, that I had a lot of trouble setting everything up. Nice course, clear videos, Instructor was good -- Udemy should not offer courses with archaic software that is deprecated and impossible to set up, as a beginner. Not helpful if I cannot work through the exercises, Youtube is free. REST API do not work, Jupyter libraries no longer work, etc etc etc
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NNatascha Martinez
Buen contenido, alta concentración de detalle en el mismo, requiere hacerlo con dedicación y observar los comandos estando atento a las explicaciones
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GGeorge Spahl
Great instructor, interesting material.
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AAudrey Rager
Good overview of Jupyter Notebooks. I learned some things about Jupyter Notebooks that will be helpful. Also a good review off Pandas and some other data science tools.
