10 Jupyter Notebook Frameworks in 10 Days (Kaggle, etc)

This original high-quality hands-on course will help you understand the basics of experimenting with Jupyter notebooks. You'll learn about the history behind Jupyter Notebook, and all modern products today which are in fact based on this free and open-source project. I'll introduce you to at least 10 different applications, and help you move further, if you want to become indeed an expert in any of them.

The 10 Jupyter-based Frameworks

• Jupyter Notebook - the free open-source project based on IPython that started all.

• Project Jupyter - an ecosystem of other free open-source applications around Jupyter Notebook, including JupyterLab.

• Anaconda Cloud - a free cloud-based solution based on JupyterLab.

• Amazon Studio Lab - a free GPU-based cloud-hosted solution, as an alternative to the commercial but famous SageMaker.

• Google Colab - another practical alternative, with free GPU offerings, from Google.

• Kaggle - the one-stop social network for Data Science competitions.

• Hex - the most modern and classy web UI from all Jupyter-based products today.

• Deepnote - another interesting third-party hosted solution of no-code widgets in Jupyter notebooks.

• JetBrains Datalore - a practical notebook-based cloud environment from the company behind ReSharper and PyCharm.

• Snowflake Notebooks - when code must be executed closer to where your big data is stored.

A last chapter will offer you a quick bootcamp in the Markdown language. And along the way you'll be exposed to the history behind Jupyter, as well as dozens of other notebook-based products that didn't make the cut.

Who Am I

• Experienced Cloud Solutions Architect and Database expert.

• Over three decades of professional experience, as both a full-time employee and independent contractor.

• Snowflake world-class expert, former Snowflake "Data Superhero" and SnowPro Certification SME.

• I passed over 40 certification exams in 2-3 years alone, all from the first attempt.

• Over 20 certifications in AWS, Azure and GCP.

• Almost 20 certifications in Data Science and Machine Learning.

• Over a dozen of certifications in Data Analytics and Big Data.

Learning Jupyter notebooks may seem easy. And you will need to learn about them, make no mistake. However, today it became truly difficult to keep up with all sorts of advanced and modern frameworks using notebooks. They come up with many data integrations, no-code widgets, application builders, artificial intelligence assistants and other advanced features.

Allow me to help you out with this domain, to acquire basic and intermediate knowledge in this area in no time.