Jupyter lab on Linux

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Hands-on Labs
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Jupyter lab on Linux<br></br>
Hands-on Labs

Jupyter lab on Linux

The "Jupyter Lab on Linux" hands-on lab is designed to provide participants with the knowledge and skills needed to effectively use Jupyter Lab in a Linux environment.
Lab Description

The "Jupyter Lab on Linux" hands-on lab is designed to provide participants with the knowledge and skills needed to effectively use Jupyter Lab in a Linux environment. This course is ideal for data scientists, analysts, and developers who work with Linux systems and want to leverage Jupyter Lab for their data analysis and exploration workflows.


To make the most of the "Jupyter Lab on Linux" hands-on lab, participants should have some prior knowledge and experience in the following areas: Linux Basics, Python Programming, Data Analysis Concepts, and Jupyter Lab Fundamentals.

Learning objective

In this hands-on lab, participants will also explore techniques for working with data in Jupyter Lab on Linux. They will learn how to import and export data, perform data cleaning and manipulation tasks using popular libraries like Pandas or NumPy, and visualize data using Matplotlib or other visualization libraries. Participants will gain insights into best practices for organizing and structuring their data analysis projects on Linux.

Lab Exercises
Getting started with the Lab Environment
Log in to JupyterLab Portal
Execute Jupyter Notebooks with Python
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A hands-on lab is a virtual environment where you can actively engage in practical exercises and simulations related to a specific subject or technology. It allows you to gain real-world experience and develop practical skills.

Upon enrolment, student will receive voucher code  and access instructions to launch the lab environment.

No, generally, MOC Hands-On Labs are designed to be completed in one continuous session. Once you start a lab, it's recommended to allocate enough time to finish it in one go.

Only a system with internet access and a compatible web browser.

Yes, CloudLabs Hands-on labs often come with built-in tracking and reporting features. These features allow you to monitor trainee progress, track completion rates, and generate reports on lab performance. This enables you to assess individual or group achievements and measure the effectiveness of your training initiatives.

CloudLabs have the SLA of 15 days to update the Labs.

Learners are typically allowed to access the lab once.

We have CloudLabs Shadow which is an embedded feature integrated into the CloudLabs platform that lets Instructors shadow the learners environment.

Cloud Labs support team is available 24/7 for 365 days over email and live chat.

  1. Email Support: labs-support@spektrasystems.com 
  2. Live Chat Support: https://cloudlabs.ai/labs-support  
This Hands-on lab includes
Jupyter lab on Linux<br></br>
01 Day
03 Exercises

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