Getting Started with Data Science – Jupyter, R on Windows Machine

Whether you're a student, professional, or enthusiast interested in entering the field of data science, this course provides a comprehensive introduction to Jupyter, R, and the foundational principles of data science.

Intermediate
Lab Description

The "Getting started with Data Science - Jupyter, R on Windows Machine" course is a comprehensive program designed to equip participants with the fundamental knowledge and practical skills to begin their journey in data science using Jupyter notebooks and the R programming language on a Windows machine.

Pre-requisite

Getting started with Data Science - Jupyter, R on Windows Machine lab is suitable for beginners and individuals with some programming experience who are interested in exploring the field of data science.

Learning objective

Throughout the lab, participants will dive into the essential concepts and techniques of data science. They will learn how to effectively use Jupyter notebooks as a powerful tool for data manipulation, analysis, and visualization. Participants will gain proficiency in writing R code and leveraging the rich ecosystem of R packages to perform various data science tasks.
The lab will cover a wide range of topics, including data preprocessing, exploratory data analysis, statistical analysis, machine learning, and data visualization. Participants will learn how to clean and transform data, perform descriptive and inferential statistics, build predictive models, and visualize data using popular R libraries such as ggplot2 and dplyr.

Lab Exercises
Getting started with the Lab Environment
Log in to JupyterLab Portal
Execute Jupyter Notebooks with Python
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FAQ's

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.

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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.

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This Hands-on lab Includes
Getting Started with Data Science - Jupyter, R on Windows Machine
Azure
01 Day
03 Exercises
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