Data Science: Productivity Tools Training

Live Online & Classroom Enterprise Training

Data Science: Productivity Tools focuses on tools and practices that improve efficiency in data science workflows. It includes version control (Git), coding environments, documentation, and collaboration techniques.

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What is Data Science: Productivity Tools Training about?

This course introduces the core productivity tools every data scientist should master to work efficiently and collaborate effectively. From using the command line to navigate and manage files, to leveraging Git and GitHub for version control, learners will gain practical skills to manage projects, track changes, and collaborate in teams. By the end of the course, participants will be equipped with the tools that underpin modern data science workflows, making them more productive and job-ready.

What are the objectives of Data Science: Productivity Tools Training ?

Understand the role of productivity tools in data science workflows.
Use the command line for file management and automation.
Apply Git for version control and project tracking.
Collaborate with peers using GitHub repositories.
Integrate productivity tools into real-world data science projects.

Who is Data Science: Productivity Tools Training for?

Aspiring data scientists starting their career journey.
Students and researchers managing data-driven projects.
Professionals seeking to collaborate effectively in data teams.
Analysts and engineers aiming to adopt best practices in version control.
Anyone pursuing a complete data science learning path.

What are the prerequisites for Data Science: Productivity Tools Training?

Prerequisites:

Basic understanding of data science concepts.
Familiarity with Python or R (recommended, not mandatory).
Willingness to work with the command line.
An interest in collaborative and team-based projects.
Curiosity about improving efficiency in project workflows.

Learning Path:

Introduction to Productivity Tools in Data Science
Navigating the Command Line for Data Projects
Version Control with Git: Basics to Advanced
Collaborating and Sharing Projects on GitHub
Applying Tools in End-to-End Data Science Projects

Related Courses:

Introduction to Data Science with Python
Data Science Research Methods (Python/R Edition)
Reproducible Research for Data Science
Data Engineering Fundamentals

Available Training Modes

Live Online Training

3 Days

Course Outline Expand All

Expand All

Module 1- Installing Software

Installing R and RStudio

Introduction to RStudio

Introduction to Git and GitHub

Module 2- Basic Unix

Introduction to Unix

Working with Unix

Module 3- Reproducible Reports

Reproducible Reports with R Markdown

R Markdown

knitr

Module 4- Git and GitHub

Git and GitHub

Using Git at the Command Line

Creating a GitHub Repository

Module 5- Advanced Unix

Arguments

Getting Help and Pipes

Wild cards

Environment Variables and Shells

Executables, Permissions, and File Types

Commands You Should Learn

Who is the instructor for this training?

The trainer for this Data Science: Productivity Tools Training has extensive experience in this domain, including years of experience training & mentoring professionals.

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