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About This Course

Duration: 1 Full Day (8 Hours)
Delivery Mode: Classroom (In-Person)
Language: English
Credits: 8 PDUs / Training Hours
Certification: Course Completion Certificate
Refreshments: Lunch, snacks, and beverages provided

Course Overview

This 1 Day beginner-to-intermediate program introduces you to practical data analysis using R. The focus is on understanding how to structure data, clean it efficiently, explore patterns, generate insights, and apply analytical techniques using real datasets. Instead of covering deep programming or complex statistical theory, this workshop prioritizes applied analytics, reproducible workflows, and essential R techniques used in industry.

You will learn how analysts use R to transform messy data, explore relationships, summarize trends, and interpret insights clearly. Throughout the day, you’ll work through conceptual demonstrations, guided exercises, and scenario-based activities to gain a strong, hands-on understanding of R-powered data analysis.

Learning Objectives

By the end of the course, you will be able to:

Understand R workflows used for practical data analysis.
Import, clean, and manage datasets effectively.
Apply essential transformation techniques for analysis.
Explore data using structured EDA approaches.
Interpret simple visualizations created with R.
Identify patterns and generate insight-driven summaries.
Create a basic analysis plan using R-based workflows.

Target Audience

Data beginners moving toward analytical roles
Business analysts & reporting professionals
Students entering data analytics
Researchers working with small-to-medium datasets
Teams needing practical, non-technical analytics skills
Professionals who want to understand R at a functional level

📧 Contact us today to schedule a customized in-house session: info@mangates.com

Why Choose This Course?

This training focuses on practical R usage without overwhelming you with programming fundamentals or advanced statistics. The trainer brings experience in applied analytics, data preparation, exploratory analysis, and insight communication—ensuring the session remains hands-on, beginner-friendly, and industry-relevant. You leave with a clear understanding of how R supports real-world data decisions.

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