About this Event
Group Discounts:
- Save 10% when registering 3 or more participants
- Save 15% when registering 10 or more participants
Duration: 1 Full Day (9:00 AM – 5:00 PM)
Delivery Mode: Classroom (In-Person)
Language: English
Credits: 8 PDUs / Training Hours
Certification: Course Completion Certificate
Refreshments: Lunch, beverages, and light snacks included
If you would like weekend training sessions, kindly reach out to us at for availability and scheduling.
Course Overview
This 1 Day beginner-to-intermediate workshop introduces you to the practical application of R in data analysis. You will work through essential analytical activities such as organizing datasets, cleaning information, transforming data, exploring patterns, and interpreting findings from real-world datasets. The course focuses on useful R techniques, applied analytics, and reproducible workflows, rather than advanced programming or complex statistical theory.
You will explore how analysts use R to handle messy data, examine relationships, identify trends, summarize information, and communicate insights. Practical demonstrations, guided exercises, and scenario-based activities help turn concepts into an understanding of R-driven data analysis.
Learning Objectives
By the end of the course, you will be able to:
- Understand commonly used R analysis workflows.
- Import, structure, and organize datasets.
- Clean and maintain data for analysis.
- Transform information using essential techniques.
- Explore datasets systematically.
- Interpret basic visualizations generated in R.
- Identify trends and develop meaningful summaries.
- Prepare a basic plan for conducting analysis with R.
Target Audience
- Beginners developing data analysis capabilities
- Business analysts and reporting professionals
- Students starting in data analytics
- Researchers using small-to-medium datasets
- Teams seeking practical analytical knowledge
- Professionals wanting a functional understanding of R
Why Choose This Course?
This training is designed around practical application rather than technical complexity. You will focus on essential R techniques for working with data without being overwhelmed by programming fundamentals or advanced statistical concepts. The trainer's experience in applied analytics and insight communication keeps the session relevant, helping you understand how R can support real-world analytical decisions.
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In-House Training
Customized in-house sessions can be developed around your organization's datasets, reporting processes, and analytical challenges. Your team can work through tailored examples, realistic scenarios, and industry-specific exercises, with optional modules for data cleaning, reporting workflows, and specialized analytics.
📧 Contact us today to schedule a customized in-house, face-to-face session:
Agenda
Module 1: R for Data Analysis – Foundations & Workflow
Info: • Understanding R’s analytical ecosystem and workflow patterns
• Key objects, data structures & beginner-friendly R concepts
• How analysts use scripts for reproducible analysis
• Icebreaker Activity
Module 2: Importing & Managing Data in R
Info: • Reading CSV, Excel, and structured datasets into R
• Handling missing values, formatting issues, and data types
• Organizing datasets for smooth analytical workflows
• Activity
Module 3: Data Cleaning & Transformation Essentials
Info: • Filtering, sorting, aggregating, and reshaping datasets
• Using beginner-friendly transformation workflows
• Identifying data quality issues and fixing inconsistencies
• Role Play
Module 4: Exploratory Data Analysis (EDA) Concepts
Info: • Understanding distributions, trends, and variable relationships
• Generating summary statistics for insights
• Using EDA techniques to guide decision-making
• Case Study
Module 5: Introductory Visualization Concepts with R
Info: • Visualizing patterns using clean, simple R plotting approaches
• Choosing the right plot to answer analytical questions
• Interpreting visual outputs for insights
• Simulation
Module 6: Basic Statistical Thinking for Data Analysis
Info: • Understanding simple correlation, variation, and trends
• Applying basic hypothesis concepts without heavy math
• Interpreting results to support insights
• Group Brainstorm Activity
Module 7: Analytical Reporting & Insight Communication
Info: • Turning analysis into meaningful, decision-ready insights
• Structuring interpretation and summarizing findings
• Building a simple, actionable analysis plan
• Action Plan Review
Event venue & nearby stays
Regus ON, London – London City Centre, 380 Wellington Street, Tower B, London, Canada
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