R for Data Analysis: 1 Day Hands-On Training in Ottawa
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 focused 1 Day program introduces beginners and intermediate learners to applied data analysis with R. You will work through the essential stages of handling data, including structuring datasets, cleaning information, exploring trends, examining relationships, and interpreting analytical results. The workshop is centered on practical analytics and repeatable R workflows, without requiring deep programming expertise or advanced statistics.
Using realistic examples, you will see how analysts move from messy information toward meaningful insights. Demonstrations, guided activities, and scenario-driven exercises provide opportunities to understand how R supports practical data analysis in professional settings.
Learning Objectives
By the end of the course, you will be able to:
- Identify practical workflows for analyzing data with R.
- Import and prepare datasets.
- Clean and manage data appropriately.
- Transform information for analytical purposes.
- Apply basic exploratory data analysis methods.
- Interpret simple charts and visualizations.
- Detect useful patterns and summarize findings.
- Develop a straightforward R analysis plan.
Target Audience
- Beginners interested in analytics
- Business analysts and reporting specialists
- Students developing data skills
- Researchers analyzing small-to-medium datasets
- Teams looking for practical analytical knowledge
- Professionals seeking an introduction to functional R use
Why Choose This Course?
This workshop keeps R learning practical, focused, and approachable. It avoids unnecessary programming detail and complex statistical theory while concentrating on the techniques analysts need to work with data. The trainer's applied analytics experience ensures that examples remain relevant to workplace situations, helping you understand how R can contribute to practical data-driven decisions.
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In-House Training
Teams can receive customized face-to-face training using their own datasets, reporting needs, and organizational scenarios. Exercises and examples can be adjusted to specific industries and business requirements, while additional content can be incorporated around cleaning, reporting workflows, or specialized analytical applications.
📧 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
Where is it happening?
Event Location & Nearby Stays:
CAD 807.56 to CAD 1014.56
