About this Event
Bring your team and save:
1. Groups of three or more receive a 10% discount
2. Organizations hosting an in-house session with 10+ participants enjoy a 15% discount.
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 will be provided during the session
Course Overview
This focused 1-Day training helps participants quickly develop beginner-to-intermediate R skills for practical data science applications. You will learn essential techniques for working with data, performing statistical analysis, creating visualizations, and automating analytical workflows using R.
Rather than spending time on unnecessary fundamentals, the course concentrates on practical skills that can make an immediate impact on your analytical capabilities. Real datasets, practical exercises, and guided mini-projects help you build confidence using R from day one.
Learning Objectives
By the end of the course, you will be able to:
- Understand fundamental R structures for analytical work.
- Clean and prepare datasets effectively.
- Use dplyr to manipulate and analyze data.
- Develop meaningful visualizations using ggplot2.
- Perform exploratory analysis with greater confidence.
- Build simple predictive models and understand the output.
- Automate workflows to make reporting faster.
Who Can Attend?
- Aspiring data and analytics professionals
- Business analysts transitioning toward data science
- Excel users seeking advanced analytical capabilities
- Students and researchers working with data
- Professionals wanting practical R skills quickly
Why Choose This Course?
The course focuses on rapid, practical learning. Delivered by an industry expert with experience in analytics, automation, and R-based problem-solving, the training is structured around real data science workflows. Participants gain hands-on experience and develop the ability to think analytically and produce meaningful insights—all in one day.
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Want to train your entire team?
We offer fully customized in-house sessions tailored to your organization's data processes, tools, and datasets. The workshop can be adapted to industry-specific analytics such as finance, healthcare, operations, or research. Whether your team is new to R or needs a refresher, we design a program that fits your workflow goals.
📧 Contact us today to schedule a customized in-house, face-to-face session:
Agenda
Module 1: R Essentials for Data Science
Info: • Learn core R syntax and data structures.
• Work with vectors, factors, lists, and data frames.
• Organize scripts and set up analytical environments.
• Icebreaker
Module 2: Data Importing & Cleaning
Info: • Import CSV, Excel, and structured datasets.
• Handle missing, inconsistent, and duplicate data.
• Use apply-family functions for transformations.
• Case Study
Module 3: Data Manipulation with dplyr
Info: • Use filter, mutate, arrange, summarize, and group_by.
• Join datasets using various join techniques.
• Build multi-step data pipelines using %>%.
• Simulation
Module 4: Visualization with ggplot2
Info: • Create bar, line, scatter, and box plots.
• Apply themes, labels, and custom styling.
• Use faceting for multi-panel visual exploration.
• Case Study
Module 5: Exploratory Data Analysis (EDA)
Info: • Generate descriptive statistics and summary tables.
• Explore trends, outliers, and distributions.
• Identify correlations and data patterns.
• Role Play
Module 6: Predictive Insights with R (Regression)
Info: • Build simple linear regression models.
• Interpret coefficients, predictions, and errors.
• Visualize regression results and residual patterns.
• Simulation
Module 7: Automation & Reporting in R
Info: • Write functions to automate repeated tasks.
• Understand R Markdown for reproducible reports.
• Export processed data and charts efficiently.
• Action Plan Review
Event venue & nearby stays
Regus 120 Collins Street, 120 Collins Street #Levels 31 & 50, Melbourne, Australia
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