Data Visualization and Analysis with R

Build a strong foundation in data analysis and visualization using R by mastering data preparation, exploration, and statistical techniques. Learn how to create advanced, interactive, and real time visualizations that uncover insights and support timely, data driven business decisions.

data-visualization-and-analysis-with-r

Advanced

Data Visualization

5 Days

Data Visualization

data-visualization

Online
On-site
Hybrid

Data Visualization and Analysis with R

Build a strong foundation in data analysis and visualization using R by mastering data preparation, exploration, and statistical techniques. Learn how to create advanced, interactive, and real time visualizations that uncover insights and support timely, data driven business decisions.

Duration:
5 Days
Rating:
4.8/5.0
Level:
Advanced
1500+ users onboarded

Who will Benefit from this Training?

Training Objectives

Build a high-performing, job-ready tech team.

Personalise your team’s upskilling roadmap and design a befitting, hands-on training program with Uptut

Key training modules

Comprehensive, hands-on modules designed to take you from basics to advanced concepts
Download Curriculum
  • R Foundations for Visualization
    1. Apply r foundations for visualization in practical visualization workflows
    2. Build and refine examples using realistic datasets
    3. Check clarity, accuracy, and stakeholder readability
    4. Document choices and iterate based on feedback
  • Data Import and Wrangling
    1. Apply data import and wrangling in practical visualization workflows
    2. Build and refine examples using realistic datasets
    3. Check clarity, accuracy, and stakeholder readability
    4. Document choices and iterate based on feedback
  • Base Graphics and ggplot2
    1. Apply base graphics and ggplot2 in practical visualization workflows
    2. Build and refine examples using realistic datasets
    3. Check clarity, accuracy, and stakeholder readability
    4. Document choices and iterate based on feedback
  • Interactive and Geospatial Viz
    1. Apply interactive and geospatial viz in practical visualization workflows
    2. Build and refine examples using realistic datasets
    3. Check clarity, accuracy, and stakeholder readability
    4. Document choices and iterate based on feedback
  • Time Series Viz and Forecasting
    1. Apply time series viz and forecasting in practical visualization workflows
    2. Build and refine examples using realistic datasets
    3. Check clarity, accuracy, and stakeholder readability
    4. Document choices and iterate based on feedback
  • Statistical and ML Visuals
    1. Apply statistical and ml visuals in practical visualization workflows
    2. Build and refine examples using realistic datasets
    3. Check clarity, accuracy, and stakeholder readability
    4. Document choices and iterate based on feedback
  • Shiny Dashboards
    1. Apply shiny dashboards in practical visualization workflows
    2. Build and refine examples using realistic datasets
    3. Check clarity, accuracy, and stakeholder readability
    4. Document choices and iterate based on feedback
  • R Markdown Reporting
    1. Apply r markdown reporting in practical visualization workflows
    2. Build and refine examples using realistic datasets
    3. Check clarity, accuracy, and stakeholder readability
    4. Document choices and iterate based on feedback
  • Domain Visualizations
    1. Apply domain visualizations in practical visualization workflows
    2. Build and refine examples using realistic datasets
    3. Check clarity, accuracy, and stakeholder readability
    4. Document choices and iterate based on feedback
  • Ethics and Best Practices
    1. Apply ethics and best practices in practical visualization workflows
    2. Build and refine examples using realistic datasets
    3. Check clarity, accuracy, and stakeholder readability
    4. Document choices and iterate based on feedback
  • Projects and Case Studies
    1. Apply projects and case studies in practical visualization workflows
    2. Build and refine examples using realistic datasets
    3. Check clarity, accuracy, and stakeholder readability
    4. Document choices and iterate based on feedback

Hands-on Experience with Tools

Training Delivery Format

Flexible, comprehensive training designed to fit your schedule and learning preferences
Opt-in Certifications
AWS, Scrum.org, DASA & more
100% Live
on-site/online training
Hands-on
Labs and capstone projects
Lifetime Access
to training material and sessions

How Does Personalised Training Work?

Skill-Gap Assessment

Analysing skill gap and assessing business requirements to craft a unique program

1

Personalisation

Customising curriculum and projects to prepare your team for challenges within your industry

2

Implementation

Supplementing training with consulting support to ensure implementation in real projects

3

Why this course

  • Comprehensive Data Understanding: R's data visualization and analysis capabilities enable businesses to understand their data better.
  • Data-Driven Decision Making: By harnessing R's analytical tools and visualizations, businesses can make well-informed decisions based on data rather than intuition.
  • Improved Business Performance: Armed with data analysis and visualizations from R, businesses can identify growth opportunities, optimize processes, and enhance customer experiences.

Training objectives

  • Gain a solid foundation in the R programming language.
  • Learn techniques to import data from various sources into R and effectively manipulate and clean datasets for analysis.
  • Understand the principles of exploratory data analysis and use R's visualization tools to uncover patterns, relationships, and anomalies in the data.
  • Acquire expertise in creating a wide range of static and interactive data visualizations using R.
  • Explore advanced visualization techniques in R, such as geospatial visualizations, time series plotting, and interactive dashboards.
  • Integrate statistical analysis into data exploration using R's statistical packages.
  • Learn how to process and visualize real-time data streams in R, enabling businesses to respond promptly to changing conditions.

Who will benefit

  • Data Analysts and Data Scientists
  • Business Analysts and Managers
  • IT Professionals:
  • Financial Analysts and Economists
  • Anyone Interested in Data Analysis and Visualization

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Frequently Asked Questions

1. What are the pre-requisites for this training?
Faq PlusFaq Minus

The training does not require you to have prior skills or experience. The curriculum covers basics and progresses towards advanced topics.

2. Will my team get any practical experience with this training?
Faq PlusFaq Minus

With our focus on experiential learning, we have made the training as hands-on as possible with assignments, quizzes and capstone projects, and a lab where trainees will learn by doing tasks live.

3. What is your mode of delivery - online or on-site?
Faq PlusFaq Minus

We conduct both online and on-site training sessions. You can choose any according to the convenience of your team.

4. Will trainees get certified?
Faq PlusFaq Minus

Yes, all trainees will get certificates issued by Uptut under the guidance of industry experts.

5. What do we do if we need further support after the training?
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We have an incredible team of mentors that are available for consultations in case your team needs further assistance. Our experienced team of mentors is ready to guide your team and resolve their queries to utilize the training in the best possible way. Just book a consultation to get support.

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