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Integrating R Quarto & Python Language for Dynamic Reporting

Enhance efficiency with R Quarto and Python for seamless reporting.

  • Schedule

    24 – 26 September 2024

    18.30 – 21.30 (WIB)

  • Online-Interactive Learning

    Via Zoom

  • Investment

    Rp. 1.500.000

Course Summary

One of the capabilities of R tools is the neatness of the reports generated, especially with the development of the Quarto Markdown format, which further simplifies report creation.

The advantages of R can be applied to enhance the results of relatively simple Python reports. In addition to improving report results, we can also utilize Quarto Markdown to create dynamic reports.

Dynamic report creation can be achieved by linking narratives with code chunks, allowing the report’s text to dynamically reflect the results of data processing.

It is hoped that with this training, participants can save time in creating reports with consistent text formatting over time and ultimately become more productive in their other tasks. Additionally, participants can gain knowledge about combining the two programming languages to achieve the same goal.

Learning Outcomes

Upon completion of this workshop, you will be able to:

  • Getting to know the latest Markdown from R, Quarto Markdown
  • Utilizing Python language in R file templates (Quarto)
  • Understanding how to use inline code to generate dynamic reporting
  • Refreshment to basic python data analytics & visualization

Syllabus

  • Introduction to Python programming
  • Basic Python syntax and data manipulation
  • Integrating Python with Quarto Markdown
  • Overview of Quarto Markdown
  • Comparing Quarto Markdown with traditional Markdown
  • Creating and managing .qmd files
  • Writing and executing Python code chunks in .qmd files
  • Displaying code output and results in reports
  • Using inline code for dynamic text and calculations
  • Customizing Quarto Markdown documents (YAML)
  • Exporting report to HTML
    • PDF & Words – Optional

STUDENT TESTIMONIALS

This testimonial video is taken after our previous Online Data Science Series: Time Series Analysis for Business Forecasting.

LEARN FROM ANYWHERE

Our learning format is online-interactive, you will feel the interactive experience as if you were present in a physical classroom. You can access the class using your Zoom account on pre-defined dates.

  • LEARN AT YOUR OWN PACE

    Zoom recording, course Books (PDF & HTML files), the dataset for practice, reference notes, and working files are accessible through our Learning Management System account.

  • PROOF YOUR MASTERY

    Show current and prospective employers of your mastery in computer vision with a signed certificate of completion.

  • CONNECT WITH LIKE MINDED PEOPLE

    Be a part of our data-passionate community with 5000+ members and 1000+ alumni.

FOR ABSOLUTE BEGINNERS

Workshops in this series are tailored to casual programmers and non-programmers that are taking their first steps into data science. It assumes no prior knowledge or academic background, and attendees will be introduced to the beautiful art of writing R / Python code to produce data visualization and build machine learning models. The workshop has a gentle learning slope that is designed with non-technical professionals and academics in mind.

Yes, you can still attend the workshop as it is a beginner-friendly workshop.

Our system will send you an email containing a link and details to join a Google Classroom.

Online learning will be conducted via Zoom.us, Link to join the Zoom Class will be announced via Google Classroom.

Learning materials can be obtain via Google Classroom

Yes, you will receive a certificate of completion.

YOUR INSTRUCTOR

Victor Nugraha

Victor is an experienced Senior Instructor at Algoritma Data Science School, renowned for his successful training sessions for prestigious organizations across various industries, such as BCA, BRI, Bank Indonesia. OCBC NISP, CIMB Niaga, DBS Bank, Lembaga Administratif Negara, and Berau Coal. With a proven track record, he specializes in product analysis and product management, showcasing his expertise in leveraging data-driven insights. Victor is highly proficient in utilizing data science tools such as R and Python to unveil valuable insights from vast datasets, enabling him to craft diverse machine learning models.