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Cross-Selling and Product Recommendation: Market Basket Analysis

Online Data Science Series

30 June – 2 July 2020
14.00 – 17.00 (WIB)

VIA ZOOM
Online-Interactive Learning

IDR 1.100.000

Course Summary

This 3-day online workshop is a beginner-friendly introduction to Market Basket Analysis with R. By studying this market basket analysis, you can provide product recommendations to customers based on historical transactions from previous customers.

Throughout the online course, we will provide participants with a rich interactive experience. One Instructor and two Teaching Assistants will help participants to troubleshoot or help with any difficulties encountered by participants.

NOTE:

  • If you had attended one of our DSS workshops in the past, you are not advised to attend the first day of this workshop. Please register here to skip the first day of the workshops: bit.ly/regis_2day.
  • The workshop will be delivered in Bahasa Indonesia

COURSE OBJECTIVE

Upon completion of this workshop, you will be able to:
  • Work with the R language and open source packages for data cleansing and manipulation process
  • Perform a business recommendation for a cross-selling strategy based on the model’s extracted rules
  • Evaluate and produce visualization for generated rules for business-making decision support

Syllabus

  • R and R Studio
  • Data type in R
  • Data structures in R
  • Importing dataset
  • Working with transaction logs in R:  tips and techniques
  • Working with sparse matrix
  • Visualizing transaction data
  • Market basket analysis metrics
  • Apriori algorithm
  • Extracting rules
  • Evaluating model performance

Market Basket Analysis on Retail Dataset

  • Analyze generated rules
  • Produce interactive visualization for market rules

STUDENT TESTIMONIALS

This testimonial video is taken after our previous online-interactive learning workshop (Automate Series: Business Reporting with R):

David Tahi Ulubalang

Your Instructor

Having a wide variety of industrial experiences, David Tahi Ulubalang has picked up a lot of angle in dealing with data-related cases. He majored in Computer Science from IPB and passionate on teaching machine learning and data visualization.

David is one of 5 holders of RStudio Trainer Certification in Indonesia. He has conducted numerous consultative training for BCA, Ministry of BUMN, PT Indo Kordsa, PT Indo Tambangraya Megah, to name a few.

Online Data Science Series

Workshops in our Online Data Science Series are tailored to casual learners, working professionals, and non-programmers that are taking their first steps into data science and machine learning.

Students are not assumed to have a working knowledge of R or prior proficiency in statistics/mathematics/algebra. At such the workshop follows a gentle learning curve and emphasize on hands-on, one-to-one tutoring from our team of instructors and teaching assistants

Frequently Asked Questions

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.

This workshop is an online-interactive learning workshop led by one Instructor and two Teaching Assistants. If you encounter any issue/difficulties with any topics throughout the workshop, our Teaching Assistants will gladly help to answer your question.

Workshop Receivables:

  • Workshop Lecturer’s Notes

    Including 2x Course Books (PDF), HTML files, course transcripts (if any).

  • Highly-accelerated Learning

    Learn under the assistance of mentorship of our lead instructor and a band of qualified teaching assistants throughout the 3-day course.

  • CERTIFICATION OF COMPLETION

    Show current and prospective employers that you’ve completed the course with a signed certificate of completion.

  • Supplement Materials

    Receive supplement datasets to practice on, reference notes, working files (R Notebook or Jupyter Notebook), and other materials that will help you master the topics.