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.
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
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
R PROGRAMMING BASICS
R and R Studio
Data type in R
Data structures in R
DATA WRANGLING WITH R
Working with transaction logs in R: tips and techniques
Working with sparse matrix
Visualizing transaction data
APRIORI ALGORITHM FOR MARKET BASKET ANALYSIS
Market basket analysis metrics
Evaluating model performance
Market Basket Analysis on Retail Dataset
Analyze generated rules
Produce interactive visualization for market rules
This testimonial video is taken after our previous online-interactive learning workshop (Automate Series: Business Reporting with R):
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.
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
If I don’t have any IT or programming skills, can I still attend this workshop?
Yes, you can still attend the workshop as it is a beginner-friendly workshop.
How to join the interactive-online learning class after I’ve done the payment & registration?
Our system will send you an email containing a link and details to join a Google Classroom.
What platform will be utilized for this online-interactive learning workshop?
Online learning will be conducted via Zoom.us, Link to join the Zoom Class will be announced via Google Classroom.
How will the participants receive the learning materials?
Learning materials can be obtain via Google Classroom
Would I receive a certificate after participating in the Workshop?
Yes, you will receive a certificate of completion.
What are the learning support would I get during the workshop?
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 Lecturer’s Notes
Including 2x Course Books (PDF), HTML files, course transcripts (if any).
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.
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.