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Market Basket Analysis for Cross-Selling

Unveiling Product Pairings and Maximizing Upsell Strategies

  • Schedule

    23 – 25 April 2024

    09.00 – 15.00 (WIB)

  • Algoritma Training Center

    Menara Kadin, 4th Floor, Jl. H. R. Rasuna Said No. Kav. 2-3, South Jakarta – 12950.

  • Investment

    Rp. 5.550.000

15

Hours Course

WORKSHOP STARTS IN

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Overview:

In this comprehensive workshop, attendees will immerse themselves in the world of Market Basket Analysis, a powerful strategy for uncovering product associations and optimizing upselling tactics. The course commences with a solid foundation in R programming basics, introducing attendees to the essential tools of the trade, including R and RStudio, along with an exploration of data types and structures in R.

The core of the workshop focuses on the Apriori Algorithm, unraveling market basket analysis metrics, rule extraction, and performance evaluation. The pinnacle is a hands-on case study, where attendees apply their skills to analyze retail datasets, generating and visualizing interactive market rules. By the end, attendees will possess a valuable skill set for maximizing cross-selling opportunities and devising effective upsell strategies through the lens of Market Basket Analysis.

Course Syllabus

  • R and RStudio: Acquaint yourself with the fundamental tools, R and RStudio, essential for effective programming in R.
  • Data type in R: Gain insights into the diverse data types in R, laying the groundwork for efficient data manipulation.
  • Data structures in R: Explore the various data structures in R, essential for organizing and storing information effectively.
  • Importing Dataset: Master the art of importing datasets in R, a crucial skill for preparing data for analysis.
  • Working with transaction logs in R: Uncover tips and techniques for efficiently navigating and extracting insights from transaction logs.
  • Working with sparse matrix: Dive into working with sparse matrices, a key aspect of handling large and complex datasets.
  • Visualizing transaction data: Develop proficiency in visualizing transaction data, a crucial step towards understanding patterns and trends.
  • Market Basket Analysis Matrics: Familiarize yourself with the metrics used in market basket analysis, gaining a deeper understanding of transaction patterns.
  • Apriori algorithm: Explore the Apriori algorithm, the cornerstone of market basket analysis, and understand its application in uncovering associations.
  • Extracting rules: Learn the techniques for extracting meaningful rules from transaction data, providing actionable insights for cross-selling.
  • Evaluating model performance: Delve into methods for evaluating the performance of market basket analysis models, ensuring accuracy and reliability.
  • Analyze Generated Rules: Apply acquired skills to analyze rules generated from a real-world retail dataset, honing your ability to derive valuable insights.
  • Produce interactive visualization for market rules: Showcase your understanding by creating dynamic visualizations for market rules, enhancing your communication of analytical findings.

Course Receivables:

  • Lecturer’s Notes

    Including 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 each course.

  • Certification of Completion

    Show current employer hat you’ve completed the course with a signed certificate of completion.

  • Quality Learning Environment

    We pay meticulous attention to the logistical details of our workshops: quality audio and visual setups, comfortable sitting arrangements, and small group size.

  • Refreshments & Coffee Break

    In our commitment to delivering a premium experience, we collaborate with leading catering services in Jakarta. Our aim is to ensure that all participants are served delectable lunches and revitalizing coffee breaks.

ABOUT THIS SERIES

Courses in this series cater to a diverse audience: from casual learners and working professionals to those venturing into data science and machine learning without a programming background.

We recognize that many students may not have prior expertise in statistics, mathematics, or algebra. Therefore, our courses are designed with a gentle learning curve, placing a strong emphasis on hands-on experience and individualized instruction. Our dedicated team of instructors and teaching assistants ensure personalized guidance every step of the way.

Teaching Methodology:

Students work through tons of real-life examples using sample datasets donated by our mentors and corporate partners. We believe in a learn-by-building approach, and we employ instructors who are uncompromisingly passionate about your growth and education.