Scorecard Analysis for Behaviour Credit Scoring

Learn end-to-end credit scoring, from business transactional financial data to the machine learning algorithms behind it.

  • Schedule

    24 – 26 June 2024

    18.30 – 21.30 (WIB)

  • Online-Interactive Learning

    Via Zoom

  • Investment

    Rp. 1.500.000

Course Summary

In today’s data-driven world, the ability to harness and derive insights from various data sources is a highly sought-after skill. The Nomor Induk Kependudukan (NIK) system in Indonesia serves as a rich source of information about its citizens, and understanding and utilizing this data can yield numerous benefits across diverse domains.

This 3-days workshop is designed to equip participants with the skills and knowledge necessary to enrich and gain insights from data associated with the Nomor Induk Kependudukan (NIK) system, visualize these insights using Plotly, and present interactive visualizations in a dashboard format using Streamlit. NIK is the unique identification number assigned to Indonesian citizens, and this course will focus on leveraging this data for meaningful analysis and visualization.

Learning Outcomes

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

  • Enrich and get insights from NIK (Nomor Induk Kependudukan)
  • Visualize insights in the form of interactive plots using Plotly
  • Present interactive visualizations in a dashboard using Streamlit


  • Working with Conda Environment
  • Introduction to Python for data science
  • Data manipulation and processing with Python Pandas
  • Introduction to graph and graph terminology
  • Graph types: weighted & Unweighted graph
  • Overview of graph implementation in Python
  • Data pre-processing for graph implementation in Python
  • Graph building and graph visualization
  • Finding optimal routes based on overall costs
  • Finding optimal routes based on scale priority : weighted sum model


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


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.


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


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


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


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.


Rany Dwi Cahyaningtyas

Rany Dwi Cahyaningtyas ia a Senior Data Science Instructor with experience in programming languages such as R, Python, and SQL, she has demonstrated her expertise through leading various academic and corporate training sessions across a wide array of sectors, such as finance, banking, telecommunication, and retail. With a blend of technical expertise and a passion for education, Rany has been essential in delivering consultative training in data science to a wide array of esteemed clients and helped these companies make informed and strategic business decisions based on data.