Developing People Analytics Dashboard in Python

Transform your hiring process with a Python-built Dashboard

  • Schedule

    20 – 22 December 2022

    18.30 – 21.30 (WIB)

  • Online-Interactive Learning

    Via Zoom

  • Investment

    Rp. 1.500.000

Course Summary

In today’s data-driven world, making informed decisions about your workforce can be a daunting task. That’s why it’s crucial to have a strong understanding of statistics, programming, and domain knowledge in the people analytics process. With these skills, you can easily make hiring decisions and effectively manage your team’s performance.

But how do you effectively communicate all this data? Visualization is key, but data changes quickly and can be overwhelming. That’s where Dash comes in. Dash is a Python framework for building web applications that allows you to create interactive, customizable dashboards with ease. Plus, it’s open-source and runs on any web browser.

Join us for a 3-day online workshop where you’ll learn how to develop your own People Analytics Dashboard in Python with Dash and Plotly. Our experienced instructors and teaching assistants will provide you with hands-on examples and personalized support throughout the course. Don’t miss out on this opportunity to unlock the power of data and take your hiring process to the next level.


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

  • Work with Python and pandas for data cleansing and manipulation processes.
  • Understand the basic idea of data visualization using plotly express.
  • Building people analytics dashboard with Dash


  • Description of course materials, timeline, and objectives of the workshop
  • Description of the workflow, tools, and setup for the course
  • Introduction to Python Language
  • Working with Anaconda 
  • Using Jupyter notebook for reproducible research
  • Inspecting data structure
  • Subsetting and conditional subsetting
  • Contingency table and aggregation table
  • Data visualization with Plotly Express
  • Dash Layout : Dash layout describes what your app will look like and comprises a set of declarative Dash components.
  • Basic Dash Callbacks :Python functions are automatically called whenever an input component’s property changes.
  • Interactive Graphing and Cross Filtering : Bind interactivity to the Dash Graph component whenever you hover, click, or select points on your chart.


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.



Dwi Gustin Nurdialit

A Data Science Instructor at Algoritma Data Science School, experience building data-intensive applications, tackling complex architecture and scalability issues across multiple industries. Proficient in predictive modeling, data processing, data mining algorithms, and scripting languages, including Python and R. Capable of creating, developing, and deploying various adaptive services to translate business and functional qualifications into tangible deliverables. She has more than 150 hours of teaching experience and has been involved in numerous consultative data science training and course production for our clients, to name a few:

  • Badan Tenaga Atom Nasional (BATAN)
  • Direktorat Jenderal Pajak (DJP)
  • Perusahaan Listrik Negara (PLN)
  • Telkom