GCI World 2026 September Session4 Opening

Course Announcements and Resources

Course materials and communication tools include Omni Campus, Slack, the student guide, and Google Drive. Students are encouraged to bookmark these resources and read the student guide.

WhatsApp groups are unofficial and are created by members. Joining is optional, and the course team is not responsible for issues that arise in those groups.

Make sure your Slack display name matches the name registered in Omni Campus. The display name is separate from your full name, and a mismatch could affect grade records.

Optional weekly consultations are available for questions about lectures, support from assistants, and discussion with other participants. The schedule is in the student guide, and announcements are also posted on Slack.

Competition Information

Competition materials are available on Google Drive.

• Deadline: November 20 at 1:00 a.m. UTC. Late submissions will not be accepted.
• Submit your own model predictions. Students applying for honors or outstanding-student status must also submit their code as a ZIP file.
• Multiple submissions are allowed, but only the latest version will be evaluated.
• Participation is optional for normal course completion. To receive an award, students must place in the top 20% of competition participants. Outstanding-student selection also depends on overall scores and other requirements.

Students are encouraged to read the tutorial and begin early. Session 7, on October 29, will include a practical lesson and Q&A, so participants should work through the materials beforehand.

Lesson 4: Visualizing Data with Matplotlib

The previous lesson covered using Pandas to clean and structure data, including working with Series and DataFrames, selecting rows and columns, merging tables, and grouping data to calculate totals.

This lesson introduces Matplotlib and focuses on visualizing different kinds of data. Visualization has two main purposes:

1. Exploratory data analysis (EDA): Helps analysts understand data, spot patterns and outliers, and check whether the data supports initial ideas.
2. Communication: Makes findings easier to understand than they would be in a large table—for example, by showing sales trends or best-selling products.

Planned topics include:

• The Matplotlib pyplot and object-oriented interfaces
• Basic functions for creating different chart types
• Improving readability with elements such as titles and captions
• Using axes and subplots to place multiple graphs in one figure

Students do not need to memorize everything immediately and can refer back to the provided resources.

Getting Ready for the Lesson

1. Open the course Google Drive.
2. Navigate to the folder containing the code, lecture materials, and homework.
3. Open the notebook for Lesson 4.
4. Watch the lecture video, then complete the exercises.
5. The video is longer than usual, so revisit sections as needed.

Speakers and Sources Featured

• Sariful Mirdha — introduced as the session leader.
• An unnamed teaching assistant or profile speaker — describes working in the Matsuo Institute laboratory, graduating from TCI in Japan in early 2024, earning a master’s degree in economics in March, and starting work at an IT company in April. The subtitles do not make clear whether this is a separate speaker or Sariful Mirdha continuing.