Introduction to Programming and Data Analysis with Python
SAT Score Range
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5 sessions
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AB
HW
IS
+5
This series ended on March 8, 2026. All 1:1 and group chats related to this series are disabled 7 days after the last session.
About
Note: some prior knowledge of Python syntax is expected.
In this course, you will learn the fundamentals of how to use Python to analyze datasets and create visualizations. We will go over how to acquire and load data into a Python file, process and clean data, and gain insight into important trends in the data. We will also go over how to use all of these skills to make graphs and visualizations. Throughout this course, you will also learn the basics of Python libraries that are crucial for data analysis such as Pandas, Numpy, and Matplotlib.
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Sessions
✋ ATTENDANCE POLICY
Please try not to miss multiple sessions. Let me know in advance if you will not be able to attend.
SESSION 1
8
Feb
SESSION 1
Python
Python
Sun 1:00 AM - 2:00 AM UTCFeb 8, 1:00 AM - 2:00 AM UTC
Introduction to the series. You will also choose a dataset to work on later in the series. You will learn to load a sample dataset and read its contents using Pandas.
SESSION 2
15
Feb
SESSION 2
Python
Python
Sun 1:00 AM - 2:00 AM UTCFeb 15, 1:00 AM - 2:00 AM UTC
You will learn to clean and preprocess data using Numpy and also learn about built-in Python functions that you can use to better understand your dataset and its properties.
SESSION 3
22
Feb
SESSION 3
Python
Python
Sun 1:00 AM - 2:00 AM UTCFeb 22, 1:00 AM - 2:00 AM UTC
You will continue learning other useful functions of Numpy (such as computations and data manipulation) that you can use to analyze your dataset. You will start applying these skills to your own dataset that you picked on the first day.
SESSION 4
1
Mar
SESSION 4
Python
Python
Sun 1:00 AM - 2:00 AM UTCMar 1, 1:00 AM - 2:00 AM UTC
You will learn about Matplotlib and Seaborn. By the end of the session you will be able to use these libraries to create visualizations of your data.
SESSION 5
8
Mar
SESSION 5
Python
Python
Sun 1:00 AM - 2:00 AM UTCMar 8, 1:00 AM - 2:00 AM UTC
You will wrap up data analysis on your dataset and take a couple minutes to share what functions you used, the data you analyzed, any trends observed, and the visualizations you were able to gain from it.