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 Python for Data Analytics

Data Analysis is an extremely important skill to learn in today's world. This course is designed to provide the girls with an introduction to fundamental Python programming for analytics purposes. The course will teach them how to gain essential insights by evaluating data and representing it visually by working on projects that target real-life topics. By the end of this course, girls will know how to read data from sources like CSVs and use libraries like Numpy, Pandas, Matplotlib, and Seaborn to process and visualize data.

The girls will use Jupyter Notebook to code. They will complete at least two guided projects and one independent project.

Even though no prior coding experience is required for this course, knowledge of Python Level 3 or equivalent will be beneficial.


No trial classes are offered for this course. 

This program is 25 hours long with classes typically held once a week.

Topics covered

Python basics introduction

  • Print function

  • Variables and strings

  • Basic math

  • Modules, functions and standard libraries

  • Control flows

  • Loops: For and While

  • Nested loops

  • Data structures: Lists, Tuples, Dictionaries

Understanding Data 

  • Structured vs Unstructured Data

  • Data Acquisition

    • Introduction to Pandas library

    • Series vs DataFrame

    • Reading files (CSV, TXT, XLS, JSON)

    • Writing data to files

    • HTML: Web scraping

  • Data Cleaning & Preparation

    • Handling missing data

    • Filtering out missing data

    • Filling in missing data

    • Removing duplicates

  • Data Wrangling

    • Combining and merging datasets

    • Reshaping and pivoting

  • Visualizing Data

    • Understanding and Interpreting Data

    • Exploratory Data Analysis

    • Introduction to Matplotlib

    • Figures and subplots

    • Colors, markers

    • Labels and legends

    • Saving plots to file

    • Bar plot

    • Pie chart

    • Box plot

    • Line plot

    • Scatter plot

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