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Courses

Data Science with Python

Level
Senior High · Grades 10–12
Difficulty
Intermediate
Duration
12 modules
Curriculum
36 lessons

Curriculum

12 units
  1. 01Getting to Know Data Science and NotebooksYou understand the data science workflow and can set up Google Colab or Jupyter to read your first data file with pandas.3 lessonsShow contents
  2. 02Python for Working with DataYou can store data in lists and dictionaries, compute the mean, median, and per-group averages with plain Python, and understand why pandas is needed.3 lessonsShow contents
    • Lists and Dictionaries as Data Containers50 minLocked
    • Computing Averages per Class with Plain Python1 hLocked
    • Recap and Self-Check: Python for Working with Data45 minLocked
  3. 03Meet Pandas: Series and DataFrameYou can create and read DataFrames, check their structure and data types, create new columns, sort, and save results to CSV.3 lessonsShow contents
    • Series and DataFrame: How Pandas Sees a Table50 minLocked
    • Exploring siswa.csv with head, info, and describe55 minLocked
    • Recap and Self-Check: Pandas Basics45 minLocked
  4. 04Selecting and Filtering DataYou can select rows and columns with boolean filters, loc, iloc, and query, compute the proportion of data meeting a condition, and change data safely.3 lessonsShow contents
    • Boolean Filters, loc, and iloc for Selecting Data50 minLocked
    • Practice Filtering Student Data for the Homeroom Teacher55 minLocked
    • Recap and Self-Check: Selecting and Filtering Data45 minLocked
  5. 05Cleaning DataYou can detect and fix missing values, duplicates, inconsistent categories, and wrong data types, and record every cleaning decision.3 lessonsShow contents
    • Recognising Dirty Data: Missing, Duplicated, and Inconsistent50 minLocked
    • Cleaning the Student Council Survey Step by Step1 hLocked
    • Recap and Self-Check: Data Cleaning45 minLocked
  6. 06Descriptive StatisticsYou can compute and interpret the mean, median, mode, standard deviation, quartiles, and IQR, and detect outliers with the 1.5 IQR rule.3 lessonsShow contents
    • Measures of Centre and Spread50 minLocked
    • Computing Descriptive Statistics and Detecting Outliers55 minLocked
    • Recap and Self-Check: Descriptive Statistics45 minLocked
  7. 07Grouping and Joining DataYou can summarise data per group with groupby and agg, build cross tables with pivot_table, and join two tables safely with merge.3 lessonsShow contents
    • The Split-Apply-Combine Pattern with groupby50 minLocked
    • Analysing Canteen Sales with groupby, pivot_table, and merge1 hLocked
    • Recap and Self-Check: Grouping and Joining45 minLocked
  8. 08Data Visualisation with matplotlibYou can create complete line and bar charts with titles, labels, and legends using matplotlib and pandas, and save them as images.3 lessonsShow contents
    • The Anatomy of a Chart and How matplotlib Works50 minLocked
    • Making Canteen Sales Bar Charts and Saving Them1 hLocked
    • Recap and Self-Check: Basic matplotlib Charts45 minLocked
  9. 09Choosing the Right ChartYou can choose a chart type that fits the question, create histograms, boxplots, and scatter plots, and recognise and avoid misleading charts.3 lessonsShow contents
    • Choosing the Chart Type That Fits the Question50 minLocked
    • Practising Histograms, Boxplots, and Scatter Plots55 minLocked
    • Recap and Self-Check: The Right and Honest Chart45 minLocked
  10. 10Correlation and Time-Based DataYou can compute and interpret correlation, distinguish correlation from causation, and process and visualise dated data with moving averages.3 lessonsShow contents
    • Correlation, Causation, and Time-Based Data50 minLocked
    • Analysing Daily Temperature and Iced Tea Sales1 hLocked
    • Recap and Self-Check: Correlation and Time Data45 minLocked
  11. 11Real Data and Data EthicsYou can find and assess real datasets, tidy official downloaded tables, validate the results, and protect personal data ethically.3 lessonsShow contents
    • Finding Real Datasets and Judging Their Quality50 minLocked
    • Tidying an Official Download and Masking Personal Data1 hLocked
    • Recap and Self-Check: Real Data and Ethics45 minLocked
  12. 12Final Project: Analysing a Real DatasetYou can design, build, test, and present a complete analysis of a real dataset, from questions to honest conclusions.3 lessonsShow contents
    • Designing a Real-Dataset Analysis Project50 minLocked
    • Building the Project Notebook Step by Step1 hLocked
    • Presenting Findings, Evaluation, and Final Self-Check1 hLocked

Prerequisites

Basic Python

Tools and materials

Python, pandas, matplotlib

Final project

An analysis of a real dataset

Mentor

ES

EduSTEAM Team