₹0 for students · Certificate · Beginner

Plotting and Programming in Python

15 lessons: Python, pandas and plotting with real world-development data

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15 lessons · ~7 hours · 30-question final exam · pass mark 70%

About the course

What you’ll learn

Learn Python the way data analysts use it. Start with variables, types and built-in functions, then load real GDP and life-expectancy data with pandas, select and summarise it, plot it with matplotlib, and automate your work with lists, loops, conditionals and functions. Each lesson has a study guide, the full Software Carpentry episode with exercises, and a quiz. Pass every quiz and the final exam to earn a verifiable certificate.

PythonpandasmatplotlibJupyterData framesFunctionsData analysis

Part of the career tracks: Data Analyst, Machine Learning Engineer, GenAI and LLM Builder, Computer Science Foundations, Cybersecurity and Connected Systems

How the certificate works

  1. Read each lesson’s study guide, then the full lesson and any notebooks or exercises.
  2. Pass every lesson quiz with 70% or more.
  3. Pass the final exam: 30 questions in 45 minutes.
  4. Get a certificate with a public verification link, and add it to LinkedIn.

Syllabus

15 lessons and 5 hands-on projects in 4 parts

Python basics

1
Running and Quitting Python
20 min · Run Python interactively, as scripts, or in Jupyter notebooks.
2
Variables and Assignment
25 min · Variables are names for values; assign with =.
3
Data Types and Type Conversion
25 min · Core types: int, float, str, bool; check with type().
4
Built-in Functions and Help
25 min · Call functions with parentheses and arguments; some arguments are optional.
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Project: Trip expense splitterHands-on project
25 min · 3 steps, checked as you go

Working with data in pandas

5
Libraries
20 min · Libraries are collections of modules; the standard library ships with Python.
6
Reading Tabular Data into DataFrames
30 min · pd.read_csv loads a CSV file into a DataFrame (columns are Series).
7
Pandas DataFrames: Selecting and Filtering
40 min · .iloc selects by position; .loc selects by label (label slices include both ends).
8
Plotting
35 min · plt.plot draws lines; add xlabel, ylabel, title and legend.
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Project: Class marks reportHands-on project
35 min · 4 steps, checked as you go

Automating analysis

9
Lists
25 min · Lists hold ordered values in square brackets; index from 0, -1 is last.
10
For Loops
30 min · for item in collection: runs the indented body once per item.
11
Conditionals
25 min · if / elif / else choose a branch; only the first true branch runs.
12
Looping Over Data Sets
30 min · Loop over file names and load each with pd.read_csv.
★
Project: Attendance trackerHands-on project
35 min · 4 steps, checked as you go

Writing good code

13
Writing Functions
35 min · def name(params): defines a function; calling it runs the body.
14
Variable Scope
20 min · Local variables live only inside the function call.
15
Programming Style
25 min · PEP 8: 4-space indents, snake_case names, CapWords classes, readable line lengths.
★
Project: Sign-up form validatorHands-on project
30 min · 4 steps, checked as you go
★
Capstone: Placement drive shortlisterHands-on project
60 min · 5 steps, checked as you go

Course content is derived from Software Carpentry's "Plotting and Programming in Python" lesson (https://swcarpentry.github.io/python-novice-gapminder/), Copyright (c) The Carpentries (https://carpentries.org/), licensed under CC BY 4.0. Vikosha wrote new study guides and quiz questions; changes were made. Certificates are issued by Vikosha and are not issued or endorsed by The Carpentries. Licence: CC BY 4.0, Copyright (c) The Carpentries. View the original curriculum