Welcome

M1: Python Foundation

Module 1: Python Foundations for Healthcare

In this module, you'll build a solid foundation in Python programming, using real healthcare scenarios to make each concept practical and relevant. Whether you're calculating a patient's BMI, cleaning up demographic data, or writing simple logic to flag abnormal lab values, you'll start to see how even the basics of Python can bring structure and clarity to complex healthcare challenges. No prior programming experience is needed—just a curious mind and a passion for improving care through smart, data-driven solutions.

Module 1: Python Foundations for Healthcare - 1.1

Module 1: Python Foundations for Data Analysis

Module Overview

This module introduces the fundamentals of Python programming with a focus on practical applications in healthcare data analysis. The goal is to equip learners with essential Python skills required for reading data, performing calculations, and writing clean, structured code.

Python is widely used in healthcare for tasks such as analyzing electronic health records, calculating medical indicators, and automating repetitive workflows. Whether you’re a clinician exploring analytics or an analyst entering healthcare, these skills form the baseline for advanced topics covered in later modules.

Learning Objectives

By the end of this module, learners will be able to:

Understand Python syntax, variables, and data types
Use control flow (if-else statements and loops) to automate logic
Write functions for repeatable calculations
Read from and write to files (CSV and JSON)
Build and test scripts in a Jupyter Notebook environment

1.1 Introduction to Python and Jupyter Notebooks

Key Concepts:

What is Python and why is it used in healthcare analytics?
Installing Python (via Anaconda or pip)
Introduction to Jupyter Notebooks

Activity:

Open a new Jupyter Notebook and type:

python

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print("Welcome to Python for Healthcare Analytics")

1.2 Variables and Data Types

Key Concepts:

Python variable naming rules
Common data types: int, float, str, bool, list, dict

Example:

python

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patient_age = 57

blood_pressure = 142.5

diagnosis = "Hypertension"

medications = ["Lisinopril", "Amlodipine"]

Practice:

Create a variable for a patient’s ID, age, and diagnosis
Store multiple lab results in a list
Create a dictionary with keys: name, age, diagnosis, and medication

Module 1: Python Foundations for Healthcare - 1.2

1.3 Control Flow (Conditions and Loops)

Key Concepts:

if, elif, else statements
for and while loops
Logical operators: ==, !=, >, <, and, or

Example:

python

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if blood_pressure > 140:

print("High blood pressure")

python

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for med in medications:

print(f"Patient is taking: {med}")

Practice:

Write a loop that prints all medication names
Write an if statement that flags a patient as "At Risk" if age > 65 or BP > 140

1.4 Writing Functions

Key Concepts:

Defining reusable functions using def
Parameters and return values

Example:

python

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def calculate_bmi(weight_kg, height_m):

return weight_kg / (height_m ** 2)

Practice:

Write a function to calculate BMI and test it with different values
Write a function that returns "Eligible" or "Ineligible" based on patient age and diagnosis

1.5 Working with Files

Key Concepts:

Reading from and writing to .csv and .json files
Using the open(), read(), write() functions
Using pandas as an alternative (preview for Module 2)

Example (CSV with built-in tools):

python

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with open("patients.csv", "r") as file:

lines = file.readlines()

for line in lines:

print(line)

Example (CSV with Pandas):

python

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import pandas as pd

df = pd.read_csv("patients.csv")

print(df.head())

Practice:

Create a .csv file with 5 patients and read it using Python
Write a Python script that reads the file, calculates BMI, and prints it

1.6 Summary and Assessment

Summary:

In this module, you have learned the core building blocks of Python that will serve as the foundation for all future modules. You now understand:

How to define and use variables
Control flow for conditional logic
Loops to automate repetitive tasks
Functions to encapsulate logic
How to work with files and datasets

Assessment (Suggested Format: Notebook or LMS Quiz):

Create a script that:
- Reads patient height and weight from a list of dictionaries
- Calculates BMI
- Flags patients with BMI > 30 as "Obese"
Write a function risk_score(age, bp, cholesterol) that returns a simple risk category:
- "Low", "Moderate", or "High"

Files & Resources

patients.csv – sample dataset
Jupyter Notebook template for all exercises
Python cheat sheet PDF (optional)
Instructions for installing Anaconda and launching notebooks

Let me know if you’d like this content:

Converted into a downloadable PDF or Word course guide
Loaded into an LMS platform structure
Paired with a complete Jupyter Notebook and answer key
Packaged with visuals or interactive elements (e.g., slides, diagrams)

Python Foundation Quiz

Disclaimer: The videos included have been thoughtfully selected to support and enrich the learning experience. While not essential to the completion of the course, they offer valuable insights that may deepen your understanding of the module content. Dr Data Insights does not claim authorship or involvement in the creation of these tutorials.