In Episode 6, we introduced Python data types and provided a general overview of collections like lists, tuples, and dictionaries. Now, in Episode 7, we’ll begin exploring each data type one by one, starting with Strings.

🎯 Objective

By the end of this episode, learners will understand:

• What a string is in Python.

• How to create and store strings.

• The len() Function in Python

• Common string operations (concatenation, indexing, and slicing).

Let’s get started!

What a string is in Python

In Python, a string is a sequence of characters, which can include letters, numbers, or symbols, enclosed in either single quotes ('...') or double quotes ("..."). These quotes are known as delimiters. A delimiter is a character that indicates where a string begins and ends in Python.

📌 Example (healthcare context):

patient_name = "Ahmed Ali"
diagnosis = "Hypertension"
hospital_id = "CH12345"
hospital = 'City Hospital'

Python can tell us what kind of data we’re dealing with by using the type() function.

Example:

patient_name = "Ahmed Ali"
print(type(patient_name))

Output:

<class 'str'>

This shows that the variable patient_name is of the type string (str).

Strings vs. String Literals

• String: In Python, a string is a data type used to represent text. When we call something a string, it means the stored value is text.
  String literal: This refers to the exact characters you write in your code to create a string. For example, "Mohamed Omer" is a string literal, the quotes and text you type. When stored in a variable, like patient_name = "Mohamed Omer", the value of patient_name is a string.

👉 In short:

String Literal → "Mohamed Omer"  (what you write in code with quotes)
String         → Mohamed Omer    (the actual stored text)

The len() Function in Python

In Python, the len() function is used to find the length of a string, which is the total number of characters it contains, including spaces and symbols.

This is very useful in healthcare settings, for example, when checking if a patient ID or medical record number has the correct length.

🩺 Example 1: Simple String

patient_name = "Ahmed Ali"
print(len(patient_name))

Output:

9

👉 The string "Ahmed Ali" has 9 characters (including the space between Ahmed and Ali).

🩺 Example 2: Patient ID

patient_id = "MRN12345"
print(len(patient_id))

Output:

8

👉 The patient ID has 8 characters, which can be checked to ensure it matches the required format.

🩺 Example 3: Empty String

note = ""
print(len(note))

Output:

0

👉 An empty string has a length of 0.

✅ Key Takeaway:

• len() counts every character, including spaces, numbers, and symbols.

• It helps you validate input (e.g., ensuring a password, patient ID, or report isn’t too short or too long).

Multiline Strings in Python

Sometimes, a single line of text is not enough. In healthcare or medical informatics, you may want to store long notes, discharge summaries, or patient history that spread across multiple lines.

Python allows us to create multiline strings using triple quotes (""" or ''').

🩺 Example 1: Patient Note

patient_note = """Patient complains of headache.
Blood pressure measured at 140/90.
Advised to reduce salt intake and follow up in 2 weeks."""
print(patient_note)

Output:

Patient complains of headache.
Blood pressure measured at 140/90.
Advised to reduce salt intake and follow up in 2 weeks.

👉 Notice how the text keeps its format across multiple lines.

🩺 Example 2: Medical Report (with triple single quotes)

medical_report = '''Lab results:
- Hemoglobin: 13.5 g/dL
- Glucose: 95 mg/dL
- Cholesterol: Normal
'''
print(medical_report)

Output:

Lab results:
- Hemoglobin: 13.5 g/dL
- Glucose: 95 mg/dL
- Cholesterol: Normal

✅ Key Notes on Multiline Strings

• They are defined with triple quotes (""" or ''').

• Useful for storing paragraphs, reports, or formatted text.

String Operations

1️⃣ Concatenation (Joining strings together)

Concatenation means combining two or more strings into one. This is very useful in healthcare when you want to join patient information, like their name and ID, into a single message, using the + operator.

single message.

first_name = "Ahmed"
last_name = "Ali"
full_name = first_name + " " + last_name # The purpose of the double quotes here is to create a space between the two names. 
print(full_name)

Output:

Ahmed Ali

2️⃣ Repetition (Repeating a string)

Repetition allows you to repeat a string multiple times using the * operator. This can be helpful, for example, when creating separators in reports or repeating a symbol.

separator = "-" * 30
print(separator)

Output:

------------------------------

3️⃣ Indexing (Accessing a single character)

When you write a string in Python, Python stores it in memory as a sequence of characters. To help us find or work with specific characters, Python gives each character a numbered position, which we call an index.

Think of a string as a row of numbered lockers, where each locker holds one character.

• Indexing from Left to Right (Positive Indexing)

  In Python, when you count from the left side, indexing starts at 0 (not 1).

  For example:

word = "HELLO"

Here’s how Python sees it:

👉 That means:

• word[0] → "H"

• word[1] → "E"

• word[4] → "O"

Indexing from Right to Left (Negative Indexing)

Python also allows us to count from the right side. When we count backwards, the index starts at -1.

Using the same example:

word = "HELLO"

👉 That means:

• word[-1] → "O" (last character)

• word[-2] → "L" (second from the right)

• word[-5] → "H" (first character, same as index 0)

patient_id = "MRN12345"
print(patient_id[0])  # First character
print(patient_id[-1]) # Last character

Output:

M
5

4️⃣ Slicing (Extracting part of a string)

Slicing means cutting out a substring (a smaller piece of a string) by telling Python where to start and where to stop.

The basic syntax is:

string[start:stop]

• start → the index where the slice begins (included).

• stop → the index where the slice ends (excluded).

word = "HOSPITAL"

print(word[0:4])   # "HOSP"
print(word[2:7])   # "SPITA"

👉 Notice that the slice includes the character at the start index, but stops right before the stop index.

Output:

HOSP
SPITA

Sometimes you don’t always have to write both numbers.

• If you leave out start, Python begins at the beginning.

• If you leave out stop, Python goes all the way to the end.

print(word[:4])   # "HOSP"   (from start to index 3)
print(word[3:])   # "PITAL"  (from index 3 to end)
print(word[:])    # "HOSPITAL" (entire string)

You can also slice from the right using negative indexes.

print(word[-4:])   # "ITAL"  (last 4 letters)
print(word[:-3])   # "HOSPI" (everything except last 3)

There’s an optional step value:

string[start:stop:step]

• step tells Python how many characters to skip.

print(word[0:7:2])   # "HSPL" (every 2nd character)
print(word[::-1])    # "LATIPSOH" (reverses the string)

Slicing is like cutting out a piece of a cake; it always includes the start index but stops right before the stop index. You can use positive or negative indices, and you can also add a step to skip characters or reverse a string.

5️⃣ Membership (Checking if a word exists in a string)

You can use the keywords in or not in to check if a substring exists inside a string.

note = "Patient has diabetes"
print("diabetes" in note)     # True
print("cancer" not in note)   # True

Output:

True
True

These are the basic string operations. Later, we can also explore string methods (like .lower(), .upper(), .replace(), etc.) which make working with strings even more powerful.

Let’s wrap up Episode 7 with a hands-on exercise!

📝 Practice Exercise: Strings in Action

You are given this string:

patient_name = "Samar Ali"

Part 1: Indexing

1. Print the first character of the name.

2. Print the last character of the name.

Part 2: Slicing

3. Extract "Samar" from the string.

4. Extract "Ali" from the string.

5. Reverse the entire string.

6. Get every second letter in "Samar".

Part 3: String Operations

7. Concatenate " Samar Ali" with the string " is a patient".

8. Repeat the string "ID-" 3 times.

9. Find the length of the string using len()

After you finish, send your answers to my email saja@sajamedtech.com for feedback.

What’s Next?

In the next episode, we’ll explore string methods in Python that allow us to transform, clean, and analyze text data more effectively.

See You Later!

In this episode, we will explore:

• What Python data types are and why they matter

• The difference between structured and unstructured medical data

• Python's basic data types: int, float, str, bool

• Common Python collections: lists, tuples, and dictionaries

• How to check data types using type() and isinstance()

You will also see real-life healthcare examples that show how data types help organize and protect medical information.

🧠 What are Python data types, and why do they matter in healthcare?

In Python, every piece of data, like a number, a word, or a True/False value, has a type. Knowing the data type helps Python (and you) decide what you can and cannot do with that data. Python data types are the basic tools that help developers and analysts manage the large amounts of medical information created every day.

📋Understanding structured vs unstructured medical data

The medical field deals with two primary categories of information that require different processing approaches:

✅ Structured medical data is very organized and fits well into traditional databases. This includes:

• Patient demographics

• Vital signs measurements

• Laboratory test results

• Medication dosages

✅ Unstructured data doesn't have a set format but holds very valuable clinical insights. This includes:

• Clinical notes and discharge summaries

• Medical images (X-rays, MRIs, CT scans, ultrasounds)

• Transcribed conversations between doctors and patients

• Patient-generated health data from wearable devices

• Genetic sequencing reports

📌 Data Types in Python

Python provides several built-in data types that align perfectly with healthcare needs:

• Numeric types (int, float) handle quantitative medical data like patient ages, blood pressure readings, and lab values.

    patient_age = 50     #This is an integer number
    body_temperature = 98.6      #This is a float number
  

  • Integers (int): Perfect for whole numbers like patient age, heart rate, or step counts.

  • Floating-point numbers (float): Ideal for measurements with decimal values such as body temperature (98.6°F), or medication dosages (2.5mg).

• String types (str) are immutable, meaning they can’t be changed after they are created. This makes them safer for storing sensitive patient information, as it prevents accidental changes.

  Strings are written inside single quotes ‘’ or double quotes “”.

    patient_name = "Ali"
    diagnosis = 'Hypertension'
  

• Boolean types (bool) represent true/false values, ideal for test results and condition flags:

  • Laboratory test results (positive/negative)

  • Patient status flags (admitted/discharged)

  • Insurance verification (covered/not covered)

      is_discharged = False
      covered_with_insurance = True
    

Working with Python Collections: Lists, Tuples, and Dictionaries

In real-life healthcare and data science, we often need to manage groups of related information, like a list of symptoms, a fixed range of lab values, or detailed patient records. Python gives us special tools called collections to handle this kind of data efficiently.

In this section, you will learn about Lists for storing changeable data like medications, Tuples for storing fixed data sets like reference ranges, and Dictionaries for pairing labels with values like a patient’s name, age, and test results.

These structures help keep your data organized, readable, and accessible, which is especially important when working with medical information or building healthcare applications.

Let’s explore each one and see how they work in simple, real-world examples:

• Lists can be changed, which means they are mutable. They are written with square brackets []. Lists are ordered collections, making them great for:

  1. Tracking symptoms that may change during treatment

      symptoms = ["fever", "cough", "fatigue"]
      print(symptoms)
     

     2. Recording vital sign measurements over time

     3. Storing patient visit history

• Tuples store collections of related values, like symptoms or medications. They are immutable (unchangeable) ordered collections and are written with parentheses ().

  Use tuples when you want to protect the data from being changed. ideal for:

  • Lab result reference ranges that shouldn't change

    hemoglobin_range = (12.0, 15.5)  # Lower and upper limit (g/dL)
    print("Hemoglobin normal range:", hemoglobin_range)

• Dictionaries map keys to values, making them perfect for linking patient IDs to records. They are written inside curly brackets.

    patient_record = {
        "patient_id": "MRN12345",
        "name": "Sama Ahmed",
        "age": 25,
        "blood_type": "O+",
        "allergies": ["Penicillin", "Sulfa"],
        "vital_signs": {"temperature": 98.6, "blood_pressure": "120/80"}
    }
  

  Don't worry about the dictionary syntax. We will cover this in more detail in future episodes.

🧠 How to check data types in Python

1. You can use Python’s built-in function type() to find out the data type of any variable.

    heart_rate = 85
    print(type(heart_rate))  # Output: <class 'int'>
   

   Note that the output shows you the 'class' type of the data, which is ‘int‘, an integer.

   Try this on your device:

    # Patient details
    patient_name = "Amina Yusuf"          # str
    patient_age = 34                      # int
    patient_temp = 38.2                   # float
    is_discharged = False                 # bool
   
    # Checking data types
    print(type(patient_name))
    print(type(patient_age))
    print(type(patient_temp))
    print(type(is_discharged))
   

   For medical applications, type() offers a quick way to confirm that patient data is in the expected format before performing calculations or analysis.

2. Using isinstance() for Safer and Smarter Type Checking

   While type() tells you the exact type of a value, isinstance() is more flexible and often better when your program needs to handle different (but related) data types.

   Let’s say we want to know whether a piece of data is a number, a string, or something else.

   Here’s how you can do it:

# Let's try with a number
heart_rate = 85

print(isinstance(heart_rate, int))  # This will print: True

# Now try with a word (a string)
blood_type = "O+"

print(isinstance(blood_type, int))  # This will print: False
print(isinstance(blood_type, str))  # This will print: True

• isinstance(value, type) This is the syntax for isinstance.
  It checks: “Is this value of this type?”

  If yes, it prints True
  If no, it prints False

• You can even check two types at once:

    age = 30
    print(isinstance(age, (int, float)))  # Will be True if age is int or float
  

  ✅ Why This Is Helpful

  When working with real patient data, it’s important to:

  • Know what type of data you are dealing with (number, text, etc.)

  • Avoid mistakes like doing math on words

So isinstance() is like asking:

"Is this value a number or text?"
And Python answers: True or False

Now, try this and let me know what the outputs are:

    temperature = 98.6
    print(isinstance(temperature, float)) 

    patient_name = "Amina"
    print(isinstance(patient_name, str))

🧪 Practice Exercise: Organize and Check Patient Data

Create a Python program that stores the following information about a patient:

• Full name

• Age

• Body temperature

• Is the patient under observation? (yes/no)

• Allergies list

• Hemoglobin reference range

• Patient’s blood type

Use both type() and isinstance() to print the data types of each variable.

💻 What to do:

• Use print() to show each variable’s value

• Use type() to check its data type

• Try isinstance() on at least 3 variables to see if they match the expected type

📩 Once you complete the exercise, please send your code and results to my email so I can review your progress and provide feedback. saja@sajamedtech.com

✅ Conclusion: Why Data Types Matter in Medical Coding

Understanding data types is one of the most important skills you can learn as a beginner programmer, especially in healthcare, where working with sensitive and structured data is part of daily operations.

Knowing whether a piece of data is a number, a word, or a true/false value helps you:

• Use the right logic and operations

• Prevent errors in calculations

• Ensure patient data stays clean and accurate

• Work confidently with larger and more complex datasets in the future

In the next episode, we’ll begin a deeper exploration of each Python data type, starting with strings. You will learn how to work with text data, apply basic string operations, and understand why this is important in managing healthcare records.

See you tomorrow!

In the previous episode, you wrote your very first lines of Python code. You learned how to use the print() function, create basic variables, and write comments.

Now, we will dive a bit deeper into an important building block of Python: the variable.

🧠 What You’ll Learn in This Episode:

• What is a variable in Python, and how does it work

• What is the Assignment Operator in Python

• Rules for Naming Variables in Python

• Best practices for naming variables

🔡 What is a Variable?

A variable is a name you assign to a piece of information so Python can store and use it later.

Think of it like a labeled box that holds a value.

patient_name = "Fatima"

Here:

• patient_name is the variable

• "Fatima" is the value stored inside it

Variables are essential in programming because they make your code:

1/ Accessible

When you assign a value to a variable, you can reuse that value anywhere in your program without needing to retype it.

In simple words, Variables act like labels, so you don’t have to remember or rewrite the actual value.

📌 Example:

hospital_name = "Green Valley Clinic"

print("Welcome to", hospital_name)
print("Thank you for visiting", hospital_name)

Instead of writing "Green Valley Clinic" again and again, you just write the variable hospital_name.

This approach makes your code easier to read, faster to write, and simpler to update later.

2/ Give values context

By naming a variable, you give meaning to the value it holds.

In simple words, the name of a variable explains what the value is and why it matters.

📌 Example:

temp = 37.5

This is acceptable, but it lacks clarity.

However, this is much better:

patient_temperature = 37.5

Now, anyone reading the code knows this value represents a patient’s temperature, not just a random number.

Giving context helps you understand your code later, allows others to read your code more easily, and reduces mistakes in large projects.

What is the Assignment Operator in Python?

In Python, the = symbol is called the assignment operator. It is used to assign a value to a variable.

📌 Example:

patient_age = 45

Here, you are telling Python: “Store the value 45 inside the variable called patient_age.”

So now, whenever you use patient_age, Python will know that it means 45.

But what is the difference between the equal sign and the assignment operator?

In mathematics, the equal sign = means both sides are exactly equal.

For example:

3 + 2 = 5

This is a statement of equality.

But in Python (and most programming languages), = doesn’t mean “equal to.” It means:

“Take the value on the right and store it in the variable on the left.”

So:

x = 10

Means: “Let the variable x hold the value 10.”

This is a one-way operation, not a comparison.

⚠️ Common Mistake:

People often confuse the assignment operator (=) with the comparison operator (==).

• = is used to assign values to variables

• == is used to compare values (we’ll learn this in future episodes)

🏷️ Rules for Naming Variables in Python

When you create a variable in Python, you can choose the name, but it must follow some rules so Python can understand and process it correctly.

Here are the most important rules and best practices:

1. Variable names must start with a letter or an underscore (_)

• Valid:

    name = "Ali"
    _age = 30
  

• ❌ Invalid if you start the variable name with a number:

    1name = "Sara"  # Error! Starts with a number
  

2. The name can include letters, numbers, and underscores

• Valid:

    patient1 = "Mariam"
    patient_name = "Hassan"
  

• ❌ Invalid if you use any other special characters like - or # :

    patient-name = "Amir"  # Error! Hyphens are not allowed
  

3. Variable names are case-sensitive

Name = "Zainab"
name = "Ahmed"

These are two different variables (Name and name) because Python treats uppercase and lowercase letters as different.

4. You cannot use Python’s reserved words as variable names

Python's reserved words, like if, for, True, and print, are special keywords used for its operations and cannot be used as variable names.

❌ Invalid:

if = 5  # ❌ Error: "if" is a reserved word

✅ Instead, use something like:

if_value = 5

💡 Best Practices:

• Use clear, meaningful names:

Good: patient_name, temperature, heart_rate
Bad: a, b, x1 (not descriptive)

• Use lowercase letters and underscores (snake_case)

  In Python, the standard way to name variables is to use lowercase letters with words separated by underscores.

  ✅ Recommended:

patient_name = "Ali"
blood_pressure = 120

This style is called “snake_case” and is the preferred naming convention in Python.

❌ Not recommended:

PatientName = "Ali"       # CamelCase – more common in other languages like Java

• Avoid using very long names unless necessary

🧪 Practice Exercise: Create a Simple Hospital Intake Form

Scenario:

You’re working at the reception desk of a hospital. Create a Python program that stores a new patient’s basic information using variables.

Your task:

1. Create 5 variables to store:

   • Patient name

   • Patient ID number

   • Department (e.g., “Radiology”)

   • Doctor’s name

   • Room number

2. Use print() to display the patient’s intake form in a clean format

3. Add comments to explain what each line is doing

📝 Example Output:

Patient Intake Form
---------------------
Name: Huda Kareem
Patient ID: 10432
Department: Radiology
Doctor: Dr. Salim
Room No: 12B

Use clear and meaningful variable names.

After you finish, send your answer to the following email: saja@sajamedtech.com

📩 Coming Up Next in Episode 6:

In the next episode, we will explore data types, how Python understands the kind of data you are working with (like text, numbers, or true/false values), and why it matters.

See you tomorrow!

Now it’s time for the exciting part: writing your very first Python code! 🎉

🧠 What Will You Learn in This Episode?

• How to run your first Python command

• How to use the print() function

• How Python reads and executes code

• How to declare a variable and inspect its value

• How to write comments

• Two simple examples: one related to healthcare and one from daily life.

Let’s keep it simple and fun. No prior coding knowledge needed!

🛠️ How to Open a New Python File

📌Note: If you are using your smartphone, skip Anaconda and Visual Studio Code, as these options only work on computers. Instead, proceed to the section on What is the print() Function in Python?

🟢 On Anaconda (Jupyter Notebook)

1. Open Anaconda Navigator from your Start Menu or Applications folder.

   

2. Click Launch under the Jupyter Notebook section.

   

3. A browser tab will open (usually at http://localhost:8888).

4. Navigate to the folder where you want to create your file.

5. Click New > Python 3 (ipykernel) from the top right corner.

   

6. A new notebook will open, now you can type Python code in the gray "cells" and click Run.

   

7. Try to write the following code:

    print("Hello, future coder!")
   

8. After that, run the code using the ▶️ “Run” button above

   

9. You will see the output below the cell.

   

   📌 Note: Jupyter Notebook saves files with a .ipynb extension (Notebook format).

A .ipynb file is a Jupyter Notebook file. It stands for "Interactive Python Notebook."

It allows you to write Python code in small sections (cells), add text, images, and explanations, run code, see the results immediately below the code cell, and save everything in one file.

🔵 On Visual Studio Code (VS Code)

1. Open Visual Studio Code.

   

2. Create a new folder or open an existing folder where you want to save your Python file.

   

3. After opening your folder, you will see its name. To the right, there are four symbols. Click on "New File".

   

4. Enter a name for your file and add the .py extension at the end. (e.g., episode4.py):

5. In the file, start writing your Python code.

6. Try to write the following code:

    print("Hello, future coder!")
   

7. After that, run the code using the ▶️ “Run” button above in the right corner

   

8. You will see the terminal open in the lower half of the code editor, displaying the folder and file names, along with the output.

   

What just happened?
You told Python to display the message inside the quotation marks ““ using the print() function. It’s the most basic and useful command for beginners.

What is the print() Function in Python?

The print() Function is a built-in function that outputs the specified message to the screen (standard output). It is one of the most basic and commonly used functions in Python. It tells Python to display a message or the result of a calculation on the screen.

print("Hello, future coder!")

🧠 In simple terms: print() is how Python talks back to you.

Whenever you want Python to show something, like text, numbers, or results, you use print().

You can also print numbers, variables, or even results of math operations:

print(5 + 3)    #Try it in your code editor!

How Python Reads and Executes Code

When you write a Python program, Python reads your code from top to bottom, one line at a time, and executes each instruction step by step.

Think of Python like a person reading a recipe:

1. It starts at the top.

2. It reads the first instruction (line of code).

3. It follows the instructions and does what you told it to do.

4. Then it moves to the next line.

🧪 Example:

print("Step 1: Starting...")
print("Step 2: Doing something")
print("Step 3: Done!")

🖥️ Output:

Step 1: Starting...
Step 2: Doing something
Step 3: Done!

Python reads and runs the lines in order; it does not skip around unless you tell it to (like with conditions or loops, which we’ll learn later).

📌 Why This Is Important:

Understanding how Python processes your code step by step helps you:

• Read and understand other people’s code

• Write better programs yourself

• Debug problems when something goes wrong

How to Declare a Variable and Check Its Value?

A variable is like a container that stores a value (like a number, a word, or any data). You give it a name, and Python remembers the value for you.

To declare (create) a variable:

age = 25
name = "Ahmed"

• age stores the number 25

• name stores the word “Ahmed”

To inspect (see) the value of a variable:

You can use print():

print(age)
print(name)

🖥️ Output:

25
Ahmed

💬 How to Write Comments in Python

Comments are notes you write in your code to explain what you are doing.
Python ignores them when running the code; they are just for you (or others) to understand better.

✍️ Single-line comment:

Comments in Python start with #. When comments start on a new line, they are called block comments, while comments that appear on the same line as code are called inline comments.

# This is a block comment
age = 30  # This stores the person's age/ inline comment

📌Why comments matter:

They help you and others understand your code, especially as projects grow in length and complexity.

Real-Life Examples

Let's look at two examples to see how Python can help us solve simple problems.

🩺 Example 1: Medical Scenario – Checking patient information

# Storing patient information
patient_name = "Mariam"
patient_age = 45

# Printing the information
print("Patient Name:", patient_name)
print("Patient Age:", patient_age)

🖥️ Output:

Patient Name: Mariam
Patient Age: 45

📌What this shows: How to store and print data, which is useful for building medical record systems later.

🏡 Example 2: Daily To-Do List

# Storing tasks for the day
task1 = "Check emails"
task2 = "Attend Python class"
task3 = "Go for a walk"

# Printing the to-do list
print("Today's Tasks:")
print(task1)
print(task2)
print(task3)

🖥️ Output:

Today's Tasks:
Check emails
Attend Python class
Go for a walk

📌What this shows: How Python can help organize everyday routines by storing and displaying tasks.

🧪 Exercise: Create a Simple Patient Profile Program

🩺 Scenario:

You’re working at a health center, and you need to quickly print out a patient’s basic information to share with a nurse. You will store and display the patient’s details using Python.

🎯 What to do:

1. Create variables to store the following:

   • Patient's full name

   • Age

   • Gender

   • Department (e.g., Pediatrics, Cardiology, etc.)

   • Hospital name

2. Use the print() function to display all the information clearly.

3. Add comments to explain what each part of the code is doing.

📝 Example Output:

Patient Information
--------------------
Name: Amina Yusuf
Age: 29
Gender: Female
Department: Dermatology
Hospital: Sunrise Medical Center

💡 Bonus Tip (Optional):

You can also add a short welcome message at the top using print() — like:

print("Welcome to Sunrise Medical Center")

📩 After you finish, please send a screenshot of your exercise to this email: saja@sajamedtech.com

🚀What’s Coming in Episode 5?

In the next episode, we will explore variables and data types.

💬 Let me know in the comments or messages:
- What setup did you use to run your first code?
- What do you want to build with Python?

Don’t forget to subscribe to Hashnode to get a notification when the next episode is released.

See you tomorrow!

In this article, we will set up your Python environment so you are ready to start coding in the next episode, whether you are using a laptop, a smartphone, or just want to code in your browser.

I will provide you with several setup options, including my personal favorite.
You can choose the option that best suits your device, your learning style, and your goals.
This way, you can stick with the setup that works best for you, not just for today, but for all the upcoming episodes.

🟢 Before We Begin

In the last episode, we talked about what Python is and described it as a popular, beginner-friendly programming language known for its clear and easy-to-read syntax. In this lesson, there is another important term you should know: "IDE" or "Integrated Development Environment."

What does it mean? An IDE is a software application that gives you everything you need to write, run, and debug code, all in one place. Think of it like a digital desk for coding. It usually includes a code editor, a terminal/console, and tools for testing and debugging.

There are many types of IDEs, such as VS (Visual Studio) Code, PyCharm, and Anaconda's Jupyter Notebook. In this episode, I will focus on two IDEs: Visual Studio Code and Anaconda's Jupyter Notebook.

📌 Note: If you are using your smartphone, skip Anaconda and Visual Studio Code because these options only work on computers. Check out Option 4 instead.

Let’s get started!

🧰 Option 1: Anaconda (Easiest for Beginners)

If you want everything pre-installed (Python + Jupyter + Python libraries), Anaconda is a complete all-in-one environment.

🛠 Steps:

1. Download Anaconda from https://www.anaconda.com/products/distribution.

   They will ask you to provide an email to download the Distribution. After you provide your it, check your email inbox, as they will send the download link to your email.

   

2. Make Sure to choose Distribution Installers:

   

3. Follow the installer (for Windows or Mac)

4. Open Anaconda Navigator and launch Jupyter Notebook

Anaconda IDE usually comes with

• Python

• Jupyter: allows you to write and run code in small sections, known as "cells."

• Pandas, NumPy, Matplotlib, and many more libraries.

  Don’t worry if you don’t understand what these libraries are right now; we will discuss them more in future episodes.

✅ In this option, you don’t need to install Python and an IDE separately. All are included!

🧰 Option 2: Python + VS Code (My Preferred Setup)

Personally, I prefer downloading Python from python.org and using Visual Studio Code (VS Code) as my code editor “IDE“.

Why? Because VS Code:

• Is lightweight, fast, and clean

• Is used by many professionals and developers

• Prepares you for more advanced coding and projects

🛠 Steps:

1. Go to https://www.python.org and download the latest version of Python

   

2. Important: During installation, check the box that says “Add Python to PATH”

   

After installation, open Command Prompt or Terminal.

🍎 On Mac: How to Open Terminal

1. Press Command + Spacebar to open Spotlight Search

2. Type Terminal and hit Enter

3. A white or black window will open with a line like:

Your-Mac:~ yourname$

💻 On Windows: How to Open Command Prompt

1. Click the Start Menu (Windows icon in the bottom-left corner)

2. Type cmd in the search bar

3. Click on Command Prompt (you'll see a black window open)

📌 It will look like this:

3. After opening Command Prompt (Windows) or Terminal (Mac), type the following and press Enter:

    python --version
   

4. You should see something like Python 3.13.5. This confirms that Python was installed successfully and shows the version you have.

5. After installing Python, download Visual Studio Code from https://code.visualstudio.com

   

6. After setup, open VS Code, go to Extensions, search for Python, and install the one by Microsoft.

   

7. Now, you are ready to create and run your .py files! (We'll talk about this in the next episode.)

✅ If you’re ready to dive deeper into programming with more control, this setup is a great place to start!

🧰 Option 3: Google Colab (No Installation Needed)

Want to start right away in your browser without downloading anything?
Use Google Colab, which runs Python in your browser.

🛠 Steps:

1. Go to colab.research.google.com

2. Sign in with your Google account

3. Click “New Notebook”

4. Start writing Python instantly!

✅ Pros:

• No installation

• Works on any device

• Saves your notebooks directly to Google Drive

📱 Option 4: Using Your Smartphone?

If you don’t have access to a computer, you can still start learning Python on your Android or iOS device.

📲 Android:

• Download Pydroid 3 from the Google Play Store

• Open the app and start writing Python

• Beginner-friendly and works offline

🍎 iPhone/iPad:

• Download Pyto (free) or Pythonista 3 (paid) from the App Store

• These apps allow you to run and test Python code directly on your iOS device

📅 What’s Coming in Episode 4?

In the next episode, we’ll write your first real Python code together:

• Print your first message

• Try a mini-medical example

• Build confidence, one line at a time

💬 Let me know in the comments which setup you chose and why? I’d love to hear from you!

https://sajamedtech.com/#contact

And don’t forget to subscribe to the series on Hashnode to get notified the moment the next episode goes live.

Whether you're a medical student, a healthcare worker, or just someone curious about programming, you're exactly where you need to be.

Today, we’ll explore:

💬 What is Python?

🤔 Why should you learn it, even if you’ve never written a line of code?

So, What Is Python?

Python is a popular, high-level programming language that’s known for being:

✅ Simple to Learn: You don’t need to memorize weird symbols or complex rules to get started. Python reads almost like plain English, perfect for beginners.

print("Hello, future medical coder!")

This single line displays a message on the screen: "Hello, future medical coder!" Simple, right?

In some other programming languages, the syntax can be difficult to learn, like this Java code:

public class HelloMedicalCoder {
    public static void main(String[] args) {
        System.out.println("Hello, future medical coder");
    }
}

So frustrating with so many symbols and words, right?

✅ Easy to Read: You’ll spend more time understanding the logic behind coding and less time figuring out syntax. That makes learning smoother and less frustrating.

✅ Powerful Enough for Anything: Although Python is easy for beginners, it's also used by major companies like Google, NASA, and hospitals to create complex tools, including AI, healthcare platforms, and data analysis systems.

👩‍⚕️ Why Python Is Relevant to You?

You might be wondering: “I’m not a tech person. Why should I learn this?”

Here’s why Python is useful in medicine and real life:

🏥 In Healthcare:

🌍 In Real Life:

🔍 Real-Life Examples of Python in Action

🩺 Example 1 — Healthcare: Identifying Patients with Fever

Imagine this:
You're on a hospital ward with five patients, quickly checking and noting their temperatures.

36.5, 37.2, 38.6, 39.1, 36.8

Now you want to identify which patients have a fever (anything above 38°C). Instead of checking each one by hand, calculating, and writing it down, you can simply ask Python: “Can you tell me which patients have a fever?”

And Python replies:

Patients with fever: 38.6, 39.1

✅ Simple, fast, and accurate.

🎓 Example 2 — Education: Predicting Which Students May Need Help

Imagine this:
You're a teacher reviewing your students' midterm grades and whether they passed the final exam:

Midterm Grades: 45, 60, 75, 85, 50  
Passed Final Exam (1 = Yes, 0 = No): 0, 0, 1, 1, 0

Now, a new student scores 70 on their midterm. You're wondering: “Will this student likely pass the final exam, or should I give them extra support?”

You ask Python: “Based on the past grades, what’s your prediction?”

And Python replies:

Prediction: Student with grade 70 → Likely to pass ✅

🧠 Your Challenge for Today

You don’t need to code anything today.

Just answer this: “What’s one small, boring, or repetitive task you’d love to automate in your daily life?”

Coming up with a real idea gives your learning a purpose. When you eventually write code, it’ll feel meaningful, not random or abstract.

Write down your idea and share it with me using the following link:

https://sajamedtech.com/#contact

📅 What’s Coming Tomorrow?

In Episode 3, we’ll finally get started with:

🔧 How to set up and install the Python environment.

See you tomorrow in Episode 3 of The Medical Coder’s Path! 💻🩺

Ever since I was in middle school, I have been fascinated by technology. I remember being curious about computers, software, and how digital tools work. While most of my classmates were focused on traditional paths, I found myself drawn to anything that had to do with computers or software. But when it came time to choose a career path, I took a different road; I entered medical school.

During my journey in medicine, I was genuinely fascinated by the science of the human body, diseases, and how healthcare works. I enjoyed the subject learning, studying, and understanding, but when it came to real-life hospital work, I realized something important: it didn’t feel like my path. While I respected the clinical side of medicine, I couldn’t see myself doing it long-term: the patient follow-ups, the hospital rotations, and the constant hustle.

At the same time, there was something else growing quietly in the background: my love for technology. Every time I had a break from studies, whether during vacations or weekends, I would find myself diving into online courses, exploring programming tools, and learning how technology works. It wasn’t just a hobby anymore; it became a part of who I am. I kept thinking about how powerful it would be if I could combine both worlds: healthcare and coding.

Now, years later, I have found my path more clearly than ever. And that is what this blog series is about: bringing together medicine and programming in a way that’s simple, approachable, and exciting.

🩺 What This Series Is About

This series is for medical students, graduates, and healthcare professionals who feel like I once did, curious about tech, unsure where to start, and eager to make an impact beyond the hospital walls.

Over the next 30 days, I will guide you through the basics of Python, one of the easiest and most useful programming languages to learn.

We'll keep it:

• ✅ Simple and beginner-friendly

• 🩺 Focused on healthcare-relevant examples

• 🧠 Practical with hands-on mini challenges

• 🌱 Motivation to keep going

📅 What’s Coming Up Tomorrow?

In Episode 2, we’ll start with the very basics:

💬 What is Python? Why do so many people in healthcare, AI, and research use it?

🙌 Let’s Learn Together

You don’t need to be a programmer. You just need a bit of curiosity, and you already have that if you’re reading this.

So let’s learn together, one day at a time, one line of code at a time.
This is The Medical Coder’s Path, and I’m so excited you’re here.

See you tomorrow! 👩‍⚕️👨‍💻