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Day-2 – Python Fast Track for Developers (C# → AI mode)

Now we need to learn basics of python . Not deeply but only what needed to AI/ML. Today session also we divided into 3 parts: 

Part-1 : Python Basics for Developers

1️⃣ Variables

C#:

int age = 30;
string name = "Test";

Python:

age = 30

name = "Test"

👉 No type declaration. Dynamic typing.

2️⃣ Lists (Like C# List<T>)

Python:

numbers = [1, 2, 3, 4]
names = ["UT", "AI", "Engineer"]

Access:

print(numbers[0])

Loop:

for num in numbers:
print(num)

3️⃣ Dictionaries (Like C# Dictionary<TKey, TValue>)

Python:

user = {

    "name": "UT",

    "age": 30

}

print(user["name"])

4️⃣ Functions

C#:

string Greet(string name)

{

    return $"Hello {name}";

}

Python:

def greet(name):

    return f"Hello {name}"

print(greet("Test"))

5️⃣ If-Else

Python:

if age > 18:

    print("Adult")

else:

    print("Minor")

Indentation = Important in Python ⚠


Part-2 : Virtual Environment + Packages

1️⃣ Create Virtual Environment

Open terminal:

python -m venv venv

Activate:

Windows:

venv\Scripts\activate

2️⃣ Install Packages

pip install numpy pandas matplotlib scikit-learn jupyter

These are core ML libraries.

3️⃣ Start Jupyter Notebook

jupyter notebook

Create:
day2_python_basics.ipynb

OR

Another best option is - If you dont want to install anything on your laptop or if you want to practice on your office laptop then use Google Colab - which is browser specific & best for running python code, that requires no setup and runs entirely in the cloud.

For more info watch this Video: https://youtu.be/0N0NuVKWhDA


Part 3 - Mini Practice

Inside Jupyter or Colab, write this:

Task-1

Create list of numbers 1–10
Print only even numbers

Task-2

Create dictionary:

student = {

    "name": "UT",

    "marks": [80, 85, 90]

}

Calculate average marks.

Task-3

Create function:

  1. Takes list

  2. Returns sum


Github Link: You can copy all code from below github link:



🧠 Important Mindset Today:

We are NOT becoming: Python developer 

We are becoming: AI Engineer 


🎯 End of Day-2 Deliverables

✅ Python installed
✅ Virtual environment created
✅ Jupyter running
✅ Basic script written
✅ Pushed to GitHub (Week1 folder)


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