The document provides an overview of an internship report submitted by Sayan Laskar. During the internship, Sayan completed an online Python course offered by Google and Coursera. The course covered fundamental Python programming concepts like syntax, data types, control structures, functions, and object-oriented programming. Sayan gained skills in Python programming, basic syntax, data structures, and fundamental programming concepts. The report includes details of the weekly topics covered during the course and the skills learned.

1. DEPARTMENT OF ELECTRONICS AND TELE-COMMUNICATION
ENGINEERING
TRIPURAINSTITUTEOFTECHNOLOGY
(AnAutonomousInstitution)
RecognizedbyAICTE,PermanentlyAffiliatedtoTripuraUniversity,Tripura.
Agartala,WestTripura 2023–
2024
INTERNSHIPREPORT
UnderSupervision of
(Duration:16/07/23 to 18/08/23)
Submitted by
Sayan laskar
Rollno:226304027
ELECTRONICANDTELE-COMMUNICATIONENGINEERING

2. CERTIFICATE
This is to certify that the “Internship Report” submitted by sayan laskar(Registration.
No:2022-018637) is work done by her and submitted during 2023–24 academic year, in partial
fulfilment of the requirements for the internship report in crash course on python

3. ACKNOWLEDGEMENT
I would like to extend my sincere gratitude to Google and Coursera for offering the
comprehensive Python course. The learning experience provided through this course has been
invaluable in enhancing my understanding of Python programming.
The well-structured curriculum, interactive learning materials, and practical exercises have
immensely contributed to my proficiency in Python. The dedication of the instructors and the support
of the learning community have made this learning journey both enriching and rewarding.
I am grateful for the opportunity to delve into Python programming through this course,
enabling me to broaden my skill set and empowering me to apply this knowledge in real-world
scenarios.
Thank you, Google and Coursera, for providing a platform that fosters continuous learning
and skill development.
Sincerely,
[sayan laskar]

4. INDEX
SlNo.CONTENTS
1. Introduction
2. Softwarerequirementsspecifications
2.1 Systemconfiguration
2.2 Softwarerequirements
2.3 Hardwarerequirements
3. SKILL I GAIN
Python programming
Basic python syntax
Basic python data structures
Object oriented programming(OOP)
Fundamental programming concepts
What I learn
Understand what python is and why python is relevant to automation
Write short scripts to perform automated action
Understand how to use the basic python :string ,lists,and dictionaries
Create your own python object
4. Conclusion
5. Bibliography

5. Weekly overview of Internship Activities:
DATE DAY
NAME OF TOPICS / MODULE
COMPLETED
16/07/23 MONDAY
SPECILATION INTRODUCTION ,COURSE
INTRODUCTION
17/07/23 TUESDAY POGRAM SURVEYS ,GOOGLE CERT
PARTICIPANT ENTRY SURVEY
18/07/23 WEDNESDAY
TAKE A MINUTE TO SET YOURSELF UP
FOR SUCCESS
19/07/23 THURSDAY
WELCOM TO THE COURSE
20/07/23 FRIDAY
MEET A GREAT

6. DATE
23/07/23 MONDAY
24/07/23 TUESDAY
25/07/23 WEDNESDAY
26/07/23 THURSDAY
27/07/23 FRIDAY
DAY
NAME OF TOPICS / MODULE
COMPLETED
MONDAY
BASIC PYTHON SYNTAX
INTRODUCTION,DATA TYPS,VARIABLES
TUESDAY
EXPRESSION NUMBER AND TYPE
CONVERSIONS
WEDNESDAY
IMPLICIT VS EXPLICIT CONVERSION
THURSDAY
STUDY GUID EXPRESSIONS AND
VARIABLES
FRIDAY
PRACTICE QUIZ EXPRESSIONS AND
VARIABLES
NAME OF TOPICS / MODULE
,VARIABLES
EXPRESSION NUMBER AND TYPE
IMPLICIT VS EXPLICIT CONVERSION
EXPRESSIONS AND
PRACTICE QUIZ EXPRESSIONS AND

7. DATE
7/08/23 MONDAY
8/08/23 TUESDAY
9/08/23 WEDNESDAY
10/08/23 THURSDAY
11/08/23
DAY
NAME OF TOPICS / MODULE
COMPLETED
MONDAY
WHAT IS A FOR LOOP,A CLOSER LOOK AT
THE RANGE () FUNCATION,NESTED FOR
LOOPS ,COMMON ERROS IN FOE LOOPS
TUESDAY
BASIC STRUCTURES
INTRODUCTION,WHAT IS A STRING ? THE
PART OF A STRING,STRING INDEXING AND
SLICING,CREATING NEW STRING,BASIC
STRING MATHODS ,ADVANCE STRING
MRTHODS,FORMATTING STRINGS
WEDNESDAY
STRING INDXING AND SLICING,CREATING
NEW STRING,BASIC STRING
METHODS,MORE STRING METHODS
THURSDAY
STRING REFRRENCE
GUIDE,FORMATTING STRING GUIDE
FRIDAY
STUDY GUIDE STRINGS,PRACTICE QUIZ
NAME OF TOPICS / MODULE
COMPLETED
WHAT IS A FOR LOOP,A CLOSER LOOK AT
THE RANGE () FUNCATION,NESTED FOR
LOOPS ,COMMON ERROS IN FOE LOOPS
INTRODUCTION,WHAT IS A STRING ? THE
,STRING INDEXING AND
SLICING,CREATING NEW STRING,BASIC
STRING MATHODS ,ADVANCE STRING
MRTHODS,FORMATTING STRINGS
STRING INDXING AND SLICING,CREATING
NEW STRING,BASIC STRING
G METHODS
GUIDE,FORMATTING STRING GUIDE
STUDY GUIDE STRINGS,PRACTICE QUIZ

8. DATE DAY
NAME OF TOPICS / MODULE
COMPLETED
14/08/23 MONDAY
FINAL PROJECT
INTRODUCTION,PROBLEM STETMENT
15/08/23 TUESDAY
RESEARCH
16/08/23 WEDNESDAY PLANNING
17/08/23 THURSDAY WRITING THE SCRIPT
18/08/23 FRIDAY PUTTING IT ALL TOGETHER
18/08/23 FRIDAY TEST

10. 1. INTRODUCTION
Welcome to the Python Essentials course! This course is designed to provide you with a comprehensive
understanding of Python programming from the ground up. Whether you're new to programming or
looking to expand your skills, this course will equip you with the fundamental knowledge necessary to
become proficient in Python.

11. 2. SOFTWAREREQUIREMENTSSPECIFICATIONS
2.1 Systemconfigurations
Thesoftwarerequirementspecificationwasverylessaswewereperformingverybasictasks. But the
institute provided us a good machine for each of us and a good internet connection.
2.2 Softwarerequirements:
OperatingSystem:Windows8andabove
Web Server: Googlr Coursera
2.3 HardwareRequirements:
Processor :Intelcorei5/Ryzen5
Memory :8GBRAM
HardDiskSSD :512GB

12. 3.SKILLS I AM GAIN
3.1 PYTHON / PYTHON PROGRAMMING
Python programming is a high-level, versatile language renowned for its simplicity and readability. Its
ease of learning and powerful capabilities make it a popular choice for various applications across
diverse fields.
Notable features of Python include its:
Clear and Readable Syntax: Python emphasizes code readability, employing indentation for block
delimiters rather than relying on braces or keywords. This characteristic makes it easy for beginners to
grasp and write code.
Versatility: Python finds application in web development, data analysis, scientific computing, artificial
intelligence, automation, and more. Its extensive libraries and frameworks support a wide array of
functionalities.
Rich Ecosystem: The language boasts a vast ecosystem of libraries and packages, such as NumPy,
Pandas, TensorFlow, and Django, enabling users to efficiently tackle complex tasks without reinventing
the wheel.
Interpretation and Dynamism: Python is an interpreted language, allowing for rapid development and
immediate execution of code. Its dynamic typing system provides flexibility by inferring variable types
during runtime.
Community Support: Python benefits from a vibrant and welcoming community, offering extensive
documentation, tutorials, forums, and online resources. This support network makes it easier for
developers to seek help and collaborate on projects.
Overall, Python's blend of simplicity, power, and community support renders it an excellent choice for
both beginners and seasoned developers alike, empowering them to create robust and innovative
solutions across various domains.

13. 3.2 BASIC PYTHON SYNTAX
Clear and Readable Syntax: Python emphasizes code readability, employing indentation for block
delimiters rather than relying on braces or keywords. This characteristic makes it easy for beginners to
grasp and write code.
Versatility: Python finds application in web development, data analysis, scientific computing, artificial
intelligence, automation, and more. Its extensive libraries and frameworks support a wide array of
functionalities.
Rich Ecosystem: The language boasts a vast ecosystem of libraries and packages, such as NumPy,
Pandas, TensorFlow, and Django, enabling users to efficiently tackle complex tasks without reinventing
the wheel.
Interpretation and Dynamism: Python is an interpreted language, allowing for rapid development and
immediate execution of code. Its dynamic typing system provides flexibility by inferring variable types
during runtime.
Community Support: Python benefits from a vibrant and welcoming community, offering extensive
documentation, tutorials, forums, and online resources. This support network makes it easier for
developers to seek help and collaborate on projects.
Overall, Python's blend of simplicity, power, and community support renders it an excellent choice for
both beginners and seasoned developers alike, empowering them to create robust and innovative
solutions across various domains. Python, known for its readability and simplicity, employs
straightforward syntax, making it accessible for beginners and conducive to rapid development.
Key Elements:
Comments:
Denoted by #, used to annotate code for explanation or clarification. Comments are ignored during
execution.
python
# This is a comment
Variables and Assignments:
Variables are containers for storing data. Python uses dynamic typing, enabling variables to hold
different data types.
python
x = 5 # Integer assignment
y = 3.14 # Float assignment
name = "Python" # String assignment
Print Statement:
Used to display output. print() function can handle various data types and expressions.

14. python
print("Hello, world!")
Indentation:
Python uses indentation to define blocks of code (e.g., loops, conditional statements, functions).
Indentation is crucial for the interpreter to understand the code structure.
python
if x > 0:
print("Positive number")
else:
print("Non-positive number")
Control Structures:
Python uses colons (:) and indentation to signify the start and end of control structures like loops and
conditional statements.
python
for i in range(5):
print(i)
if condition:
# do something
else:
# do something else
Basic Data Types:
Python supports fundamental data types like integers, floats, strings, booleans, lists, tuples, dictionaries,
and sets.
python
num = 10 # Integer
pi = 3.14 # Float
name = "Python" # String
is_valid = True # Boolean
my_list = [1, 2, 3] # List
Python's syntax emphasizes readability and simplicity, making it an ideal language for beginners while
maintaining power and flexibility for more advanced users.

15. BASIC PYTHON DATA STRACTURES
Python offers several fundamental data structures to organize and manipulate data efficiently.
1. Lists:
Ordered collection of elements.
Mutable (can be changed after creation).
Elements can be of different types.
python
my_list = [1, 2, 'hello', 3.14]
2. Tuples:
Similar to lists but immutable (cannot be changed after creation).
Often used for fixed collections.
python
my_tuple = (1, 2, 'world', 3.14)
3. Dictionaries:
Unordered collection of key-value pairs.
Access elements via keys (like a dictionary word-definition system).
python
my_dict = {'name': 'Alice', 'age': 30, 'city': 'New York'}
4. Sets:
Unordered collection of unique elements.
Useful for mathematical set operations like union, intersection, difference.
python
my_set = {1, 2, 3, 4, 4, 2} # Results in {1, 2, 3, 4}
Operations:
Accessing Elements:
Lists, tuples, and dictionaries use indexing or keys to access elements.
Sets cannot be indexed; use set operations to manipulate them.
Manipulating Data:
Lists and dictionaries can be modified (adding, removing, updating elements).
Tuples and sets are immutable but can be manipulated indirectly.
Choosing Data Structures:
Lists: Ideal for ordered collections where elements might change.
Tuples: Use for fixed collections or situations requiring immutability.
Dictionaries: Perfect for key-value pair storage and quick lookup.
Sets: For collections requiring unique elements or set operations.
Python's versatile data structures cater to various programming needs, allowing efficient organization and
manipulation of data in different contexts.

16. OBJECT ORIENTED POGRAMMING (OOP)
Object-Oriented Programming is a programming paradigm that revolves around the concept of objects,
which bundle data and functions that operate on the data into a single entity. In Python, everything is an
object.
Key Concepts:
Classes and Objects:
Class: Blueprint or template defining the structure and behavior of objects.
Object: An instance of a class, representing a specific entity.
python
class Car:
def _init_(self, make, model):
self.make = make
self.model = model
my_car = Car("Toyota", "Corolla")
Attributes and Methods:
Attributes: Data stored within a class or object.
Methods: Functions defined inside a class to manipulate its attributes.
python
class Dog:
def _init_(self, name):
self.name = name
def bark(self):
return f"{self.name} says woof!"
my_dog = Dog("Buddy")
print(my_dog.bark()) # Outputs: "Buddy says woof!"
Encapsulation:
Encapsulation hides the internal state of objects and restricts direct access to certain components.
Access specifiers like public, private, and protected control access to attributes and methods.
python
class BankAccount:
def _init_(self, account_number, balance):
self._account_number = account_number # Protected attribute
self.__balance = balance # Private attribute
def get_balance(self):
return self.__balance # Private attribute accessed via method
Inheritance:
Inheritance allows a class (child) to inherit properties and behaviors from another class (parent).
Helps in reusability and structuring code hierarchically.
python
class Vehicle:
def drive(self):
return "Vehicle is being driven"

17. class Car(Vehicle):
pass # Inherits drive() method from Vehicle class
Polymorphism:
Polymorphism allows objects of different classes to be treated as objects of a common parent class.
Enables flexibility and abstraction.
python
class Animal:
def make_sound(self):
pass
class Dog(Animal):
def make_sound(self):
return "Woof!"
class Cat(Animal):
def make_sound(self):
return "Meow!"
Object-Oriented Programming in Python enables developers to create well-structured, reusable, and
scalable code by organizing data and functionalities into objects and classes.
FUNDEMENTAL OF POGRAMMING CONCEPTS
Variables and Data Types:
Variables: Containers to store data. They can hold various data types such as integers, floats, strings,
booleans, etc.
Data Types: Categories of data values. Examples include numbers, strings, lists, and dictionaries.
2. Control Structures:
Conditional Statements: Used to perform different actions based on certain conditions (e.g., if, else,
elif).
Loops: Repeatedly execute a block of code until a condition is met (e.g., for loops, while loops).
3. Functions:
Functions: Blocks of reusable code that perform specific tasks. They improve code readability,
reusability, and maintainability.
4. Data Structures:
Lists, Tuples, Dictionaries: Structures to organize and manipulate data efficiently.
Arrays, Sets: Other structures for specific data handling needs.
5. Algorithms:
Algorithms: Step-by-step procedures or formulas used to solve problems. They are essential for
computation and data processing.
6. Input and Output:
Input: Obtaining data from users or external sources.
Output: Displaying results or information to users or external systems.
7. Error Handling:
Exceptions: Errors that occur during program execution.
Try-Except Blocks: Handling and managing exceptions gracefully to prevent program crashes.
8. Modularity and Reusability:
Modularity: Breaking code into smaller, manageable components (functions, classes) for easier
maintenance and understanding.
Reusability: Writing code that can be reused in different parts of the program or in other programs.

18. 9. Comments and Documentation:
Comments: Notes within the code to explain functionality or clarify sections.
Documentation: Comprehensive explanations, often external to the code, detailing how code works.
10. Testing and Debugging:
Testing: Evaluating code functionality to ensure it behaves as expected.
Debugging: Identifying and fixing errors or bugs in the code.
Understanding these fundamental programming concepts lays the groundwork for writing clean,
efficient, and maintainable code in any programming language

19. WHY I AM LEARN
UNDERSTEND WHAT PYTHON IS AND WHY PYTHONIS RELEVENT AUTOMATION
Python is a high-level, versatile programming language known for its simplicity and readability. It's an
open-source language with a clear and concise syntax, making it beginner-friendly while offering
powerful capabilities for developers.
Why is Python Relevant in Automation?
Simplicity and Readability:
Python's straightforward syntax and readability simplify code creation and maintenance, reducing
development time and effort.
Vast Ecosystem and Libraries:
Python offers an extensive array of libraries and frameworks tailored for automation tasks. For
instance:
Selenium: Automation for web browser interactions.
Requests: Simplified HTTP requests and API interaction.
OpenCV: Image processing and computer vision automation.
PyAutoGUI: Automating mouse and keyboard interactions.
Cross-Platform Compatibility:
Python is platform-independent, running seamlessly on various operating systems. This allows
automation scripts written in Python to function across different environments.
Community and Support:
Python boasts a large, active community that constantly contributes to libraries, offering extensive
documentation, tutorials, and forums. This support network aids in troubleshooting and innovation.
Versatility and Integration:
Python seamlessly integrates with other languages and tools, making it suitable for building complex
automation pipelines involving diverse technologies.
Rapid Prototyping and Development:

20. Python's agility enables quick prototyping and iteration, crucial in fast-paced automation development
cycles.
Scalability and Performance:
Though Python is known for ease of use, it also provides scalability and performance enhancements
through optimization techniques and use of compiled modules.
WRITE PYTHON SCRIPTS TO PERFORM AUTOMATED ACTION
1. Automation with Web Interaction (Using Selenium):
Objective: Automating browser actions like form filling, button clicks, and data extraction from
websites.
Example Script (Using Selenium):
python
from selenium import webdriver
# Launch Chrome browser
driver = webdriver.Chrome()
# Open a webpage
driver.get('https://example.com')
# Interact with elements
search_box = driver.find_element_by_name('q')
search_box.send_keys('Python automation')
search_box.submit()
# Perform actions
# ...
# Close the browser
driver.quit()
2. File Handling and Automation:
Objective: Automating file operations such as reading, writing, and manipulating files.
Example Script (File Manipulation):
python
file
with open('data.txt', 'r') as file:
data = file.read()
# Writing to a file
with open('output.txt', 'w') as file:
file.write('Automated content')
# Manipulating data
# ...
3. Automating System Tasks:

21. Objective: Automating system-related actions like managing processes, scheduling tasks, or interacting
with the operating system.
Example Script (System Task Automation):
python
import os
# Execute a system command
os.system('mkdir new_directory')
# Schedule tasks (using external libraries like schedule)
# ...
4. Automating Data Processing and Analysis:
Objective: Automating data-related tasks such as data extraction, processing, and analysis.
Example Script (Data Processing):
python
import pandas as pd
# Read data from a CSV file
data = pd.read_csv('data.csv')
# Perform data manipulation
# ...
# Analyze data
# ...
5. Automating Repetitive Tasks:
Objective: Automating any repetitive tasks to save time and minimize manual efforts.
Example Script (Repetitive Task Automation):
python
import pyautogui
import time
# Automated mouse and keyboard interactions
pyautogui.moveTo(100, 100, duration=1)
pyautogui.click()
time.sleep(2)
pyautogui.typewrite('Automating tasks with Python!')
UNDERSTAND HOW TO USE THE BASIC PYTHON STRUCTURS : STRIN,LIST,AND
DICTIONARIES
1. Strings:
Definition: Strings are sequences of characters enclosed in single, double, or triple quotes.
Example:
python
message = "Hello, Python!"

22. Operations:
Concatenation: Combining strings using the + operator.
Indexing and Slicing: Accessing individual characters or portions of strings.
Methods: String-specific functions for operations like formatting, searching, and manipulation (len(),
upper(), lower(), replace(), split(), etc.).
2. Lists:
Definition: Lists are ordered collections of items, enclosed in square brackets [ ], separated by commas.
Example:
python
numbers = [1, 2, 3, 4, 5]
fruits = ['apple', 'banana', 'orange']
Operations:
Indexing and Slicing: Accessing individual elements or subsets of lists.
Appending and Removing: Modifying lists by adding or removing elements (append(), remove(), pop(),
etc.).
List Comprehensions: Creating lists using concise and readable syntax.
3. Dictionaries:
Definition: Dictionaries are unordered collections of key-value pairs enclosed in curly braces { }.
Example:
python
student = {'name': 'Alice', 'age': 25, 'grade': 'A'}
Operations:
Accessing Values: Retrieving values by using their associated keys.
Adding and Modifying: Adding new key-value pairs or modifying existing ones.
Methods: Dictionary-specific functions (keys(), values(), items()) for various operations.
Common Operations for All Structures:
Iteration: Using loops to iterate through elements.
Membership Testing: Checking if an element exists within the structure using in or not in.
Length: Finding the length of the structure using len().
Choosing the Right Structure:
Use strings for handling text data.
Use lists for collections of items where order matters.
Use dictionaries for mapping unique keys to values.
CREATE YOUR OWN PYTHON OBJECT
Classes:
Definition: Classes are user-defined blueprints for creating objects. They encapsulate data and behavior.
Example:
python
class Car:
def _init_(self, make, model):
self.make = make
self.model = model
def display_info(self):
return f"{self.make} {self.model}"
2. Instances:
Definition: Instances are individual objects created from a class.
Creating Instances:
python
my_car = Car("Toyota", "Corolla")

23. 3. Attributes and Methods:
Attributes: Variables specific to each instance, storing data related to the object.
Methods: Functions defined inside a class, used to perform operations on the object's data.
4. Constructor (_init_ method):
The _init_ method initializes instance attributes when an object is created.
It is called automatically when creating an instance of the class.
5. Accessing Attributes and Methods:
Accessing Attributes: Done using dot notation (object.attribute).
Accessing Methods: Invoked similarly using dot notation (object.method()).
6. Inheritance:
Definition: Inheritance allows a class (child) to inherit attributes and methods from another class
(parent).
Example:
python
class ElectricCar(Car):
def _init_(self, make, model, battery_size):
super()._init_(make, model)
self.battery_size = battery_size
7. Encapsulation:
Encapsulation restricts direct access to some of the object's components, typically by using private
attributes.
8. Class and Instance Variables:
Class Variables: Shared among all instances of a class.
Instance Variables: Specific to each instance.
9. Polymorphism:
Definition: Allows objects of different classes to be treated as objects of a common parent class.
CONCLUSION:
In conclusion, I can say this internship is very useful experience for me. I’ve
learnedmanyimportantthingsabout CRASH COURSE ON PYTHON one-month
Internship Program ONLINE. I would like to thank our internship mentor for
providing us such good knowledge about the topics, and hopefully this knowledge
and skills will help me out in the future
ThankYou

24. BIBLIOGRAPHY
Thisbooks&websiteshelpmealotduringtheprogram: BOOKS
1. PYTHON ALL AIN ONE BY JOHN SHOVIC
2. LEARNING WITH PYTHON ALLEN DOWNEY
WEBLINKS
1. https://wiki.python.org
2. https://thepythoncodingbook.com