MITx: Introduction to Computer Science and Programming Using Python (Free Course)

 An introduction to computer science as a tool to solve real-world analytical problems using Python 3.5.

About this course

This course is the first of a two-course sequence: Introduction to Computer Science and Programming Using Python, and Introduction to Computational Thinking and Data Science. Together, they are designed to help people with no prior exposure to computer science or programming learn to think computationally and write programs to tackle useful problems. Some of the people taking the two courses will use them as a stepping stone to more advanced computer science courses, but for many it will be their first and last computer science courses. This run features lecture videos, lecture exercises, and problem sets using Python 3.5. Even if you previously took the course with Python 2.7, you will be able to easily transition to Python 3.5 in future courses, or enroll now to refresh your learning.

Since these courses may be the only formal computer science courses many of the students take, we have chosen to focus on breadth rather than depth. The goal is to provide students with a brief introduction to many topics so they will have an idea of what is possible when they need to think about how to use computation to accomplish some goal later in their career. That said, they are not "computation appreciation" courses. They are challenging and rigorous courses in which the students spend a lot of time and effort learning to bend the computer to their will

What you'll learn

A Notion of computation

The Python programming language

Some simple algorithms

Testing and debugging

An informal introduction to algorithmic complexity

Data structures

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Python Coding challenge - Day 42 | What is the output of the following Python code?

 

A step-by-step explanation of the code: 

for i in range(1):

    print(i, end=' ')

We have a for loop that iterates over the values in the range created by range(1). The range(1) generates a sequence of numbers from 0 up to, but not including, 1. Since it only includes one value (0), the loop will run only once.

In the loop, the variable i takes on the value of 0, which is the only value generated by range(1).

Inside the loop, we have the print statement. This statement prints the current value of i, which is 0. The end parameter is set to a space (' '), which means it will print a space after the value of i.

After printing the value of i (0) with a space character after it, the loop completes its one and only iteration.

So, the code will output: 0

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Introduction to Python (Free Course)

 

Python is a general-purpose programming language that is becoming ever more popular for data science. Companies worldwide are using Python to harvest insights from their data and gain a competitive edge. Unlike other Python tutorials, this course focuses on Python specifically for data science. In our Introduction to Python course, you’ll learn about powerful ways to store and manipulate data, and helpful data science tools to begin conducting your own analyses. Start DataCamp’s online Python curriculum now. 

Python Basics

An introduction to the basic concepts of Python. Learn how to use Python interactively and by using a script. Create your first variables and acquaint yourself with Python's basic data types. 

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Python Coding challenge - Day 41 | What is the output of the following Python code?

 

Solution - 

for k in range(3, 9, 2):

    print(k, end=' ')

The code begins with a for loop that specifies a loop variable k. It is used to iterate over a range of values.

The range(3, 9, 2) function is used to define the range of values for k. The three arguments inside range are:

Start: 3

Stop: 9 (the loop will stop before reaching 9)

Step: 2 (the increment between each value)

The loop is designed to iterate through the values generated by range(3, 9, 2).

In the first iteration of the loop, k takes the value 3. It then proceeds to the next iteration.

In the second iteration, k takes the value 5. It continues to the next iteration.

In the third and final iteration, k takes the value 7. The loop has reached the end of the specified range.

Inside the loop, the print statement is used to display the current value of k. The end=' ' argument is specified to ensure that a space character is added after each value.

After printing each value of k, the loop continues to the next iteration.

Once the loop has finished all iterations, the program completes, and the output is displayed.

The output of this code is: 3 5 7

It shows the values of k (3, 5, and 7) separated by space characters as specified in the print statement.

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Data Science Math Skills (Free Course)

 

There are 5 modules in this course

Data science courses contain math—no avoiding that! This course is designed to teach learners the basic math you will need in order to be successful in almost any data science math course and was created for learners who have basic math skills but may not have taken algebra or pre-calculus. Data Science Math Skills introduces the core math that data science is built upon, with no extra complexity, introducing unfamiliar ideas and math symbols one-at-a-time. 

Learners who complete this course will master the vocabulary, notation, concepts, and algebra rules that all data scientists must know before moving on to more advanced material.

Topics include:

~Set theory, including Venn diagrams

~Properties of the real number line

~Interval notation and algebra with inequalities

~Uses for summation and Sigma notation

~Math on the Cartesian (x,y) plane, slope and distance formulas

~Graphing and describing functions and their inverses on the x-y plane,

~The concept of instantaneous rate of change and tangent lines to a curve

~Exponents, logarithms, and the natural log function.

~Probability theory, including Bayes’ theorem.

While this course is intended as a general introduction to the math skills needed for data science, it can be considered a prerequisite for learners interested in the course, "Mastering Data Analysis in Excel," which is part of the Excel to MySQL Data Science Specialization.  Learners who master Data Science Math Skills will be fully prepared for success with the more advanced math concepts introduced in "Mastering Data Analysis in Excel." 

Good luck and we hope you enjoy the course!

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Python Coding challenge - Day 40 | What is the output of the following Python code?

 

This Python code will iterate over the list lis using a for loop. Within each iteration, it will unpack the sublists into the variables p and q. Then it will print the sum of p and q followed by an ampersand (&). Let's go through the steps:

p and q will take the values from the sublists in lis successively.

In the first iteration, p will be 8 and q will be 7. The sum will be 15. So, it will print 15&.

In the second iteration, p will be 6 and q will be 5. The sum will be 11. So, it will print 11&.

Therefore, the output of the code will be: 15&11&

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Learn Python in One Day and Learn It Well Python for Beginners with Hands-on Project The only book you need to start coding in Python immediately (Second Edition) By Jamie Chan (Free PDF)

 

(2nd Edition: Covers Object Oriented Programming) Learn Python Fast and Learn It Well. Master Python Programming with a unique Hands-On Project

Have you always wanted to learn computer programming but are afraid it'll be too difficult for you? Or perhaps you know other programming languages but are interested in learning the Python language fast? This book is for you. You no longer have to waste your time and money learning Python from lengthy books, expensive online courses or complicated Python tutorials.

What this book offers...

Python for Beginners Complex concepts are broken down into simple steps to ensure that you can easily master the Python language even if you have never coded before. Carefully Chosen Python Examples Examples are carefully chosen to illustrate all concepts. In addition, the output for all examples are provided immediately so you do not have to wait till you have access to your computer to test the examples. Careful selection of topics Topics are carefully selected to give you a broad exposure to Python, while not overwhelming you with information overload. These topics include object-oriented programming concepts, error handling techniques, file handling techniques and more. Learn The Python Programming Language Fast Concepts are presented in a "to-the-point" style to cater to the busy individual. With this book, you can learn Python in just one day and start coding immediately.

How is this book different...

The best way to learn Python is by doing. This book includes a complete project at the end of the book that requires the application of all the concepts taught previously. Working through the project will not only give you an immense sense of achievement, it"ll also help you retain the knowledge and master the language. Are you ready to dip your toes into the exciting world of Python coding? This book is for you. With the first edition of this book being a #1 best-selling programming ebook on Amazon for more than a year, you can rest assured that this new and improved edition is the perfect book for you to learn the Python programming language fast. Click the BUY button and download it now.

What you'll learn:

- What is Python? - What software you need to code and run Python programs? - What are variables? - What are the common data types in Python? - What are Lists and Tuples? - How to format strings - How to accept user inputs and display outputs - How to control the flow of program with loops - How to handle errors and exceptions - What are functions and modules? - How to define your own functions and modules - How to work with external files - What are objects and classes - How to write your own class - What is inheritance - What are properties - What is name mangling .. and more... Finally, you'll be guided through a hands-on project that requires the application of all the topics covered. Click the BUY button and download the book now to start learning Python. Learn it fast and learn it well.

BUY - Python (2nd Edition): Learn Python in One Day and Learn It Well. Python for Beginners with Hands-on Project. (Learn Coding Fast with Hands-On Project Book 1)

PDF - Learn Python in One Day and Learn It Well Python for Beginners with Hands-on Project The only book you need to start coding in Python immediately (Second Edition) By Jamie Chan (Free PDF)

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Learning Python: Learn to code like a professional with Python - an open source, versatile, and powerful programming language

Learn to code like a professional with Python - an open source, versatile, and powerful programming language

Key Features

• Learn the fundamentals of programming with Python - one of the best languages ever created
• Develop a strong set of programming skills that you will be able to express in any situation, on every platform, thanks to Python's portability
• Create outstanding applications of all kind, from websites to scripting, and from GUIs to data science

Book Description

Learning Python has a dynamic and varied nature. It reads easily and lays a good foundation for those who are interested in digging deeper. It has a practical and example-oriented approach through which both the introductory and the advanced topics are explained. Starting with the fundamentals of programming and Python, it ends by exploring very different topics, like GUIs, web apps and data science. The book takes you all the way to creating a fully fledged application.

The book begins by exploring the essentials of programming, data structures and teaches you how to manipulate them. It then moves on to controlling the flow of a program and writing reusable and error proof code. You will then explore different programming paradigms that will allow you to find the best approach to any situation, and also learn how to perform performance optimization as well as effective debugging. Throughout, the book steers you through the various types of applications, and it concludes with a complete mini website built upon all the concepts that you learned. 

What you will learn

• Get Python up and running on Windows, Mac, and Linux in no time
• Grasp the fundamental concepts of coding, along with the basics of data structures and control flow.
• Write elegant, reusable, and efficient code in any situation
• Understand when to use the functional or the object oriented programming approach
• Create bulletproof, reliable software by writing tests to support your code
• Explore examples of GUIs, scripting, data science and web applications
• Learn to be independent, capable of fetching any resource you need, as well as dig deeper

Who this book is for

Python is the most popular introductory teaching language in U.S. top computer science universities, so if you are new to software development, or maybe you have little experience, and would like to start off on the right foot, then this language and this book are what you need. Its amazing design and portability will help you become productive regardless of the environment you choose to work with.

Table of Contents

1. Introduction and first steps - Take a deep breath
2. Built-in data types
3. Iterating and making decisions
4. Functions, the building blocks of code
5. Saving time and memory
6. Advanced Concepts - OOP, Decorators, Iterators
7. Testing, Profiling and dealing with Exceptions
8. The edges: GUIs and Scripts
9. Data Science
10. Web Development done right
11. Debugging and troubleshooting
12. Summing up: a complete example

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Python Coding challenge - Day 39 | What is the output of the following Python code?

 

The code is a simple Python while loop that starts with the variable cl set to 4. It increments cl by 1 in each iteration and prints the updated value of cl followed by a hyphen ("-") until cl is no longer less than 9. Here's the output of the code: 5-6-7-8-9-

The loop starts with cl equal to 4, and in each iteration, it increments cl by 1. When cl reaches 9, the loop stops because the condition cl < 9 is no longer true.

 step by step solutions 

Initialize the variable cl with the value 4:

cl = 4

Start a while loop with the condition cl < 9. This means the loop will continue as long as cl is less than 9.

Inside the loop, increment the value of cl by 1. This is done using the cl = cl + 1 statement:

cl = cl + 1

Print the updated value of cl, followed by a hyphen (-) without moving to the next line due to the end parameter:

print(cl, end='-')

The loop will continue to the next iteration or exit the loop depending on whether the condition cl < 9 is still true.

The loop repeats steps 3-5 until the condition cl < 9 is no longer true. When cl becomes equal to 9, the loop exits.

Here's the output produced by the code, showing each step:

Step 1: cl = 4

Step 2: Entering the while loop with the condition cl < 9 (4 < 9 is true)

Step 3: Incrementing cl by 1, cl is now 5

Step 4: Printing 5 with an end of '-', output so far: 5-

Step 2: Entering the while loop with the condition cl < 9 (5 < 9 is true)

Step 3: Incrementing cl by 1, cl is now 6

Step 4: Printing 6 with an end of '-', output so far: 5-6-

Step 2: Entering the while loop with the condition cl < 9 (6 < 9 is true)

Step 3: Incrementing cl by 1, cl is now 7

Step 4: Printing 7 with an end of '-', output so far: 5-6-7-

Step 2: Entering the while loop with the condition cl < 9 (7 < 9 is true)

Step 3: Incrementing cl by 1, cl is now 8

Step 4: Printing 8 with an end of '-', output so far: 5-6-7-8-

Step 2: Entering the while loop with the condition cl < 9 (8 < 9 is true)

Step 3: Incrementing cl by 1, cl is now 9

Step 4: Printing 9 with an end of '-', output so far: 5-6-7-8-9-

Step 2: Exiting the while loop as the condition cl < 9 is no longer true

The final output is 5-6-7-8-9-, which is the result of running the code.

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IBM Data Analyst Professional Certificate

 Prepare for a career as a data analyst. Gain the in-demand skills and hands-on experience to get job-ready in as little as 4 months. No prior experience required.

What you'll learn

Master the most up-to-date practical skills and tools that data analysts use in their daily roles

Learn how to visualize data and present findings using various charts in Excel spreadsheets and BI tools like IBM Cognos Analytics & Tableau

Develop working knowledge of Python language for analyzing data using Python libraries like Pandas and Numpy, and invoke APIs and Web Services 

Gain technical experience through hands on labs and projects and build a portfolio to showcase your work

Prepare for a career in Data Analytics

Receive professional-level training from IBM

Demonstrate your proficiency in portfolio-ready projects

Earn an employer-recognized certificate from IBM

Qualify for in-demand job titles: Data Analyst, Associate Data Analyst, Business Analyst

JOIN - IBM Data Analyst Professional Certificate

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Python Coding challenge - Day 38 | What is the output of the following Python code?

 

py = 2 + 3: In this line, you're creating a variable named py and assigning it the result of the addition of 2 and 3, which is 5. So, py now holds the value 5.

print('py'): In this line, you are using the print() function to display the string 'py'. This code will not print the value of the variable py but will directly print the string 'py' as it is enclosed in single quotes.

Here's your code with step-by-step explanations: 

# Step 1: Calculate the sum of 2 and 3

py = 2 + 3  # py is assigned the value 5

# Step 2: Print the string 'py'

print('py')   # This will print the string 'py' to the console

When you run this code, it will print the string 'py' to the console, not the value stored in the variable py.

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Cybersecurity for Everyone (Free Course)

 

There are 6 modules in this course

Cybersecurity affects everyone, including in the delivery of basic products and services. If you or your organization want to better understand how to address your cybersecurity, this is the course for you and your colleagues to take -- from seasoned professionals to your non-technical colleagues.

Your instructor, Dr. Charles Harry, has served on the front lines with the NSA (National Security Agency) and as an expert advising corporate and institutional leaders on managing cybersecurity risk. And he brings a rare and engaging perspective to help you learn cybersecurity from the ground up.

Cybersecurity for Everyone lays the groundwork to understand and explore the key issues facing policy makers attempting to manage the problem of cybersecurity, from its technical foundations to the domestic and international policy considerations surrounding governance, privacy, and risk management, to applications for achieving the goals of an enterprise, an institution, or a nation. This course is designed for students with some or no background in information technology, whether a novice or active in the cybersecurity field (engineers and computer scientists will learn the broader context and business aspects of cybersecurity), and will provide the principles to understand the current debates shaping a rapidly evolving security landscape.

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Python Coding challenge - Day 37 | What is the output of the following Python code?

 

Solutions - 

In the code a function f that takes two parameters, value and values. The function then modifies the value at the first index of the values list to be 44 and assigns 1 to a variable v, but this v variable is not used anywhere in the function.

After defining the function f, you have a variable t set to 3 and a list v with three elements: [1, 2, 3]. You then call the function f with the arguments t and v, and finally, you print the values of t and the first element of v after the function call.

Here's a step-by-step explanation of what happens:

t is initially set to 3.

v is initially set to [1, 2, 3].

The function f is called with the arguments t and v.

Inside the function, the value at the first index of the values list (which is the same list as v) is modified to be 44. So, v becomes [44, 2, 3]. However, the variable v declared in the function and set to 1 is not used.

After the function call, you print the values of t and the first element of v, which is v[0].

As a result, when you run the code, it will print: 3 44

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Using Databases with Python

 

What you'll learn

Use the Create, Read, Update, and Delete operations to manage databases

Explain the basics of Object Oriented Python

Understand how data is stored across multiple tables in a database

Utilize the Google Maps API to visualize data

Build your subject-matter expertise

This course is part of the Python for Everybody Specialization

When you enroll in this course, you'll also be enrolled in this Specialization.

Learn new concepts from industry experts

Gain a foundational understanding of a subject or tool

Develop job-relevant skills with hands-on projects

Earn a shareable career certificate

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Introduction to Image Generation (Free Course)

 

What you'll learn

How diffusion models work

Real use-cases for diffusion models

Unconditioned diffusion models

Advancements in diffusion models (text-to-image)

There is 1 module in this course

This course introduces diffusion models, a family of machine learning models that recently showed promise in the image generation space. Diffusion models draw inspiration from physics, specifically thermodynamics. Within the last few years, diffusion models became popular in both research and industry. Diffusion models underpin many state-of-the-art image generation models and tools on Google Cloud. This course introduces you to the theory behind diffusion models and how to train and deploy them on Vertex AI. 

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Python Coding challenge - Day 36 | What is the output of the following Python code?

 

Solutions - 

# Define the input string

input_string = 'cd'

# Use the partition method to split the string

result = input_string.partition('cd')

# The 'result' variable now contains a tuple with three elements

# Element 0: The part of the string before the partitioned substring

# Element 1: The partitioned substring itself

# Element 2: The part of the string after the partitioned substring

# Print the result

print(result)

In this case, the input string is 'cd', and the partition method is used to split it into three parts. The print statement will display the following result: ('', 'cd', '')

Here's a breakdown of the result:

Element 0 is an empty string '' because there is nothing before the partitioned substring 'cd' in the input string.

Element 1 is the partitioned substring itself, which is 'cd'.

Element 2 is an empty string '' because there is nothing after the partitioned substring 'cd' in the input string.

This is the expected output when using the partition method with 'cd' as both the input string and the partitioned substring.

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Python Coding challenge - Day 35 | What is the output of the following Python code?

 

i = 0  # Initialize the variable i to 0

while i < 3:  # Start a while loop that continues while i is less than 3

    print(i)  # Print the current value of i

    i += 1  # Increment i by 1

# The while loop will run three times:

# 1. i is 0, so it prints 0 and increments i to 1.

# 2. i is 1, so it prints 1 and increments i to 2.

# 3. i is 2, so it prints 2 and increments i to 3.

else:  # After the while loop is finished, execute the else block

    print(0)  # Print 0

# The else block is executed once after the while loop is done.

# The output will be:

# 0

# 1

# 2

# 0Here's the step-by-step explanation of what happens:

Initialize i to 0.

The while loop checks if i is less than 3, which is true since i is 0.

It enters the loop and prints the current value of i, which is 0.

It then increments i by 1, making it 1.

The loop iterates again since i (1) is still less than 3. It prints 1.

i is incremented to 2, and the loop continues. It prints 2.

After the third iteration, i becomes 3, and the condition i < 3 is no longer true.

The loop terminates, and the code in the else block is executed, which prints 0.

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HarvardX: CS50's Introduction to Programming with Python (Free Course)

 

An introduction to programming using Python, a popular language for general-purpose programming, data science, web programming, and more. 

About this course

An introduction to programming using a language called Python. Learn how to read and write code as well as how to test and "debug" it. Designed for students with or without prior programming experience who'd like to learn Python specifically. Learn about functions, arguments, and return values (oh my!); variables and types; conditionals and Boolean expressions; and loops. Learn how to handle exceptions, find and fix bugs, and write unit tests; use third-party libraries; validate and extract data with regular expressions; model real-world entities with classes, objects, methods, and properties; and read and write files. Hands-on opportunities for lots of practice. Exercises inspired by real-world programming problems. No software required except for a web browser, or you can write code on your own PC or Mac.

Whereas CS50x itself focuses on computer science more generally as well as programming with C, Python, SQL, and JavaScript, this course, aka CS50P, is entirely focused on programming with Python. You can take CS50P before CS50x, during CS50x, or after CS50x. But for an introduction to computer science itself, you should still take CS50x!

What you'll learn

1. Functions, Variables
2. Conditionals
3. Loops
4. Exceptions
5. Libraries
6. Unit Tests
7. File I/O
8. Regular Expressions
9. Object-Oriented Programming
10. Et Cetera

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What is the difference between deep copy and shallow copy in Python, and how can you create each type for a nested list?

In Python, a deep copy and a shallow copy are two different ways to duplicate a list (or any mutable object) with potentially different behaviors when it comes to nested objects. Here's the difference between them and how you can create each type for a nested list:

Shallow Copy:

A shallow copy creates a new object, but it doesn't create copies of the objects within the original object. Instead, it copies references to those objects. This means that changes made to objects inside the copied list will also affect the original list and vice versa if those objects are mutable.

You can create a shallow copy using the copy module's copy() function or by using the slicing [:] notation.

Example of creating a shallow copy:

import copy

original_list = [[1, 2, 3], [4, 5, 6]]

shallow_copied_list = copy.copy(original_list)

# Now, both original_list and shallow_copied_list share the same sublists.

shallow_copied_list[0][0] = 100

print(original_list)  # Output: [[100, 2, 3], [4, 5, 6]]

Deep Copy:

A deep copy, on the other hand, creates a completely independent copy of the original object and all objects contained within it, recursively. This means changes to objects within the copied list won't affect the original list and vice versa.

You can create a deep copy using the copy module's deepcopy() function.

Example of creating a deep copy:

import copy

original_list = [[1, 2, 3], [4, 5, 6]]

deep_copied_list = copy.deepcopy(original_list)

# Modifying the deep_copied_list won't affect the original_list.

deep_copied_list[0][0] = 100

print(original_list)  # Output: [[1, 2, 3], [4, 5, 6]]

In summary, the main difference between deep copy and shallow copy lies in their behavior with nested objects. A shallow copy shares references to nested objects, while a deep copy creates completely independent copies of the entire object hierarchy, ensuring that changes in one do not affect the other. The choice between them depends on your specific use case and whether you want shared or independent copies of nested objects. 

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Python Coding challenge - Day 34 | What is the output of the following Python code?

 

1.0 / 3: This part of the code calculates the division of 1.0 by 3, which is equal to approximately 0.3333333333333333.

'{}' is a string containing a placeholder enclosed in curly braces {}. In this case, {0:.2f} is the placeholder. The 0 inside the curly braces is used to specify the index of the argument to be inserted into the placeholder, and .2f is a format specifier.

:.2f is the format specifier inside the placeholder. Here's what it means:

: separates the index (in this case, 0) from the format specifier.

.2 specifies that you want to display the floating-point number with exactly two decimal places.

f indicates that you want to format the number as a floating-point number.

.format(...): This is the .format() method of the string. It's used to replace the placeholder {0:.2f} with the value of 1.0 / 3 formatted according to the specified format.

When you run this code, the 1.0 / 3 is calculated, resulting in the floating-point number 0.3333333333333333. Then, the .format() method takes this value and formats it to display only two decimal places, resulting in "0.33". Finally, the print() function displays "0.33" to the console.

So, the output of this code is: 0.33 

It formats the result of the division operation to have exactly two decimal places and prints it.

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Python Coding challenge - Day 33 | What is the output of the following Python code?

 

def myfunc(a):

    a = a + 2  # Step 1: Add 2 to the value of 'a' and store it back in 'a'

    a = a * 2  # Step 2: Multiply the updated 'a' by 2 and store it back in 'a'

    return a   # Step 3: Return the final value of 'a'

result = myfunc(2)  # Calling the 'myfunc' function with the argument 2

print(result)       # Printing the result

Here's a detailed explanation of each step:

def myfunc(a):: This line defines a function named myfunc that takes a single argument a.

a = a + 2: Inside the function, this line adds 2 to the value of a. In the context of the function call myfunc(2), a initially has a value of 2, so this line updates a to 4.

a = a * 2: Next, this line multiplies the updated value of a by 2. Since a was updated to 4 in the previous step, this line further updates a to 8.

return a: Finally, the function returns the value of a, which is now 8.

result = myfunc(2): Outside the function, we call myfunc(2) and store the result (which is 8) in a variable named result.

print(result): Finally, we print the value of result, which is 8, to the console.

So, when you run this code, it will output 8 because myfunc(2) performs a series of operations on the input value 2 and returns the result, which is 8.

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Python Coding challenge - Day 32 | What is the output of the following Python code?

 

i = 0  # Initialize the variable i to 0

while i < 3:  # Start a while loop that continues as long as i is less than 3

    print(i)  # Print the current value of i

    i += 1  # Increment the value of i by 1

    print(i + 1)  # Print the value of i + 1 after the increment

Let's break it down step by step:

i = 0: We initialize a variable i and set its initial value to 0.

while i < 3:: This line starts a while loop. The loop will continue executing as long as the value of i is less than 3. In other words, the loop will run when i is 0, 1, or 2, and it will exit when i becomes 3 or greater.

print(i): Inside the loop, we print the current value of i. The first time through the loop, this will print 0.

i += 1: After printing the value of i, we increment its value by 1. So, i changes from 0 to 1.

print(i + 1): We then print the value of i + 1. Since i is now 1, this line will print 2.

The loop returns to the top, and the process repeats if i is still less than 3. In this case, i is still less than 3 (i.e., 1 is less than 3), so the loop continues.

The second iteration of the loop starts with i equal to 1.

print(i): We print the current value of i, which is 1.

i += 1: We increment i by 1, making it equal to 2.

print(i + 1): We print i + 1, which is now 3.

The loop continues for one more iteration with i equal to 2.

print(i): We print 2.

i += 1: We increment i to 3.

print(i + 1): We print i + 1, which is 4.

The loop condition i < 3 is no longer satisfied because i is now equal to 3. Therefore, the loop exits.

So, the output of this code will be as follows: 0 2 1 3 2 4

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Python Coding challenge - Day 31 | What is the output of the following Python code?

 

In the above code a lambda function z that takes an argument x and multiplies it by the value of y, which is set to 8. Then, you call this lambda function with the argument 6 and print the result.

Here's a step-by-step breakdown of what happens:

y = 8: You define a variable y and assign it the value 8.

z = lambda x: x * y: You define a lambda function z that takes an argument x and multiplies it by the value of y. Essentially, it's equivalent to the following regular function definition:

def z(x):

    return x * y

print(z(6)): You call the lambda function z with the argument 6, and it performs the multiplication: 6 * 8, resulting in 48. Then, you print the result, so the output will be: 48

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Python Coding challenge - Day 30 | What is the output of the following Python code?

 

In this line of code, you create a Python list called L containing four elements: 'a', 'b', 'c', and 'd'. This list is stored in memory.

Here's what this line of code does:

" ": This part " " is an empty string. It's used as a separator between the elements of the list when joining them together. In this case, it's an empty string, so there will be no space or any other character between the joined elements.

.join(L): This is a method call on the empty string " ". The join() method is used to concatenate the elements of a list into a single string, with the string used as a separator. In this case, the elements of the list L ('a', 'b', 'c', 'd') will be joined together with an empty string as the separator.

print(...): Finally, the print() function is used to display the result of the join operation. The result, which is the concatenation of the elements in L without any separators, is printed to the console.

So, when you run this code, you'll see the following output: abcd

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Mastering Python Data Structures: From Basics to Advanced

Table of Contents

Chapter 1: Introduction to Data Structures

Chapter 2: Variables and Built-in Types

Chapter 3: Lists and Tuples in Depth

Chapter 4: Sets and Dictionaries

Chapter 5: Strings and Regular Expressions

Chapter 6: Numerical Computing with NumPy

Chapter 7: Stacks and Queues

Chapter 8: Linked Lists

Chapter 9: Trees and Graphs

Chapter 10: Searching and Sorting Algorithms

Chapter 11: Dynamic Programming

Chapter 12: Graph Algorithms

Chapter 13: Algorithmic Techniques

Chapter 14: Advanced Data Structures

Chapter 15: Advanced Algorithms

Chapter 16: Computational Complexity

Chapter 17: Advanced Python Topics

Chapter 18: Python in Web Development

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Google Advanced Data Analytics Professional Certificate

 

What you'll learn

Explore the roles of data professionals within an organization 

Create data visualizations and apply statistical methods to investigate data

Build regression and machine learning models to analyze and interpret data

Communicate insights from data analysis to stakeholders

1. Foundations of Data Science
2. Get Started with Python
3. Go Beyond the Numbers: Translate Data into Insights
4. The Power of Statistics
5. Regression Analysis: Simplify Complex Data Relationships
6. The Nuts and Bolts of Machine Learning
7. Google Advanced Data Analytics Capstone

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Google IT Automation with Python Professional Certificate

What you'll learn

Automate tasks by writing Python scripts

Use Git and GitHub for version control

Manage IT resources at scale, both for physical machines and virtual machines in the cloud 

Analyze real-world IT problems and implement the appropriate strategies to solve those problems

Professional Certificate - 6 course series

This beginner-level, six-course certificate, developed by Google, is designed to provide IT professionals with in-demand skills -- including Python, Git, and IT automation -- that can help you advance your career.
Knowing how to write code to solve problems and automate solutions is a crucial skill for anybody in IT.
This program builds on your IT foundations to help you take your career to the next level. It’s designed to teach you how to program with Python and how to use Python to automate common system administration tasks. You'll also learn to use Git and GitHub, troubleshoot and debug complex problems, and apply automation at scale by using configuration management and the Cloud.
This certificate can be completed in about 6 months and is designed to prepare you for a variety of roles in IT, like more advanced IT Support Specialist or Junior Systems Administrator positions. 
We recommend that you have Python installed on your machine. For some courses, you’ll need a computer where you can install Git or ask your administrator to install it for you.

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Python Coding challenge - Day 29 | What is the output of the following Python code?

 

The above code uses the pop() method on a list. Let's break it down step by step:

You have a list named cl with the following elements: [2, 3, 1].

You call the pop(2) method on the list cl. The pop() method in Python is used to remove and return an element from a list at a specified index. In this case, you're specifying index 2, which corresponds to the third element in the list (Python uses zero-based indexing).

The pop(2) method removes the element at index 2, which is the number 1, from the list cl.

The pop(2) method also returns the value that was removed, which is the number 1.

The print() function is used to display the value returned by cl.pop(2). So, it will print 1.

After executing this code, the list cl will be modified to [2, 3], and the number 1 will be printed to the console.

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Understanding Machine Learning with Python 3

 

Use your data to predict future events with the help of machine learning. This course will walk you through creating a machine learning prediction solution and will introduce Python, the scikit-learn library, and the Jupyter Notebook environment.

What you'll learn

Hello! My name is Jerry Kurata, and welcome to Understanding Machine Learning with Python. In this course, you will gain an understanding of how to use Python for Machine Learning. You will get there by covering major topics like:

How to format your problem to be solvable

How to prepare your data for use in a prediction

How to combine that data with algorithms to create models that can predict the future

By the end of this course, you will be able to use Python and the scikit-learn library to create Machine Learning solutions. And you will understand how to evaluate and improve the performance of the solutions you create.

Before you begin, make sure you are already familiar with software development and basic statistics. However, your software experience does not have to be in Python, since you will learn the basics in this course.

When you use Python together with scikit-learn, you will see why this is the preferred development environment for many Machine Learning practitioners. You will do all the demos using the Jupyter Notebook environment. This environment combines live code with narrative text to create a document with can be executed and presented as a web page.

I hope you’ll join me, and I look forward to helping you on your learning journey here at Pluralsight.

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Data Science Challenge (Free Course)

Data Science Challenge 

Duration - Less than 2 hours

Cost - Free

This project requires you to independently complete the following steps:

1.  Importing and preprocessing data

2. Analyze the data

3. Build machine learning models

4. Evaluate machine learning models

Join now - Data Science Challenge (Free Course)

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Python Functions, Files, and Dictionaries (Free Course)

What you'll learn

• Explore the dictionary data structure and user-defined functions in Python.
• Understand concepts like local and global variables, parameter-passing techniques, named functions, and lambda expressions.
• Apply Python's sorted function and control sorting order with custom functions.
• Create a final project involving social media data analysis and CSV file manipulation.

Build your subject-matter expertise

• This course is part of the Python 3 Programming Specialization
• When you enroll in this course, you'll also be enrolled in this Specialization.
• Learn new concepts from industry experts
• Gain a foundational understanding of a subject or tool
• Develop job-relevant skills with hands-on projects
• Earn a shareable career certificate

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Python Coding challenge - Day 28 | What is the output of the following Python code?

 

In the above code a list a initially defined as [2, 5, 3, 4]. Then, you are trying to insert the value 2 into the list at index 2:2, which is essentially inserting it at position 2 without replacing any existing elements. Here's what happens step by step:

a is initially defined as [2, 5, 3, 4].

a[2:2] = [2] inserts the value 2 into the list a at position 2 without replacing any existing elements.

When you print a, it will display the modified list.

So, when you print a after this operation, you will get the following output: [2, 5, 2, 3, 4]

The value 2 has been inserted at index 2, and the elements after index 2 have been shifted to accommodate the new value.

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IBM: Python Basics for Data Science (Free Course)

 

This Python course provides a beginner-friendly introduction to Python for Data Science. Practice through lab exercises, and you'll be ready to create your first Python scripts on your own!

About this course

Please Note: Learners who successfully complete this IBM course can earn a skill badge — a detailed, verifiable and digital credential that profiles the knowledge and skills you’ve acquired in this course. Enroll to learn more, complete the course and claim your badge!

What you'll learn

The objectives of this course is to get you started with Python as the programming language and give you a taste of how to start working with data in Python.

In this course you will learn about:

• What Python is and why it is useful
• The application of Python to Data Science
• How to define variables in Python
• Sets and conditional statements in Python
• The purpose of having functions in Python
• How to operate on files to read and write data in Python
• How to use pandas, a must have package for anyone attempting data analysis in Python.

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Harvard University: CS50's Introduction to Cybersecurity (Free Course)

 

About this course

This is CS50's introduction to cybersecurity for technical and non-technical audiences alike. Learn how to protect your own data, devices, and systems from today's threats and how to recognize and evaluate tomorrow's as well, both at home and at work. Learn to view cybersecurity not in absolute terms but relative, a function of risks and rewards (for an adversary) and costs and benefits (for you). Learn to recognize cybersecurity as a trade-off with usability itself. Course presents both high-level and low-level examples of threats, providing students with all they need know technically to understand both. Assignments inspired by real-world events.

What you'll learn

• hacking, cracking
• social engineering, phishing attacks
• passcodes, passwords, SSO
• brute-force attacks, dictionary attacks
• biometrics
• multi-factor authentication, password managers
• ethical hacking
• (distributed) denial-of-service attacks
• viruses, worms, botnets
• SQL injection attacks
• port-scanning
• proxies, firewalls
• automatic updates
• closed-source, open-source software
• buffer-overflow attacks
• secure deletion
• hashing, salting
• secret-key, public-key encryption, digital signatures
• full-disk encryption, ransomware
• cookies, sessions, incognito mode
• anonymization, de-identification
• verification
• operating systems, app stores

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Data Processing Using Python (Free Course)

 



Welcome to learn Data Processing Using Python!

Module 2. Basics of Python

Module 3. Data Acquisition and Presentation

Module 4. Powerful Data Structures and Python Extension Libraries

Module 5. Python Data Statistics and Mining

Module 6.  Object Orientation and Graphical User Interface

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Introduction to Generative AI (Free Course)

 

What you'll learn

• Define Generative AI
• Explain how Generative AI works
• Describe Generative AI Model Types
• Describe Generative AI Applications

This is an introductory level microlearning course aimed at explaining what Generative AI is, how it is used, and how it differs from traditional machine learning methods. It also covers Google Tools to help you develop your own Gen AI apps.

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Python Coding challenge - Day 27 What is the output of the following Python code?

 

Solutions - 

The above code will extend the list x with individual characters from the string '234', resulting in the list x containing each character as a separate element. Here's the code execution step by step:

x = ['1']: Initializes the list x with one element, which is the string '1'.

x.extend('234'): Extends the list x with the characters from the string '234'. After this line of code, the list x will contain the following elements: ['1', '2', '3', '4'].

print(x): Prints the contents of the list x, which will output: ['1', '2', '3', '4']

So, the final result is a list containing the string '1' and the characters '2', '3', and '4' as separate elements.

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Python Coding challenge - Day 26 What is the output of the following Python code?

 

Solutions - 

The above code uses Python's slice notation to extract a portion of the string s using the slice object x. Here's how it works: 

• s = 'clcoding': This line initializes a string variable s with the value 'clcoding'.
• x = slice(1, 4): This line creates a slice object x that specifies a slice from index 1 (inclusive) to index 4 (exclusive). In other words, it selects the characters at positions 1, 2, and 3 in the string s.
• print(s[x]): This line uses the slice object x to extract the characters from the string s according to the specified slice. The characters at positions 1, 2, and 3 in the string 'clcoding' are 'lco', and these characters are printed to the console.

So, when you run the code, it will output: lco

The slice s[x] extracts the characters from index 1 to 3 (4 is exclusive) in the string 'clcoding', which are 'lco'.

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Learn Python Quickly: A Complete Beginner’s Guide to Learning Python, Even If You’re New to Programming: Crash Course with Hands-On Project, Book

FREE Book 📙 

 Looking to learn Python?

Python has gone to be one of the most popular programming languages in the world, and you will be one of the few people left out if you don’t add this knowledge to your arsenal. If you’re looking to learn Python, now is an excellent time to do so. But where do you begin?

You can start right here, right now, with this audiobook. It makes learning Python simple, fast, and easy, taking away the confusion from learning a new language. When learning a new language, it's easy to be overwhelmed and not know where to start or what to focus on. You can spend a long time pursuing tutorials online only to find out you don't really understand any of the concepts they covered. That won't be a problem here! This audiobook follows a step-by-step guide, walking you through everything you need to know about Python in an easy to follow fashion. It will teach you all the basics of Python, and even some of the more advanced Python concepts, taking you from beginner to intermediate Python programmer.

This audiobook will give you:

• A solid foundation in Python programming.
• Intermediate and advanced topics once you’ve mastered the basics.
• Simple explanations of code, broken down into easy to follow steps.
• Python programming exercises and solutions.
• Two projects at the end of the audiobook designed to help you bring all the concepts you’ve learned together.
• Source code files you can refer to and run on your computer.

The exercises in this audiobook are designed to help you practice using the skills you’ve learned in the various sections. The final two projects will let you practice putting everything you’ve learned together and teaching you how to manipulate text, work with images, and create a simple Graphical User Interface (GUI).

Link - Learn Python Quickly: A Complete Beginner’s Guide to Learning Python, Even If You’re New to Programming: Crash Course with Hands-On Project, Book

This audiobook will help you master the following topics:

• Working with Python in both the command line and an Integrated Development Environment (IDE)
• Variables and operators
• Python data types
• Python data structures
• Handling inputs and outputs
• Getting user inputs
• Conditional/control flow statements
• Error handling
• Functions, parameters, and scope
• Built-in function
• Creating modules
• Object-oriented programming
• Reading and writing files
• Recursion
• Image handling

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Python Coding challenge - Day 25 What is the output of the following Python code?

 

The above code will split the string r into a list using the default whitespace separator, but since there are no whitespace characters in the string '123', it will not split the string, and you will get a list with the original string as its only element. Here's the output you would get: ['123']

The split() method without any arguments splits a string by whitespace characters (spaces, tabs, newlines, etc.). Since '123' contains no whitespace characters, it remains as a single element in the list. If you want to split '123' into individual digits, you can use an empty string as the argument to the split() method like this:

r = '123'

print(r.split(''))

However, this will raise an error because an empty string cannot be used as a separator. If you want to split '123' into individual characters as strings, you can do it like this:

r = '123'

split_list = list(r)

print(split_list)

This will output:

['1', '2', '3']

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Regular Expressions in Python

 

What you'll learn

Construct regex patterns

Validate passwords and user input in web forms

Extract patterns and replace strings with regex

Learn step-by-step

In a video that plays in a split-screen with your work area, your instructor will walk you through these steps:

Introduction to Regular Expressions in Python

Intermediate Regular Expressions in Python

Password Validation with Regular Expressions

Form and User Input Validation with Regular Expressions

Extraction and Word Replacement from Server Logs 

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Clean and analyze social media usage data with Python

 

Objectives

Increase client reach and engagement

Gain valuable insights that will help improve social media performance

Achieve their social media goals and provide data-driven recommendations

Project plan

This project requires you to independently complete the following steps:

• Import required libraries
• Generate random data for the social media data
• Load the data into a Pandas DataFrame and explore the data
• Clean the data
• Visualize and analyze the data

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