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Programming Tutorial | Introduction, Basic Concepts, Getting started, Problems

This comprehensive guide of Programming Tutorial or Coding Tutorial provides an introduction to programming, covering basic concepts, setting up your development environment, and common beginner problems. Learn about variables, data types, control flow statements, functions, and how to write your first code in various languages. Explore resources and tips to help you to begin your programming journey. We designed this Programming Tutorial or Coding Tutorial to empower beginners and equip them with the knowledge and resources they will need to get started with programming.

Programming Tutorial

1. What is Programming?

Programming , also known as coding , is the process of creating a set of instructions that tell a computer how to perform a specific task. These instructions, called programs, are written in a language that the computer can understand and execute.

Table of Content

• What is Programming?
• Getting Started with Programming
• Common Programming Mistakes and How to Avoid Them
• Basic Programming EssentialsA Beginner’s Guide to Programming Fundamentals
• Advanced Programming Concepts
• Writing Your First Code
• Top 20 Programs to get started with Coding/Programming
• Next Steps after learning basic Coding/Programming
• Resources and Further Learning
• Frequently Asked Questions (FAQs) on Programming Tutorial

Think of programming as giving commands to a robot. You tell the robot what to do, step-by-step, and it follows your instructions precisely. Similarly, you tell the computer what to do through code, and it performs those tasks as instructed.

The purpose of programming is to solve problems and automate tasks. By creating programs, we can instruct computers to perform a wide range of activities, from simple calculations to complex tasks like managing databases and designing video games.

A. How Programming Works:

Programming involves several key steps:

• Problem definition: Clearly define the problem you want to solve and what you want the program to achieve.
• Algorithm design: Develop a step-by-step procedure for solving the problem.
• Coding: Translate the algorithm into a programming language using a text editor or integrated development environment (IDE).
• Testing and debugging: Run the program and identify and fix any errors.
• Deployment: Share the program with others or use it for your own purposes.

B. Benefits of Learning to Code:

Learning to code offers numerous benefits, both personal and professional:

• Develop critical thinking and problem-solving skills: Programming encourages logical thinking, problem decomposition, and finding creative solutions.
• Boost your creativity and innovation: Coding empowers you to build your own tools and applications, turning ideas into reality.
• Increase your employability: The demand for skilled programmers is high and growing across various industries.
• Improve your communication and collaboration skills: Working with code often requires collaboration and clear communication.
• Gain a deeper understanding of technology: Learning to code gives you a better understanding of how computers work and how they are used in the world around you.
• Build self-confidence and motivation: Successfully completing programming projects can boost your confidence and motivate you to learn new things.

Whether you’re interested in pursuing a career in technology or simply want to expand your knowledge and skills, learning to code is a valuable investment in your future.

2. Getting Started with Programming Tutorial

A. choosing your first language.

Assess Resource Availability:

• Free Online Resources: Platforms like Geeksforgeeks, Coursera, edX, and Udemy offer structured learning paths for various languages.
• Paid Online Courses: Platforms like Geeksforgeeks, Coursera, edX, and Udemy offer structured learning paths for various languages.
• Books and eBooks: Numerous beginner-friendly books and ebooks are available for most popular languages.
• Community Support: Look for active online forums, communities, and Stack Overflow for troubleshooting and questions.

B. Which Programming Language should you choose as your First Language?

Here’s a breakdown of popular beginner-friendly languages with their Strengths and Weaknesses:

C. Setting Up Your Development Environment

Choose a Text Editor or IDE :

• Text Editors: Sublime Text, Atom, Notepad++ (lightweight, good for beginners)
• Offline IDEs: Visual Studio Code, PyCharm, IntelliJ IDEA (feature-rich, recommended for larger projects)
• Online IDEs: GeeksforGeeks IDE

Install a Compiler or Interpreter:

• Compilers: Convert code to machine language (C++, Java)
• I nterpreters: Execute code line by line (Python, JavaScript)

Download Additional Software (if needed):

• Web browsers (Chromium, Firefox) for web development
• Android Studio or Xcode for mobile app development
• Game engines (Unity, Unreal Engine) for game development

Test Your Environment:

• Write a simple program (e.g., print “Hello, world!”)
• Run the program and verify the output
• Ensure everything is set up correctly
• Start with a simple editor like Sublime Text for code basics.
• Use an IDE like Visual Studio Code for larger projects with advanced features.
• Join online communities or forums for help with setup issues.

3. Common Programming Mistakes and How to Avoid Them

• Syntax errors: Typographical errors or incorrect grammar in your code.
• Use syntax highlighting in your editor or IDE.
• Logical errors: Errors in the logic of your program, causing it to produce the wrong results.
• Carefully review your code and logic.
• Test your program thoroughly with different inputs.
• Use debugging tools to identify and fix issues.
• Runtime errors: Errors that occur during program execution due to unforeseen circumstances.
• Seek help from online communities or forums for specific errors.
• Start with simple programs and gradually increase complexity.
• Write clean and well-formatted code for better readability.
• Use comments to explain your code and logic.
• Practice regularly and don’t be afraid to experiment.
• Seek help from online communities or mentors when stuck.

4. Basic Programming Essentials – A Beginner’s Guide to Programming Fundamentals:

This section delves deeper into fundamental programming concepts that form the building blocks of any program.

A. Variables and Data Types:

Understanding Variable Declaration and Usage:

• Variables are containers that hold data and can be assigned different values during program execution.
• To declare a variable, you specify its name and data type, followed by an optional assignment statement.
• Example: age = 25 (declares a variable named age of type integer and assigns it the value 25).
• Variables can be reassigned new values throughout the program.

Exploring Different Data Types:

• Integers: Whole numbers without decimal points (e.g., 1, 2, -3).
• Floats: Decimal numbers with a fractional part (e.g., 3.14, 10.5).
• Booleans: True or False values used for conditions.
• Characters: Single letters or symbols (‘a’, ‘$’, ‘#’).
• Strings: Sequences of characters (“Hello, world!”).
• Other data types: Arrays, lists, dictionaries, etc. (depending on the language).

Operations with Different Data Types:

Each data type has supported operations.

• Arithmetic operators (+, -, *, /) work with integers and floats.
• Comparison operators (==, !=, >, <, >=, <=) compare values.
• Logical operators (&&, ||, !) combine conditions.
• Concatenation (+) joins strings.
• Operations with incompatible data types may lead to errors.

B. Operators and Expressions:

Arithmetic Operators:

• Perform basic mathematical calculations (+, -, *, /, %, **, //).
• % (modulo) returns the remainder after division.
• ** (power) raises a number to a certain power.
• // (floor division) discards the fractional part of the result.

Comparison Operators:

• Evaluate conditions and return True or False.
• == (equal), != (not equal), > (greater than), < (less than), >= (greater than or equal), <= (less than or equal).

Logical Operators: Combine conditions and produce True or False.

• && (and): both conditions must be True.
• || (or): at least one condition must be True.
• ! (not): reverses the truth value of a condition.

Building Expressions:

• Combine variables, operators, and constants to form expressions.
• Expressions evaluate to a single value. Example: result = age + 10 * 2 (calculates the sum of age and 20).

C. Control Flow Statements:

Conditional Statements: Control the flow of execution based on conditions.

• if-else: Executes one block of code if the condition is True and another if it’s False.
• switch-case: Executes different code blocks depending on the value of a variable.

Looping Statements: Repeat a block of code multiple times.

• for: Executes a block a specific number of times.
• while: Executes a block while a condition is True.
• do-while: Executes a block at least once and then repeats while a condition is True.

Nested Loops and Conditional Statements:

• Can be combined to create complex control flow structures.
• Inner loops run inside outer loops, allowing for nested logic.

D. Functions:

Defining and Calling Functions:

• Blocks of code that perform a specific task.
• Defined with a function name, parameters (optional), and a code block.
• Called throughout the program to execute the defined functionality.

Passing Arguments to Functions:

• Values passed to functions for processing.

Returning Values from Functions:

• Functions can return a value after execution.
• Useful for collecting results.
• A function calling itself with a modified input.
• Useful for solving problems that involve repetitive tasks with smaller inputs.

These topics provide a solid foundation for understanding programming fundamentals. Remember to practice writing code and experiment with different concepts to solidify your learning.

5. Advanced Programming Concepts

This section explores more advanced programming concepts that build upon the foundational knowledge covered earlier.

A. Object-Oriented Programming (OOP)

OOP is a programming paradigm that emphasizes the use of objects to represent real-world entities and their relationships.

1. Classes and Objects:

• Classes: Define the blueprint for objects, specifying their properties (attributes) and behaviors (methods).
• Objects: Instances of a class, with their own set of properties and methods.

2. Inheritance and Polymorphism:

• Inheritance: Allows creating new classes that inherit properties and methods from existing classes (superclasses).
• Polymorphism: Enables objects to respond differently to the same message depending on their type.

3. Encapsulation and Abstraction:

• Encapsulation: Encloses an object’s internal state and methods, hiding implementation details and exposing only a public interface.
• Abstraction: Focuses on the essential features and functionalities of an object, ignoring unnecessary details.

B. Concurrency and Parallelism

Concurrency and parallelism are crucial for improving program efficiency and responsiveness.

1. Multithreading and Multiprocessing:

• Multithreading: Allows multiple threads of execution within a single process, enabling concurrent tasks.
• Multiprocessing: Utilizes multiple processors to run different processes simultaneously, achieving true parallelism.

2. Synchronization and Concurrency Control:

Mechanisms to ensure data consistency and prevent conflicts when multiple threads or processes access shared resources.

6. Writing Your First Code

Here is your first code in different languages. These programs all achieve the same goal: printing “ Hello, world! ” to the console. However, they use different syntax and conventions specific to each language.

Printing “Hello world” in C++:

Explanation of above C++ code:

• #include: This keyword includes the <iostream> library, which provides functions for input and output.
• int main(): This defines the main function, which is the entry point of the program.
• std::cout <<: This keyword prints the following expression to the console.
• “Hello, world!” This is the string that is printed to the console.
• std::endl: This keyword inserts a newline character after the printed string.
• return 0; This statement exits the program and returns a success code (0).

Printing “Hello world” in Java:

Explanation of above Java code:

• public class HelloWorld: This keyword defines a public class named HelloWorld .
• public static void main(String[] args): This declares the main function, which is the entry point of the program.
• System.out.println(“Hello, world!”); This statement prints the string “ Hello, world! ” to the console.

Printing “Hello world” in Python:

Explanation of above Python code:

• print: This keyword prints the following argument to the console.

Printing “Hello world” in Javascript:

Explanation of above Javascript code:

• console.log: This object’s method prints the following argument to the console.

Printing “Hello world” in PHP:

Explanation of above PHP code:

• <?php: This tag initiates a PHP code block.
• echo: This keyword prints the following expression to the console.
• ?>: This tag ends the PHP code block.

7. Top 20 Programs to get started with Coding/Programming Tutorial:

Here are the list of some basic problem, these problems cover various fundamental programming concepts. Solving them will help you improve your coding skills and understanding of programming fundamentals.

8. Next Steps after learning basic Coding/Programming Tutorial:

Congratulations on taking the first step into the exciting world of programming! You’ve learned the foundational concepts and are ready to explore more. Here’s a comprehensive guide to help you navigate your next steps:

A. Deepen your understanding of Basic Programming Concepts:

• Practice regularly: Implement what you learn through practice problems and coding exercises.
• Solve code challenges: Platforms like GeeksforGeeks, HackerRank, LeetCode, and Codewars offer challenges to improve your problem-solving skills and coding speed.

B. Learn advanced concepts:

• Data structures: Learn about arrays, linked lists, stacks, queues, trees, and graphs for efficient data organization.
• Algorithms: Explore algorithms for searching, sorting, dynamic programming, and graph traversal.
• Databases: Learn SQL and NoSQL databases for data storage and retrieval.
• Version control: Use Git and GitHub for code versioning and collaboration.

C. Choose a focus area:

• Web development: Learn HTML, CSS, and JavaScript to build interactive web pages and applications.
• Mobile app development: Choose frameworks like Flutter (Dart) or React Native (JavaScript) to build cross-platform apps.
• Data science and machine learning: Explore Python libraries like NumPy, pandas, and scikit-learn to analyze data and build machine learning models.
• Game development: Learn game engines like Unity (C#) or Unreal Engine (C++) to create engaging games.
• Desktop app development: Explore frameworks like PyQt (Python) or C# to build desktop applications.
• Other areas: Explore other areas like robotics, embedded systems, cybersecurity, or blockchain development based on your interests.

D. Build projects:

• Start with small projects: Begin with simple projects to apply your knowledge and gain confidence.
• Gradually increase complexity: As you progress, tackle more challenging projects that push your boundaries.
• Contribute to open-source projects: Contributing to open-source projects is a great way to learn from experienced developers and gain valuable experience.
• Showcase your work: Create a portfolio website or blog to showcase your skills and projects to potential employers or clients.

9. Resources and Further Learning

A. Online Courses and Tutorials:

• Interactive platforms: GeeksforGeeks, Codecademy, Coursera, edX, Khan Academy
• Video tutorials: GeeksforGeeks, YouTube channels like FreeCodeCamp, The Coding Train, CS50’s Introduction to Computer Science
• Language-specific tutorials: GeeksforGeeks, Official documentation websites, blogs, and community-driven resources

B. Books and eBooks:

• Beginner-friendly books: “Python Crash Course” by Eric Matthes, “Head First Programming” by David Griffiths
• A dvanced topics: “Clean Code” by Robert C. Martin, “The Pragmatic Programmer” by Andrew Hunt and David Thomas
• Free ebooks: Many free programming ebooks are available online, such as those on Project Gutenberg

C. Programming Communities and Forums:

• Stack Overflow: Q&A forum for programming questions
• GitHub: Open-source platform for hosting and collaborating on code projects
• Reddit communities: r/learnprogramming, r/python, r/webdev
• Discord servers: Many languages have dedicated Discord servers for discussions and support

D. Tips for Staying Motivated and Learning Effectively:

• Set realistic goals and deadlines.
• Start small and gradually increase complexity.
• Practice regularly and code consistently.
• Find a learning buddy or group for accountability.
• Participate in online communities and forums.
• Take breaks and avoid burnout.
• Most importantly, have fun and enjoy the process

10. Frequently Asked Questions (FAQs) on Programming Tutorial:

Question 1: how to learn programming without tutorial.

Answer: Learning programming without tutorials involves a self-directed approach. Start by understanding fundamental concepts, practicing regularly, and working on small projects. Utilize books, documentation, and online resources for reference.

Question 2: How to learn coding tutorial?

Answer: Learning coding through tutorials involves choosing a programming language, finding online tutorials or courses, and following them step by step. Practice coding alongside the tutorial examples and apply the concepts to real-world projects for a hands-on learning experience.

Question 3: What are 3 important things to know about programming?

Answer: Problem Solving: Programming is fundamentally about solving problems. Logic and Algorithms: Understanding logical thinking and creating efficient algorithms is crucial. Practice: Regular practice and hands-on coding improve skills and understanding.

Question 4: How many days do I need to learn programming?

Answer: The time to learn programming varies based on factors like prior experience, the complexity of the language, and the depth of knowledge desired. Learning the basics can take weeks, but mastery requires continuous practice over months.

Question 5: Can tutorials help coding?

Answer: Yes, tutorials are valuable resources for learning coding. They provide structured guidance, examples, and explanations, making it easier to understand and apply Programming Tutorial concepts.

Question 6: How do you use tutorials effectively?

Answer: Use tutorials effectively by following these steps: Set clear learning goals. Work on hands-on exercises and projects. Seek additional resources for deeper understanding. Regularly review and practice concepts learned.

Question 7: Can coding be done on a phone?

Answer: Yes, coding can be done on a phone using coding apps or online platforms that provide mobile-friendly coding environments. However, a computer is generally more practical for extensive coding tasks.

Question 8: Can I learn coding on GeeksforGeeks?

Answer: Yes, GeeksforGeeks is a popular platform for learning coding. Many Tutorials, Courses are provided you to learn various programming languages and concepts.

Question 9: Can we do coding on a laptop?

Answer: Yes, coding can be done on a laptop. Laptops are common tools for coding as they provide a portable and versatile environment for writing, testing, and running code.

Question 10: What is the difference between coding and programming?

Answer: The terms are often used interchangeably, but coding is typically seen as the act of writing code, while programming involves a broader process that includes problem-solving, designing algorithms, and implementing solutions. Programming encompasses coding as one of its stages.

This comprehensive programming tutorial has covered the fundamentals you need to start coding. Stay updated with emerging technologies and keep practicing to achieve your goals. Remember, everyone starts as a beginner. With dedication, you can unlock the world of programming!

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Improve your Coding Skills with Practice

What kind of Experience do you want to share?

How to think like a programmer — lessons in problem solving

By Richard Reis

If you’re interested in programming, you may well have seen this quote before:

“Everyone in this country should learn to program a computer, because it teaches you to think.” — Steve Jobs

You probably also wondered what does it mean, exactly, to think like a programmer? And how do you do it??

Essentially, it’s all about a more effective way for problem solving .

In this post, my goal is to teach you that way.

By the end of it, you’ll know exactly what steps to take to be a better problem-solver.

Why is this important?

Problem solving is the meta-skill.

We all have problems. Big and small. How we deal with them is sometimes, well…pretty random.

Unless you have a system, this is probably how you “solve” problems (which is what I did when I started coding):

• Try a solution.
• If that doesn’t work, try another one.
• If that doesn’t work, repeat step 2 until you luck out.

Look, sometimes you luck out. But that is the worst way to solve problems! And it’s a huge, huge waste of time.

The best way involves a) having a framework and b) practicing it.

“Almost all employers prioritize problem-solving skills first. Problem-solving skills are almost unanimously the most important qualification that employers look for….more than programming languages proficiency, debugging, and system design. Demonstrating computational thinking or the ability to break down large, complex problems is just as valuable (if not more so) than the baseline technical skills required for a job.” — Hacker Rank ( 2018 Developer Skills Report )

Have a framework

To find the right framework, I followed the advice in Tim Ferriss’ book on learning, “ The 4-Hour Chef ”.

It led me to interview two really impressive people: C. Jordan Ball (ranked 1st or 2nd out of 65,000+ users on Coderbyte ), and V. Anton Spraul (author of the book “ Think Like a Programmer: An Introduction to Creative Problem Solving ”).

I asked them the same questions, and guess what? Their answers were pretty similar!

Soon, you too will know them.

Sidenote: this doesn’t mean they did everything the same way. Everyone is different. You’ll be different. But if you start with principles we all agree are good, you’ll get a lot further a lot quicker.

“The biggest mistake I see new programmers make is focusing on learning syntax instead of learning how to solve problems.” — V. Anton Spraul

So, what should you do when you encounter a new problem?

Here are the steps:

1. Understand

Know exactly what is being asked. Most hard problems are hard because you don’t understand them (hence why this is the first step).

How to know when you understand a problem? When you can explain it in plain English.

Do you remember being stuck on a problem, you start explaining it, and you instantly see holes in the logic you didn’t see before?

Most programmers know this feeling.

This is why you should write down your problem, doodle a diagram, or tell someone else about it (or thing… some people use a rubber duck ).

“If you can’t explain something in simple terms, you don’t understand it.” — Richard Feynman

Don’t dive right into solving without a plan (and somehow hope you can muddle your way through). Plan your solution!

Nothing can help you if you can’t write down the exact steps.

In programming, this means don’t start hacking straight away. Give your brain time to analyze the problem and process the information.

To get a good plan, answer this question:

“Given input X, what are the steps necessary to return output Y?”

Sidenote: Programmers have a great tool to help them with this… Comments!

Pay attention. This is the most important step of all.

Do not try to solve one big problem. You will cry.

Instead, break it into sub-problems. These sub-problems are much easier to solve.

Then, solve each sub-problem one by one. Begin with the simplest. Simplest means you know the answer (or are closer to that answer).

After that, simplest means this sub-problem being solved doesn’t depend on others being solved.

Once you solved every sub-problem, connect the dots.

Connecting all your “sub-solutions” will give you the solution to the original problem. Congratulations!

This technique is a cornerstone of problem-solving. Remember it (read this step again, if you must).

“If I could teach every beginning programmer one problem-solving skill, it would be the ‘reduce the problem technique.’ For example, suppose you’re a new programmer and you’re asked to write a program that reads ten numbers and figures out which number is the third highest. For a brand-new programmer, that can be a tough assignment, even though it only requires basic programming syntax. If you’re stuck, you should reduce the problem to something simpler. Instead of the third-highest number, what about finding the highest overall? Still too tough? What about finding the largest of just three numbers? Or the larger of two? Reduce the problem to the point where you know how to solve it and write the solution. Then expand the problem slightly and rewrite the solution to match, and keep going until you are back where you started.” — V. Anton Spraul

By now, you’re probably sitting there thinking “Hey Richard... That’s cool and all, but what if I’m stuck and can’t even solve a sub-problem??”

First off, take a deep breath. Second, that’s fair.

Don’t worry though, friend. This happens to everyone!

The difference is the best programmers/problem-solvers are more curious about bugs/errors than irritated.

In fact, here are three things to try when facing a whammy:

• Debug: Go step by step through your solution trying to find where you went wrong. Programmers call this debugging (in fact, this is all a debugger does).

“The art of debugging is figuring out what you really told your program to do rather than what you thought you told it to do.”” — Andrew Singer

• Reassess: Take a step back. Look at the problem from another perspective. Is there anything that can be abstracted to a more general approach?

“Sometimes we get so lost in the details of a problem that we overlook general principles that would solve the problem at a more general level. […] The classic example of this, of course, is the summation of a long list of consecutive integers, 1 + 2 + 3 + … + n, which a very young Gauss quickly recognized was simply n(n+1)/2, thus avoiding the effort of having to do the addition.” — C. Jordan Ball

Sidenote: Another way of reassessing is starting anew. Delete everything and begin again with fresh eyes. I’m serious. You’ll be dumbfounded at how effective this is.

• Research: Ahh, good ol’ Google. You read that right. No matter what problem you have, someone has probably solved it. Find that person/ solution. In fact, do this even if you solved the problem! (You can learn a lot from other people’s solutions).

Caveat: Don’t look for a solution to the big problem. Only look for solutions to sub-problems. Why? Because unless you struggle (even a little bit), you won’t learn anything. If you don’t learn anything, you wasted your time.

Don’t expect to be great after just one week. If you want to be a good problem-solver, solve a lot of problems!

Practice. Practice. Practice. It’ll only be a matter of time before you recognize that “this problem could easily be solved with .”

How to practice? There are options out the wazoo!

Chess puzzles, math problems, Sudoku, Go, Monopoly, video-games, cryptokitties, bla… bla… bla….

In fact, a common pattern amongst successful people is their habit of practicing “micro problem-solving.” For example, Peter Thiel plays chess, and Elon Musk plays video-games.

“Byron Reeves said ‘If you want to see what business leadership may look like in three to five years, look at what’s happening in online games.’ Fast-forward to today. Elon [Musk], Reid [Hoffman], Mark Zuckerberg and many others say that games have been foundational to their success in building their companies.” — Mary Meeker ( 2017 internet trends report )

Does this mean you should just play video-games? Not at all.

But what are video-games all about? That’s right, problem-solving!

So, what you should do is find an outlet to practice. Something that allows you to solve many micro-problems (ideally, something you enjoy).

For example, I enjoy coding challenges. Every day, I try to solve at least one challenge (usually on Coderbyte ).

Like I said, all problems share similar patterns.

That’s all folks!

Now, you know better what it means to “think like a programmer.”

You also know that problem-solving is an incredible skill to cultivate (the meta-skill).

As if that wasn’t enough, notice how you also know what to do to practice your problem-solving skills!

Phew… Pretty cool right?

Finally, I wish you encounter many problems.

You read that right. At least now you know how to solve them! (also, you’ll learn that with every solution, you improve).

“Just when you think you’ve successfully navigated one obstacle, another emerges. But that’s what keeps life interesting.[…] Life is a process of breaking through these impediments — a series of fortified lines that we must break through. Each time, you’ll learn something. Each time, you’ll develop strength, wisdom, and perspective. Each time, a little more of the competition falls away. Until all that is left is you: the best version of you.” — Ryan Holiday ( The Obstacle is the Way )

Now, go solve some problems!

And best of luck ?

Special thanks to C. Jordan Ball and V. Anton Spraul . All the good advice here came from them.

Thanks for reading! If you enjoyed it, test how many times can you hit in 5 seconds. It’s great cardio for your fingers AND will help other people see the story.

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Course info.

• Prof. John Guttag

Departments

• Electrical Engineering and Computer Science

As Taught In

• Computer Science

Introduction to Computer Science and Programming

Lecture 3: problem solving.

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You are leaving MIT OpenCourseWare

Problem Solving and Programming | Unit 1 – 6 Notes

Course objectives:.

Prime objective is to give students a basic introduction to programming and problem solving with computer language Python. And to introduce students not merely to the coding of computer programs, but to computational thinking, the methodology of computer programming, and the principles of good program design including modularity and encapsulation.

• To understand problem solving, problem solving aspects, programming and to know about various program design tools.
• To learn problem solving with computers
• To learn basics, features and future of Python programming.
• To acquaint with data types, input output statements, decision making, looping and functions in Python
• To learn features of Object Oriented Programming using Python
• To acquaint with the use and benefits of files handling in Python

Examination Scheme:

In Semester : 30 Marks End Semester: 70 Marks PR: 25 Marks

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Unit I: Problem Solving, Programming and Python Programming

General Problem Solving Concepts- Problem solving in everyday life, types of problems, problem solving with computers, difficulties with problem solving, problem solving aspects, top down design. Problem Solving Strategies, Program Design Tools: Algorithms, Flowcharts and Pseudo-codes, implementation of algorithms. Basics of Python Programming: Features of Python, History and Future of Python, Writing and executing Python program, Literal constants, variables and identifiers, Data Types, Input operation, Comments, Reserved words, Indentation, Operators and expressions, Expressions in Python.

Unit 2: Decision Control Statements

Decision Control Statements: Decision control statements, Selection/conditional branching Statements: if, if-else, nested if, if-elif-else statements. Basic loop Structures/Iterative statements: while loop, for loop, selecting appropriate loop. Nested loops, The break, continue, pass, else statement used with loops. Other data types- Tuples, Lists and Dictionary.

Unit 3: Functions and Modules

Need for functions, Function: definition, call, variable scope and lifetime, the return statement. Defining functions, Lambda or anonymous function, documentation string, good programming practices. Introduction to modules, Introduction to packages in Python, Introduction to standard library modules.

Unit 4: Strings

Strings and Operations- concatenation, appending, multiplication and slicing. Strings are immutable, strings formatting operator, built in string methods and functions. Slice operation, ord() and chr() functions, in and not in operators, comparing strings, Iterating strings, the string module.

Unit 5: Object Oriented Programming

Programming Paradigms-monolithic, procedural, structured and object oriented, Features of Object oriented programming-classes, objects, methods and message passing, inheritance, polymorphism, containership, reusability, delegation, data abstraction and encapsulation. Classes and Objects: classes and objects, class method and self object, class variables and object variables, public and private members, class methods.

Unit 6: File Handling and Dictionaries

Files: Introduction, File path, Types of files, Opening and Closing files, Reading and Writing files. Dictionary method. Dictionaries- creating, assessing, adding and updating values. Case Study: Study design, features, and use of any recent, popular and efficient system developed using Python. (This topic is to be excluded for theory examination).

• Computer Science and Engineering
• NOC:Problem Solving through Programming in C (Video) 
• Co-ordinated by : IIT Kharagpur
• Available from : 2017-12-21
• Intro Video
• Lecture 1 : Introduction
• Lecture 2 : Idea of Algorithms
• Lecture 3 : Flow Chart and Pseudocode
• Lecture 4 : Introduction to Programming Language Concepts
• Lecture 5 : Variables and Memory
• Lecture 6 : Types of Software and Compilers
• Lecture 7 : Introduction to C Programming Language
• Lecture 8 : Variables and Variable Types in C
• Lecture 9 : Introducing Functions
• Lecture 10 : Address and Content of Variables and Types
• Lecture 11 : Assignment Statement and Operators in C
• Lecture 12 : Arithmetic Expressions and Relational Expressions
• Lecture 13 : Logical Operators and Change in Control Flow
• Lecture 14 : Use of Logical Operaotrs in Branching
• Lecture 15 : Branching : IF - ELSE Statement
• Lecture 16 : IF-ELSE Statement (Contd.)
• Lecture 17 : Switch statement
• Lecture 18 : Switch Statement (Contd.) and Introduction to Loops
• Lecture 19 : Implementing Repetitions (Loops)
• Lecture 20 : Implementation of Loops with for Statement (Contd.)
• Lecture 21 : For Statement (Contd.)
• Lecture 22 : Example of If-Else
• Lecture 23 : Example of Loops
• Lecture 24 : Example of Loops (Contd.)
• Lecture 25: Example of Loops (Contd.), Use of FOR Loops
• Lecture 26 : Introduction to Arrays
• Lecture 27 : Arrays (Contd.)
• Lecture 28 : Arrays (Contd.)
• Lecture 29 : Program using Arrays
• Lecture 30 : Array Problem
• Lecture 31 : Linear Search
• Lecture 32 : Character Array and Strings
• Lecture 33 : String Operations
• Lecture 34 : 2-D Array Operation
• Lecture 35 : Introducing Functions
• Lecture 36 : More on Functions
• Lecture 37 : Function (Contd.)
• Lecture 38 : Scanf and Printf Functions; Function Prototype
• Lecture 39 : Parameter Passing in Function Revision
• Lecture 40 : Parameter Passing in Function Revision (Contd.)
• Lecture 41: Substitution of # include and Macro
• Lecture 42: "search" as a function
• Lecture 43: Binary Search
• Lecture 44: Binary Search (Contd.)
• Lecture 45: Sorting Methods
• Lecture 46 : Bubble Sort (Contd.)
• Lecture 47 : Use of Pointer in Function : Context Bubble Sort
• Lecture 48 : Arrays at Strings
• Lecture 49 : Data Representation
• Lecture 50 : Bisection Method
• Lecture 51 : Interpolation
• Lecture 52 : Trapezoidal Rule and Runge-Kutta Method
• Lecture 53 : Recursion
• Lecture 54 : Recursion(Contd.)
• Lecture 55 : Structure
• Lecture 56 : Structure (Contd.)
• Lecture 57 : Structure with typedef
• Lecture 58 : Pointer
• Lecture 59 : Pointer (Contd.)
• Lecture 60 : Pointer in Structures
• Lecture 61 : Dynamic Allocation and File
• Week 2 - PMRF Live Session
• Week 3 - PMRF Live Session
• Watch on YouTube
• Assignments
• Download Videos
• Transcripts
• Handouts (3)

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[PDF] GE3151 Problem Solving and Python Programming (PSPP) Books, Lecture Notes, 2 marks with answers, Important Part B 16 Marks Questions, Question Bank & Syllabus

Download GE3151 Problem Solving and Python Programming (PSPP) Books Lecture Notes Syllabus Part-A 2 marks with answers GE3151 Problem Solving and Python Programming Important Part-B 16 marks Questions , PDF Books, Question Bank with answers Key, GE3151 Problem Solving and Python Programming Syllabus & Anna University GE3151 Problem Solving and Python Programming Question Papers Collection.

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Download link is provided for Students to download the Anna University GE3151 Problem Solving and Python Programming Syllabus Question Bank Lecture Notes Part A 2 marks with answers & Part B 16 marks Question Bank with answer , Anna University Question Paper Collection, All the materials are listed below for the students to make use of it and get good (maximum) marks with our study materials.

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GE3151 PROBLEM SOLVING AND PYTHON PROGRAMMING

UNIT I COMPUTATIONAL THINKING AND PROBLEM SOLVING

Fundamentals of Computing – Identification of Computational Problems -Algorithms, building blocks of algorithms (statements, state, control flow, functions), notation (pseudo code, flow chart, programming language), algorithmic problem solving, simple strategies for developing algorithms (iteration, recursion). Illustrative problems: find minimum in a list, insert a card in a list of sorted cards, guess an integer number in a range, Towers of Hanoi.

UNIT II DATA TYPES, EXPRESSIONS, STATEMENTS

Python interpreter and interactive mode, debugging; values and types: int, float, boolean, string, and list; variables, expressions, statements, tuple assignment, precedence of operators, comments; Illustrative programs: exchange the values of two variables, circulate the values of n variables, distance between two points.

UNIT III CONTROL FLOW, FUNCTIONS, STRINGS

Conditionals: Boolean values and operators, conditional (if), alternative (if-else), chained conditional (if-elif-else); Iteration: state, while, for, break, continue, pass; Fruitful functions: return values, parameters, local and global scope, function composition, recursion; Strings: string slices, immutability, string functions and methods, string module; Lists as arrays. Illustrative programs: square root, gcd, exponentiation, sum an array of numbers, linear search, binary search.

UNIT IV LISTS, TUPLES, DICTIONARIES

Lists: list operations, list slices, list methods, list loop, mutability, aliasing, cloning lists, list parameters; Tuples: tuple assignment, tuple as return value; Dictionaries: operations and methods; advanced list processing – list comprehension; Illustrative programs: simple sorting, histogram, Students marks statement, Retail bill preparation.

UNIT V FILES, MODULES, PACKAGES

Files and exception: text files, reading and writing files, format operator; command line arguments, errors and exceptions, handling exceptions, modules, packages; Illustrative programs: word count, copy file, Voter’s age validation, Marks range validation (0-100).

  TEXT BOOKS:

• Allen B. Downey, “Think Python : How to Think like a Computer Scientist”, 2nd Edition, O’Reilly Publishers, 2016.
• Karl Beecher, “Computational Thinking: A Beginner&#39;s Guide to Problem Solving and programming”, 1st Edition, BCS Learning &amp; Development Limited, 2017.

REFERENCES:

• Paul Deitel and Harvey Deitel, “Python for Programmers”, Pearson Education, 1st Edition,
• G Venkatesh and Madhavan Mukund, “Computational Thinking: A Primer for Programmers and Data Scientists”, 1st Edition, Notion Press, 2021.
• John V Guttag, &quot;Introduction to Computation and Programming Using Python: With Applications to Computational Modeling and Understanding Data‘‘, Third Edition, MIT Press 2021
• Eric Matthes, “Python Crash Course, A Hands – on Project Based Introduction to Programming”, 2nd Edition, No Starch Press, 2019.
• https://www.python.org/
• 6. Martin C. Brown, “Python: The Complete Reference”, 4th Edition, Mc-Graw Hill,2018.

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Anna University GE3151 Problem Solving and Python Programming Books Question Banks Lecture Notes Syllabus GE3151 Problem Solving and Python Programming Part A 2 Marks with Answers Part – B 16 Marks Questions with Answers & Anna University GE3151 Problem Solving and Python Programming Question Paper Collection and Local Author Books.

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