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Principles of Algorithmic Problem Solving (PDF)

Principles of Algorithmic Problem Solving by Johan Sannemo is an illuminating guide that unveils the intricate world of solving problems through algorithms. This comprehensive book delves deep into the fundamental principles that underlie the art of algorithmic problem solving, providing readers with invaluable insights and techniques to tackle complex computational challenges.

Sannemo’s expertise shines through as he expertly navigates readers through the multifaceted landscape of problem-solving methodologies. With clarity and precision, he elucidates the core principles that govern the development of efficient algorithms, enabling readers to cultivate a deep understanding of the problem-solving process. Whether you are a seasoned programmer or a novice exploring the realm of algorithms, this book serves as an indispensable resource.

One of the book’s key strengths lies in its practical approach. Sannemo artfully combines theoretical explanations with real-world examples, equipping readers with the necessary tools to translate concepts into actionable solutions. Through thought-provoking exercises and illustrative code snippets, he encourages readers to actively engage in the learning process, honing their problem-solving skills and algorithmic thinking.

The author emphasizes the importance of algorithm design and analysis, shedding light on different problem-solving strategies such as divide and conquer, dynamic programming, and greedy algorithms. By elucidating the underlying principles of these strategies, Sannemo empowers readers to discern which approach is best suited for specific problem domains.

Moreover, the book explores various data structures and their impact on algorithm efficiency. Sannemo guides readers through the intricate world of arrays, linked lists, stacks, queues, trees, and graphs, unveiling their strengths, weaknesses, and optimal usage scenarios. Armed with this knowledge, readers can make informed decisions when selecting data structures to maximize their algorithmic prowess.

As readers progress through the book, they will encounter a rich tapestry of problem-solving techniques, ranging from fundamental concepts to advanced algorithms. Sannemo’s lucid explanations and captivating writing style ensure that readers remain engrossed, making the journey through this book both enlightening and enjoyable.

Principles of Algorithmic Problem Solving is an invaluable resource for computer science students, software engineers, and anyone seeking to enhance their problem-solving abilities. With its clear explanations, practical examples, and insightful exercises, this book empowers readers to tackle algorithmic challenges with confidence and creativity. Whether you aspire to excel in programming competitions or develop efficient software solutions, Sannemo’s comprehensive guide is a must-read that will equip you with the essential principles and strategies of algorithmic problem solving.

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Java, Java, Java: Object-Oriented Problem Solving

(4 reviews)

Ralph Morelli, Trinity College

Ralph Walde, Trinity College

Copyright Year: 2016

Publisher: Ralph Morelli, Ralph Walde

Language: English

Formats Available

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Learn more about reviews.

Reviewed by Onyeka Emebo, Assistant Professor, Virginia Tech on 12/28/21

The text adequately addresses areas under Object Oriented Programming using Java as a Programming Language for Introduction to Computer Science courses. It gently introduces basic concepts in computer, objects and java using problem solving... read more

Comprehensiveness rating: 5 see less

The text adequately addresses areas under Object Oriented Programming using Java as a Programming Language for Introduction to Computer Science courses. It gently introduces basic concepts in computer, objects and java using problem solving approaches and gradually builds up to more advanced Java technologies in such a simplified manner that can be easily understood. The text also provides a table of content at the beginning and a summary of points for each chapter with exercises.

Content Accuracy rating: 4

The text content is accurate, without errors and unbiased. There is however some links that needs to be updated.

Relevance/Longevity rating: 4

While the field of computer science with particular emphasis to programming as it relates to this text is constantly evolving, the approach taken by this text to teach the essentials is likely to persist. The code, tested in Java 8, should continue to work with new Java releases. Updates to the text can be done easily by the way it has been written.

Clarity rating: 5

The text is written in a clear and easy to understand manner. The objectives, explanations, examples and exercises are clear and easy to follow. The codes are well commented to aid readability.

Consistency rating: 4

The text is highly consistent in both structure and terminology. It starts each chapter with objectives and outline and concludes with summary, exercises and solutions. However, some codes within the chapters are put in figures while others are not, this could be confusing.

Modularity rating: 5

The text is divided in 17 chapters (0 - 16) and 8 appendices (A – H). Each chapter is further divided into sections and subsections. This breakdown makes it easier for instructors to apportion sections to students at different times within the course.

Organization/Structure/Flow rating: 5

The text is organized in a manner that is logical and it flows well from section to section. The structure makes navigation from chapter to chapter easier.

Interface rating: 3

I reviewed the PDF version and it looks good to a large extent. The links in the table of contents are working properly. There are clickable links within the text to different figures, sections, such as appendices, and external websites. However, there are some issues with some figure titles, e.g., figure 12, 1.10, 2.7, 2.10, 2.14, etc. are cut off. Some hyperlinks for some figures missing e.g., figure 2.8 and some figures don’t have titles.

Grammatical Errors rating: 5

The text contains no grammatical errors.

Cultural Relevance rating: 5

The text is culturally neutral. The examples are unbiased in the way it has been presented.

Reviewed by Ghaith Husari, Assistant Professor, East Tennessee State University on 4/17/20

This book covers Object-Oriented Programming under JAVA. It introduces the concepts of object-oriented programming and they are used for problem-solving. This book covers all the relevant areas of Object-Oriented Programming under Java. Also, it... read more

This book covers Object-Oriented Programming under JAVA. It introduces the concepts of object-oriented programming and they are used for problem-solving. This book covers all the relevant areas of Object-Oriented Programming under Java. Also, it covers more advanced topics such as socket programming and algorithms.

Content Accuracy rating: 5

The Object-Oriented concepts and implementation example shown in code samples are accurate and easy to learn as the code samples are aligned with the concept being discussed. Some links and URLs are out-dated but they have little to no impact on student learning. However, I would add a note that says "some of the links and URLs might not up-to-date. However, they can be found using search engines if necessary"

Programming languages get updated regularly to include new and easier functions to use. While it is impossible for a textbook to include every function, this textbook provides a great learning opportunity that allows students to build the muscle to be able to learn more about Java online. When it comes to Object-Oriented concepts, the book is extremely relevant and up-to-date

The textbook is very easy to understand and the code sample is both clear (code readability) and relevant.

Consistency rating: 5

The text and the terms it contains are consistent. Also, the textbook follows a consistent theme.

The textbook chapters are divided into sections and subsections that are shown also in the table of contents which can be used to visit each section.

The textbook consists of seventeen chapters that are organized in a logical manner. The more general concepts such as problem-solving and programing are placed at the beginning, then the chapters introduce the discuss Object-Oriented Programming come after the general chapters. The more advanced topics such as socket programming and data structures and algorithms come towards the end. This made a lot of sense to me.

Interface rating: 5

The textbook is easily accessible online and it can be downloaded to open with Edge or Adobe Reader without any problems.

No grammar issues have been noticed.

This textbook is neutral and unbiased.

Reviewed by Guanyu Tian, Assistant Professor, Fontbonne University on 6/19/18

This textbook covers Object-Oriented Programming with Java programming language pretty well. It starts with the concept of Objects and problem solving skills and then dive into Java programming language syntax. Overall, it appropriately covers all... read more

Comprehensiveness rating: 4 see less

This textbook covers Object-Oriented Programming with Java programming language pretty well. It starts with the concept of Objects and problem solving skills and then dive into Java programming language syntax. Overall, it appropriately covers all areas of the subject including the main principles of Object-Oriented Programming and Java programming language. In the later chapters, this textbook also introduces advanced topics such as concurrent programming, network/socket programming and data structures. The textbook provides table of contents at the beginning and index of terms at the end. Each chapter also provides a list of key words and a list of important concepts and technique terms.

Content Accuracy rating: 3

The content of the textbook is mostly accurate. Many URLs linked to Java documentations and APIs are not up-to-date.

Many URLs to Java references are not up-to-date and many online samples are not accessible. Nonetheless, the concepts of Object-Oriented Programming and Java programming language syntax are mostly current. Any updates to the contents of the textbook can be implemented with minimal effort.

The text is easy to understand. However, some of the texts are not displayed on adobe reader.

Consistency rating: 3

The text is consistent in terms of framework. Each chapter starts with introduction to a problem, and then discussion and design of the solution with UML diagrams; then Java is used to implement the solution(s). However, there is some level of inconsistency in terms of Java code samples. For example, some Java code examples use appropriate indentations and new lines, but some examples do not. This may confuse students.

Each chapter is divided into different sections and subsections. A student can go to each section of a chapter by clicking it in the Table of Contents.

Organization/Structure/Flow rating: 3

The topics in this text book are organized in a reasonable order. It starts with general concepts of computer and program design, then Objects and Java Programming Language, and then advanced topics in computer programming. It would be better if the textbook starts with Java programming language and then principles of Object Oriented programming.

Some of the texts are not displayed in the reviewer's adobe reader. Many diagrams and figures are poorly drawn. Overall, the interface of the book is one area that needs improvement.

No major grammar issues has been noticed.

The text of this textbook is a neutral and unbiased.

Overall, this textbook covers materials of Object-Oriented Programming with Java taught in first or second-year computer science course. However, the contents of Java programming language has not been up-to-date and the interface of the book is very poor compare to similar books the reviewer has used for learning and teaching the same materials. Some sample codes are not well written or inconsistent in terms of the use of indentation and new lines. Many URLs are obsolete and the web pages are not accessible.

Reviewed by Homer Sharafi, Adjunct Faculty Member, Northern Virginia Community College on 6/20/17

The textbook includes the material that is typically covered in a college-level CS1 course. Using an “early objects” approach and Java as the programming language, the authors go over problem-solving techniques based on object-oriented... read more

The textbook includes the material that is typically covered in a college-level CS1 course. Using an “early objects” approach and Java as the programming language, the authors go over problem-solving techniques based on object-oriented programming principles. In addition to an Index of terms towards the end of the text, each chapter summary includes the technical terms used, along with a bulleted-list of important points discussed in that chapter.

The computer science concepts and the accompanying sample code are accurate and error-free; however, the only issue is the fact that the URLs that make references to various aspects of Java, such as API documentation, JDK, and the Java Language Specification, have not been updated to reflect the fact that Sun Microsystems was acquired by Oracle back in 2010.

Like other software systems, Java is updated on a regular basis; nonetheless, the computer science concepts discussed in the textbook are based on standard undergraduate curriculum taught in a CS1 course. Therefore, any updates to the textbook would need to be with regard to the version of Java with minimal effort.

Clarity rating: 4

The authors deliver clear explanations of the computer science concepts and the accompanying Java language features.

There is a consistent theme throughout much of the text: A topic is introduced and discussed within the context of a problem. Its solution is then designed and explained using UML diagrams; finally, Java is used to illustrate how the solution is implemented on the computer.

Each chapter is divided into sections that can easily be identified within the table of contents. Therefore, it’s fairly easy for a student to pick and choose a section in a chapter and work on the other sections later. Throughout each chapter, there are self-study exercises to incrementally test understanding of the covered material. Solutions to those self-study exercises are then provided towards the end of the chapter. In addition, each chapter includes end-of-chapter exercises that can be used to assess one’s understanding of the computer science concepts as well as the various features of Java.

The book consists of seventeen chapters; however, a typical CS1 course would need the material in the first ten chapters only, and those chapters are set up in a logical manner, allowing one to go through the material sequentially. Depending on how fast he first ten chapters are covered during the course of a semester, an instructor may choose from the last seven chapters in the text to introduce more advanced topics in computer science and/or Java.

Interface rating: 1

The textbook can be accessed online or opened using Acrobat Reader with no problem. There are no issues, as long as navigation is done one page after another manually. However, when browsing through the table of contents (TOC) or the Index, the entries are not set up using any live links. That is, you cannot click on a page number associated with an item within the TOC or the Index to go directly to that page.

Grammatical Errors rating: 3

This reviewer did not come across any such issues, while going through the text.

This is a computing textbook, where the contents are presented using technical terms. Culturally, the textbook is completely neutral and unbiased in terms of how the material is presented.

Table of Contents

• 0 Computers, Objects, and Java
• 1 Java Program Design and Development
• 2 Objects: Defining, Creating, and Using
• 3 Methods: Communicating with Objects
• 4 Input/Output: Designing the User Interface
• 5 Java Data and Operators
• 6 Control Structures
• 7 Strings and String Processing
• 8 Inheritance and Polymorphism
• 9 Arrays and Array Processing
• 10 Exceptions: When Things Go Wrong
• 11 Files and Streams
• 12 Recursive Problem Solving
• 13 Graphical User Interfaces
• 14 Threads and Concurrent Programming
• 15 Sockets and Networking
• 16 Data Structures: Lists, Stacks, and Queues

Ancillary Material

• Ralph Morelli, Ralph Walde

About the Book

We have designed this third edition of Java, Java, Java to be suitable for a typical Introduction to Computer Science (CS1) course or for a slightly more advanced Java as a Second Language course. This edition retains the “objects first” approach to programming and problem solving that was characteristic of the first two editions. Throughout the text we emphasize careful coverage of Java language features, introductory programming concepts, and object-oriented design principles.

The third edition retains many of the features of the first two editions, including:

• Early Introduction of Objects
• Emphasis on Object Oriented Design (OOD)
• Unified Modeling Language (UML) Diagrams
• Self-study Exercises with Answers
• Programming, Debugging, and Design Tips.
• From the Java Library Sections
• Object-Oriented Design Sections
• End-of-Chapter Exercises
• Companion Web Site, with Power Points and other Resources

The In the Laboratory sections from the first two editions have been moved onto the book's Companion Web Site. Table 1 shows the Table of Contents for the third edition.

About the Contributors

Ralph Morelli, Professor of Computer Science Emeritus. Morelli has been teaching at Trinity College since 1985, the same year the computer science major was first offered. More recently, he was one of the Principal Investigators (PIs) for the Humanitarian Free and Open Source Software (HFOSS) project, an NSF-funded effort to get undergraduates engaged in building free and open source software that benefits the public.  In summer 2011 a team of Trinity HFOSS students and faculty traveled to Haiti to build an open source mobile application that helps manage beneficiaries for a humanitarian aid organization. Currently Morelli is the PI of the Mobile CSP project, an NSF-funded effort to train high school teachers in CT and elsewhere to teach the emerging Advanced Placement CS Principles course that is being created by the College Board. The main goal of this NSF initiative is to increase access to computer science among underrepresented groups, including girls, African Americans, and Hispanic Americans.  The Mobile CSP course teaches students to create mobile apps to serve their community.  In summer 2014, a group of 20 Mobile CSP students spent their summer building mobile apps for the city of Hartford. 

Ralph Walde.  Dr. Walde has given Trinity 28 years of distinguished service, first as a Professor of Mathematics and now as a Professor of Computer Science. He was instrumental in helping to establish and nourish computing at Trinity and was one of the founding members of the Computer Science Department.

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• Title: Principles of Algorithmic Problem Solving
• Author(s) Johan Sannemo
• Publisher: KTH Royal Institute of Technology (2018)
• Hardcover/Paperback: N/A
• eBook: PDF (351 pages)
• Language: English
• ISBN-10/ASIN: N/A
• ISBN-13: N/A

Algorithmic problem solving is the art of formulating efficient methods that solve problems of a mathematical nature. The purpose of this book is to contribute to the literature of algorithmic problem solving in two ways. First of all, it tries to fill in some holes in existing books. Secondly, it provides another way of learning the basics of algorithmic problem solving by helping the reader build an intuition for problem solving.

The algorithmic approach to solving problems in computer technology is an essential tool. This unique book teaches the fundamental principles of using algorithms to solve problems. It presents a readable, entertaining, and energetic book that will motivate and challenge students to open their minds to the algorithmic nature of problem solving.

• Provides a novel approach to the mathematics of problem solving focusing on the algorithmic nature of problem solving
• Uses popular and entertaining puzzles to teach you different aspects of using algorithms to solve mathematical and computing challenges
• Features a theory section that supports each of the puzzles presented throughout the book
• Assumes only an elementary understanding of mathematics
• Computer Programming
• C++ Programming
• Algorithms and Data Structures
• Functional Programming and Lambda
• Object-Oriented Analysis, Design and Programming (OOD/OOP)
• Principles of Algorithmic Problem Solving (Johan Sannemo)
• The Mirror Site (1) - PDF
• The Mirror Site (2) - PDF

Self contained with problems completely worked out in clear, readable C++11 , covers a wide swatch of advanced programming techniques, range from specialized procedures for bit manipulation, numerical analysis, subsequence problems, and random algorithms.

A comprehensive treatment focusing on the creation of efficient data structures and algorithms, using C++. This text explains how to select or design the data structure best suited to specific problems.

This book uses Python to introduce folks to programming and algorithmic thinking. It is sharply focused on classical algorithms, but it also gives a solid understanding of fundamental algorithmic problem-solving techniques.

This is a textbook about computer science. It is also about Python. However, there is much more. The tools and techniques that you learn here will be applied over and over as you continue your study of computer science.

This book covers Analysis and Design of Algorithms, Scientific Computing, Monte Carlo Simulations, and Parallel Algorithms. It teaches the core knowledge required by any scientist interested in numerical algorithms and computational finance.

This lecture notes uniquely combines rigor and comprehensiveness. It covers a broad range of algorithms in depth, yet makes their design and analysis accessible to all levels of readers. Each chapter is relatively self-contained and can be used as a unit of study.

The goal of the book is to show you how you can methodically apply different techniques to your own algorithms to make them more efficient. While this book mostly highlights general techniques, some well-known algorithms are also looked at in depth.

This practical book will help you learn and review some of the most important ideas in software engineering - data structures and algorithms - in a way that's clearer, more concise, and more engaging than other materials. Useful in technical interviews too.

This book doesn't only focus on an imperative (or procedural) approach, but also includes purely functional algorithms and data structures. It teaches you how to think like a programmer - find the practical efficiency algorithms to solve your problems.

This book introduces algorithms by looking at the real-world problems that motivate them. The book teaches a range of design and analysis techniques for problems that arise in computing applications.

A comprehensive introduction to optimization with a focus on practical algorithms for the design of engineering systems. Readers will learn about computational approaches for a range of challenges.

This open access book demonstrates all the steps required to design heuristic algorithms for difficult optimization. The classic problem of the travelling salesman is used as a common thread to illustrate all the techniques discussed.

This textbook provides a broad introduction to algorithms for decision making under uncertainty, covering the underlying mathematical problem formulations and the algorithms for solving them.

Through investigating the everyday life of the algorithm, the book opens a conversation with existing social science research that tends to focus on the power and opacity of algorithms, via unique access to the algorithm's design, development, testing, etc.

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Open and Interactive Learning Resources for Algorithmic Problem Solving

• Conference paper
• First Online: 11 August 2020
• Cite this conference paper

• João F. Ferreira 25 &
• Alexandra Mendes 26 , 27  

Part of the book series: Lecture Notes in Computer Science ((LNPSE,volume 12233))

Included in the following conference series:

• International Symposium on Formal Methods

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1 Citations

Algorithmic problem solving is a way of approaching and solving problems by using the advances that have been made in the principles of correct-by-construction algorithm design. The approach has been taught at first-year undergraduate level since September 2003 and, since then, a substantial amount of learning materials have been developed. However, the existing materials are distributed in a conventional and static way (e.g. as a textbook and as several documents in PDF format available online), not leveraging the capabilities provided by modern collaborative and open-source platforms.

In this paper, we propose the creation of an online, open-source repository of interactive learning materials on algorithmic problem solving. We show how the existing framework Mathigon can be used to support such a repository. By being open and hosted on a platform such as GitHub, the repository enables collaboration and anyone can create and submit new material. Furthermore, by making the material interactive, we hope to encourage engagement with and a better understanding of the materials.

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Mathigon’s website: https://mathigon.org (accessed 18 July 2019).

Wikipedia link: https://en.wikipedia.org/wiki/River_crossing_puzzle (accessed 18 July 2019).

The restatement of the problem and the subsequent two paragraphs are extracted from [ 1 ].

The implementation of the puzzle that we used was created by Victor Ribeiro ( https://github.com/victorqribeiro/bridge ).

See the repository textbooks (folder content/river-crossing ) in https://github.com/algprobsolving .

MyScript webpage: https://www.myscript.com .

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Acknowledgments

This work is partially financed by National Funds through the Portuguese funding agency, FCT - Fundação para a Ciência e a Tecnologia through the project: UID/EEA/50014/2019.

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INESC-ID & Instituto Superior Técnico, University of Lisbon, Lisbon, Portugal

João F. Ferreira

Department of Informatics, Universidade da Beira Interior, Covilhã, Portugal

Alexandra Mendes

HASLab, INESC TEC, Porto, Portugal

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Correspondence to João F. Ferreira .

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McMaster University, Hamilton, ON, Canada

Emil Sekerinski

University of Porto, Porto, Portugal

Nelma Moreira

University of Minho, Braga, Portugal

José N. Oliveira

Argo Ai, Munich, Germany

Daniel Ratiu

University of Pisa, Pisa, Italy

Riccardo Guidotti

University of Liverpool, Liverpool, UK

Marie Farrell

Matt Luckcuck

University of Exeter, Exeter, UK

Diego Marmsoler

José Campos

University of Newcastle, Newcastle upon Tyne, UK

Troy Astarte

Claude Bernard University, Lyon, France

Laure Gonnord

Nazarbayev University, Nur-Sultan, Kazakhstan

Antonio Cerone

University of Surrey, Guildford, UK

Brijesh Dongol

University of Giessen, Giessen, Germany

Martin Kutrib

University of Lisbon, Lisbon, Portugal

Pedro Monteiro

Airbus Operations S.A.S., Toulouse, France

David Delmas

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Ferreira, J.F., Mendes, A. (2020). Open and Interactive Learning Resources for Algorithmic Problem Solving. In: Sekerinski, E., et al. Formal Methods. FM 2019 International Workshops. FM 2019. Lecture Notes in Computer Science(), vol 12233. Springer, Cham. https://doi.org/10.1007/978-3-030-54997-8_13

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Published : 11 August 2020

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What is Programming? A Handbook for Beginners

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Analyzing the problem. What are you trying to build?

As a developer, you would start by designing the layout of the app, how it will work, its different screens and functionality, and all the small details that will make your app an awesome tool for users around the world.

Only after you have everything carefully planned out, you can start to write your code. To do that, you will need to choose a programming language to work with. Let's see what a programming language is and why they are super important.

🔸 What is a Programing Language?

A programming language is a language that computers can understand.

We cannot just write English words in our program like this:

"Computer, solve this task!"

and hope that our computer can understand what we mean. We need to follow certain rules to write the instructions.

Every programming language has its own set of rules that determine if a line of code is valid or not. Because of this, the code you write in one programming language will be slightly different from others.

💡 Tip: Some programming languages are more complex than others but most of them share core concepts and functionality. If you learn how to code in one programming language, you will likely be able to learn another one faster.

Before you can start writing awesome programs and apps, you need to learn the basic rules of the programming language you chose for the task.

💡 Tip: a program is a set of instructions written in a programming language for the computer to execute. We usually write the code for our program in one or multiple files.

For example, this is a line of code in Python (a very popular programming language) that shows the message "Hello, World!" :

But if we write the same line of code in JavaScript (a programming language mainly used for web development), we will get an error because it will not be valid.

To do something very similar in JavaScript, we would write this line of code instead:

Visually, they look very different, right? This is because Python and JavaScript have a different syntax and a different set of built-in functions .

💡 Tip : built-in functions are basically tasks that are already defined in the programming language. This lets us use them directly in our code by writing their names and by specifying the values they need.

In our examples, **print()** is a built-in function in Python while **console.log()** is a function that we can use in JavaScript to see the message in the console (an interactive tool) if we run our code in the browser.

Examples of programming languages include Python, JavaScript, TypeScript, Java, C, C#, C++, PHP, Go, Swift, SQL, and R. There are many programming languages and most of them can be used for many different purposes.

💡 Tip: These were the most popular programming languages on the Stack Overflow Developer Survey 2022 :

There are many other programming languages (hundreds or even thousands!) but usually, you will learn and work with some of the most popular ones. Some of them have broader applications like Python and JavaScript while others (like R) have more specific (and even scientific) purposes.

This sounds very interesting, right? And we are only starting to talk about programming languages. There is a lot to learn about them and I promise you that if you dive deeper into programming, your time and effort will be totally worth it.

Awesome! Now that you know what programming is and what programming languages are all about, let's see how programming is related to binary numbers.

🔹 Programming and Binary Numbers

When you think about programming, perhaps the first thing that comes to your mind is something like the below image, right? A sequence of 0 s and 1 s on your computer.

Programming is indeed related to binary numbers ( 0 and 1 ) but in an indirect way. Developers do not actually write their code using zeros and ones.

We usually write programs in a high-level programming language, a programming language with a syntax that recognizes specific words (called keywords), symbols, and values of different data types.

Basically, we write code in a way that humans can understand.

For example, these are the keywords that we can use in Python:

Every programming language has its own set of keywords (words written in English). These keywords are part of the syntax and core functionality of the programming language.

But keywords are just common words in English, almost like the ones that we would find in a book.

That leads us to two very important questions:

• How does the computer understand and interpret what we are trying to say?
• Where does the binary number system come into play here?

The computer does not understand these words, symbols, or values directly.

When a program runs, the code that we write in a high-level programming language that humans can understand is automatically transformed into binary code that the computer can understand.

This transformation of source code that humans can understand into binary code that the computer can understand is called compilation .

According to Britannica , a compiler is defined as:

Computer software that translates (compiles) source code written in a high-level language (e.g., C++) into a set of machine-language instructions that can be understood by a digital computer’s CPU.

Britannica also mentions that:

The term compiler was coined by American computer scientist Grace Hopper , who designed one of the first compilers in the early 1950s.

Some programming languages can be classified as compiled programming languages while others can be classified as interpreted programming languages based on how to they are transformed into machine-language instructions.

However, they all have to go through a process that converts them into instructions that the computer can understand.

Awesome. Now you know why binary code is so important for computer science. Without it, basically programming would not exist because computers would not be able to understand our instructions.

Now let's dive into the applications of programming and the different areas that you can explore.

🔸 Real-World Applications of Programming

Programming has many different applications in many different industries. This is truly amazing because you can apply your knowledge in virtually any industry that you are interested in.

From engineering to farming, from game development to physics, the possibilities are endless if you learn how to code.

Let's see some of them. (I promise you. They are amazing! ⭐) .

Front-End Web Development

If you learn how to code, you can use your programming skills to design and develop websites and online platforms. Front-End Web Developers create the parts of the websites that users can see and interact with directly.

For example, right now you are reading an article on freeCodeCamp 's publication. The publication looks like this and it works like this thanks to code that front-end web developers wrote line by line.

💡 Tip: If you learn front-end web development, you can do this too.

Front-End Web Developers use HTML and CSS to create the structure of the website (these are markup languages, which are used to present information) and they write JavaScript code to add functionality and interactivity.

If you are interested in learning front-end web development, you can learn HTML and CSS with these free courses on freeCodeCamp's YouTube Channel:

• Learn HTML5 and CSS3 From Scratch - Full Course
• Learn HTML & CSS – Full Course for Beginners
• Frontend Web Development Bootcamp Course (JavaScript, HTML, CSS)
• Introduction To Responsive Web Design - HTML & CSS Tutorial

You can also learn JavaScript for free with these free online courses:

• Learn JavaScript - Full Course for Beginners
• JavaScript Programming - Full Course
• JavaScript DOM Manipulation – Full Course for Beginners
• Learn JavaScript by Building 7 Games - Full Course

💡 Tip: You can also earn a Responsive Web Design Certification while you learn with interactive exercises on freeCodeCamp.

Back-End Web Development

More complex and dynamic web applications that work with user data also require a server . This is a computer program that receives requests and sends appropriate responses. They also need a database , a collection of values stored in a structured way.

Back-End Web Developers are in charge of developing the code for these servers. They decide how to handle the different requests, how to send appropriate resources, how to store the information, and basically how to make everything that runs behind the scenes work smoothly and efficiently.

A real-world example of back-end web development is what happens when you create an account on freeCodeCamp and complete a challenge. Your information is stored on a database and you can access it later when you sign in with your email and password.

This amazing interactive functionality was implemented by back-end web developers.

💡 Tip: Full-stack Web Developers are in charge of both Front-End and Back-End Web Development. They have specialized knowledge on both areas.

All the complex platforms that you use every day, like social media platforms, online shopping platforms, and educational platforms, use servers and back-end web development to power their amazing functionality.

Python is an example of a powerful programming language used for this purpose. This is one of the most popular programming languages out there, and its popularity continues to rise every year. This is partly because it is simple and easy to learn and yet powerful and versatile enough to be used in real-world applications.

💡 Tip: if you are curious about the specific applications of Python, this is an article I wrote on this topic .

JavaScript can also be used for back-end web development thanks to Node.js.

Other programming languages used to develop web servers are PHP, Ruby, C#, and Java.

If you would like to learn Back-End Web Development, these are free courses on freeCodeCamp's YouTube channel:

• Python Backend Web Development Course (with Django)
• Node.js and Express.js - Full Course
• Full Stack Web Development for Beginners (Full Course on HTML, CSS, JavaScript, Node.js, MongoDB)
• Node.js / Express Course - Build 4 Projects

💡 Tip: freeCodeCamp also has a free Back End Development and APIs certification.

Mobile App Development

Mobile apps have become part of our everyday lives. I'm sure that you could not imagine life without them.

Think about your favorite mobile app. What do you love about it?

Our favorite apps help us with our daily tasks, they entertain us, they solve a problem, and they help us to achieve our goals. They are always there for us.

That is the power of mobile apps and you can be part of this amazing world too if you learn mobile app development.

Developers focused on mobile app development are in charge of planning, designing, and developing the user interface and functionality of these apps. They identify a gap in the existing apps and they try to create a working product to make people's lives better.

💡 Tip: regardless of the field you choose, your goal as a developer should always be making people's lives better. Apps are not just apps, they have the potential to change our lives. You should always remember this when you are planning your projects. Your code can make someone's life better and that is a very important responsibility.

Mobile app developers use programming languages like JavaScript, Java, Swift, Kotlin, and Dart. Frameworks like Flutter and React Native are super helpful to build cross-platform mobile apps (that is, apps that run smoothly on multiple different operating systems like Android and iOS).

According to Flutter 's official documentation:

Flutter is an open source framework by Google for building beautiful, natively compiled, multi-platform applications from a single codebase.

If you would like to learn mobile app development, these are free courses that you can take on freeCodeCamp's YouTube channel:

• Flutter Course for Beginners – 37-hour Cross Platform App Development Tutorial
• Flutter Course - Full Tutorial for Beginners (Build iOS and Android Apps)
• React Native - Intro Course for Beginners
• Learn React Native Gestures and Animations - Tutorial

Game Development

Games create long-lasting memories. I'm sure that you still remember your favorite games and why you love (or loved) them so much. Being a game developer means having the opportunity of bringing joy and entertainment to players around the world.

Game developers envision, design, plan, and implement the functionality of a game. They also need to find or create assets such as characters, obstacles, backgrounds, music, sound effects, and more.

💡 Tip: if you learn how to code, you can create your own games. Imagine creating an awesome and engaging game that users around the world will love. That is what I personally love about programming. You only need your computer, your knowledge, and some basic tools to create something amazing.

Popular programming languages used for game development include JavaScript, C++, Python, and C#.

If you are interested in learning game development, you can take these free courses on freeCodeCamp's YouTube channel:

• JavaScript Game Development Course for Beginners
• Learn Unity - Beginner's Game Development Tutorial
• Learn Python by Building Five Games - Full Course
• Code a 2D Game Using JavaScript, HTML, and CSS (w/ Free Game Assets) – Tutorial
• 2D Game Development with GDevelop - Crash Course
• Pokémon Coding Tutorial - CS50's Intro to Game Development

Biology, Physics, and Chemistry

Programming can be applied in every scientific field that you can imagine, including biology, physics, chemistry, and even astronomy. Yes! Scientists use programming all the time to collect and analyze data. They can even run simulations to test hypotheses.

In biology, computer programs can simulate population genetics and population dynamics. There is even an entire field called bioinformatics .

According to this article .) "Bioinformatics" by Ardeshir Bayat, member of the Centre for Integrated Genomic Medical Research at the University of Manchester:

Bioinformatics is defined as the application of tools of computation and analysis to the capture and interpretation of biological data.

Dr. Bayat mentions that bioinformatics can be used for genome sequencing. He also mentions that its discoveries may lead to drug discoveries and individualized therapies.

Frequently used programming languages for bioinformatics include Python, R, PHP, PERL, and Java.

💡 Tip: R is a programming "language and environment for statistical computing and graphics" ( source ).

An example of a great tool that scientists can use for biology is Biopython . This is a Python framework with "freely available tools for biological computation."

If you would like to learn more about how you can apply your programming skills in science, these are free courses that you can take on freeCodeCamp's YouTube channel:

• Python for Bioinformatics - Drug Discovery Using Machine Learning and Data Analysis
• R Programming Tutorial - Learn the Basics of Statistical Computing
• Learn Python - Full Course for Beginners [Tutorial]

Physics requires running many simulations and programming is perfect for doing exactly that. With programming, scientists can program and run simulations based on specific scenarios that would be hard to replicate in real life. This is much more efficient.

Programming languages that are commonly used for physics simulations include C, Java, Python, MATLAB, and JavaScript.

Chemistry also relies on simulations and data analysis, so it's a field where programming can be a very helpful tool.

In this scientific article by Dr. Ivar Ugi and his colleagues from Organisch-chemisches Institut der Technischen Universität München, they mention that:

The design of entirely new syntheses, and the classification and documentation of structures, substructures, and reactons are examples of new applications of computers to chemistry.

Scientific experiments also generate detailed data and results that can be analyzed with computer programs developed by scientists.

Think about it: writing a program to generate a box plot or a scatter plot or any other type of plot to visualize trends in thousands of measurements can save researchers a lot of time and effort. This lets them focus on the most important part of their work: analyzing the results.

💡 Tips: if you are interested in diving deeper into this, this is a list of chemistry simulations by the American Chemical Society. These simulations were programmed by developers and they are helping thousands of students and teachers around the world.

Think about it...You could build the next great simulation. If you are interested in a scientific field, I totally recommend learning how to code. Your work will be much more productive and your results will be easier to analyze.

If you are interested in learning programming for scientific applications, these are free courses on freeCodeCamp's YouTube channel:

• Python for Data Science - Course for Beginners (Learn Python, Pandas, NumPy, Matplotlib)

Data Science and Engineering

Talking about data...programming is also essential for a field called Data Science . If you are interested in answering questions through data and statistics, this field might be exactly what you are looking for and having programming skills will help you to achieve your goals.

Data scientists collect and analyze data in order to answer questions in many different fields. According to UC Berkeley in the article " What is Data Science? ":

Effective data scientists are able to identify relevant questions, collect data from a multitude of different data sources, organize the information, translate results into solutions, and communicate their findings in a way that positively affects business decisions.

There are many powerful programming languages for analyzing and visualizing data, but perhaps one of the most frequently used ones for this purpose is Python.

This is an example of the type of data visualizations that you can create with Python. They are very helpful to analyze data visually and you can customize them to your fit needs.

If you are interested in learning programming for data science, these are free courses on freeCodeCamp's YouTube channel:

• Learn Data Science Tutorial - Full Course for Beginners
• Intro to Data Science - Crash Course for Beginners
• Build 12 Data Science Apps with Python and Streamlit - Full Course
• Data Analysis with Python - Full Course for Beginners (Numpy, Pandas, Matplotlib, Seaborn)

💡 Tip: you can also earn these free certifications on freeCodeCamp:

• Data Visualization
• Data Analysis with Python

Engineering

Engineering is another field where programming can help you to succeed. Being able to write your own computer programs can make your work much more efficient.

There are many tools created specifically for engineers. For example, the R programming language is specialized in statistical applications and Python is very popular in this field too.

Another great tool for programming in engineering is MATLAB . According to its official website:

MATLAB is a programming and numeric computing platform used by millions of engineers and scientists to analyze data, develop algorithms, and create models.

Really, the possibilities are endless.

You can learn MATLAB with this crash course on the freeCodeCamp YouTube channel .

If you are interested in learning engineering tools related to programming, this is a free course on freeCodeCamp's YouTube channel that covers AutoCAD, a 2D and 3D computer-aided design software used by engineers:

• AutoCAD for Beginners - Full University Course

Medicine and Pharmacology

Medicine and pharmacology are constantly evolving by finding new treatments and procedures. Let's see how you can apply your programming skills in these fields.

Programming is really everywhere. If you are interested in the field of medicine, learning how to code can be very helpful for you too. Even if you would like to focus on computer science and software development, you can apply your knowledge in both fields.

Specialized developers are in charge of developing and writing the code that powers and controls the devices and machines that are used by modern medicine.

Think about it...all these machines and devices are controlled by software and someone has to write that software. Medical records are also stored and tracked by specialized systems created by developers. That could be you if you decide to follow this path. Sounds exciting, right?

According to the scientific article Application of Computer Techniques in Medicine :

Major uses of computers in medicine include hospital information system, data analysis in medicine, medical imaging laboratory computing, computer assisted medical decision making, care of critically ill patients, computer assisted therapy and so on.

Pharmacology

Programming and computer science can also be applied to develop new drugs in the field of pharmacology.

A remarkable example of what you can achieve in this field by learning how to code is presented in this article by MIT News. It describes how an MIT senior, Kristy Carpenter, was using computer science in 2019 to develop "new, more affordable drugs." Kristy mentions that:

Artificial intelligence, which can help compute the combinations of compounds that would be better for a particular drug, can reduce trial-and-error time and ideally quicken the process of designing new medicines.

Another example of a real-world application of programming in pharmacology is related to Python (yes, Python has many applications!). Among its success stories , we find that Python was selected by AstraZeneca to develop techniques and programs that can help scientists to discover new drugs faster and more efficiently.

The documentation explains that:

To save time and money on laboratory work, experimental chemists use computational models to narrow the field of good drug candidates, while also verifying that the candidates to be tested are not simple variations of each other's basic chemical structure.

If you are interested in learning programming for medicine or health-related fields, this is a free course on freeCodeCamp's YouTube channel on programming for healthcare imaging:

• PyTorch and Monai for AI Healthcare Imaging - Python Machine Learning Course

Have you ever thought that programming could be helpful for education? Well, let me tell you that it is and it is very important. Why? Because the digital learning tools that students and teachers use nowadays are programmed by developers.

Every time a student opens an educational app, browses an educational platform like freeCodeCamp, writes on a digital whiteboard, or attends a class through an online meeting platform, programming is making that possible.

As a programmer or as a teacher who knows how to code, you can create the next great app that will enhance the learning experience of students around the world.

Perhaps it will be a note-taking app, an online learning platform, a presentation app, an educational game, or any other app that could be helpful for students.

The important thing is to create it with students in mind if your goal is to make something amazing that will create long-lasting memories.

If you envision it, then you can create it with code.

Teachers can also teach their students how to code to develop their problem-solving skills and to teach them important skills for their future.

💡 Tip: if you are teaching students how to code, Scratch is a great programming language to teach the basics of programming. It is particularly focused on teaching children how to code in an interactive way.

According to the official Scratch website:

Scratch is the world’s largest coding community for children and a coding language with a simple visual interface that allows young people to create digital stories, games, and animations.

If you are interested in learning how to code for educational purposes, these are courses that you may find helpful on freeCodeCamp's YouTube channel:

• Scratch Tutorial for Beginners - Make a Flappy Bird Game
• Computational Thinking & Scratch - Intro to Computer Science - Harvard's CS50 (2018)
• Android Development for Beginners - Full Course

Machine Learning, Artificial Intelligence, and Robotics

Some of the most amazing fields that are directly related to programming are Machine Learning, Artificial Intelligence, and Robotics. Let's see why.

Artificial Intelligence is defined by Britannica as:

The project of developing systems endowed with the intellectual processes characteristic of humans, such as the ability to reason, discover meaning, generalize, or learn from past experience.

Machine learning is a branch or a subset of the field of Artificial Intelligence in which systems can learn on their own based on data. The goal of this learning process is to predict the expected output. These models continuously learn how to "think" and how to analyze situations based on their previous training.

The most commonly used programming languages in these fields are Python, C, C#, C++, and MATLAB.

Artificial intelligence and Machine Learning have amazing applications in various industries, such as:

• Image and object detection.
• Making predictions based on patterns.
• Text recognition.
• Recommendation engines (like when an online shopping platform shows you products that you may like or when YouTube shows you videos that you may like).
• Spam detection for emails.
• Fraud detection.
• Social media features like personalized feeds.
• Many more... there are literally millions of applications in virtually every industry.

If you are interested in learning how to code for Artificial Intelligence and Machine Learning, these are free courses on freeCodeCamp's YouTube channel:

• Machine Learning for Everybody – Full Course
• Machine Learning Course for Beginners
• PyTorch for Deep Learning & Machine Learning – Full Course
• TensorFlow 2.0 Complete Course - Python Neural Networks for Beginners Tutorial
• Self-Driving Car with JavaScript Course – Neural Networks and Machine Learning
• Python TensorFlow for Machine Learning – Neural Network Text Classification Tutorial
• Practical Deep Learning for Coders - Full Course from fast.ai and Jeremy Howard
• Deep Learning Crash Course for Beginners
• Advanced Computer Vision with Python - Full Course

💡 Tip: you can also earn a Machine Learning with Python Certification on freeCodeCamp.

Programming is also very important for robotics. Yes, robots are programmed too!

Robotics is defined by Britannica as the:

Design, construction, and use of machines (robots) to perform tasks done traditionally by human beings.

Robots are just like computers. They do not know what to do until you tell them what to do by writing instructions in your programs. If you learn how to code, you can program robots and industrial machinery found in manufacturing facilities.

If you are interested in learning how to code for robotics, electronics, and related fields, this is a free course on Arduino on freeCodeCamp's YouTube channel:

• Arduino Course for Beginners - Open-Source Electronics Platform

Other Applications

There are many other fascinating applications of programming in almost every field. These are some highlights:

• Agriculture: in this article by MIT News, a farmer developed an autonomous tractor app after learning how to code.
• Self-driving cars: autonomous cars rely on software to analyze their surroundings and to make quick and accurate decisions on the road. If you are interested in this area, this is a course on this topic on freeCodeCamp's YouTube channel.
• Finance: programming can also be helpful to develop programs and models that predict financial indicators and trends. For example, this is a course on algorithmic trading on freeCodeCamp's YouTube channel.

The possibilities are endless. I hope that this section will give you a notion of why learning how to code is so important for your present and for your future. It will be a valuable skill to have in any field you choose.

Awesome. Now let's dive into the soft skills that you need to become a successful programmer.

🔹 Skills of a Successful Programmer

After going through the diverse range of applications of programming, you must be curious to know what skills are needed to succeed in this field.

A programmer should be curious. Whether you are just starting to learn how to code or you already have 20 years of experience, coding projects will always present you with new challenges and learning opportunities. If you take these opportunities, you will continously improve your skills and succeed.

Enthusiasm is a key trait of a successful programmer but this applies in general to any field if you want to succeed. Enthusiasm will keep you happy and curious about what you are creating and learning.

💡 Tip: If you ever feel like you are not as enthusiastic as you used to be, it's time to find or learn something new that can light the spark in you again and fill you with hope and dreams.

A programmer must be patient because transforming an initial idea into a working product can take time, effort, and many different steps. Patience will keep you focused on your final goal.

Programming can be challenging. That is true. But what defines you is not how many challenges you face, it's how you face them. If you thrive despite these challenges, you will become a better programmer and you could create something that could change the world.

Programmers must be creative because even though every programming language has a particular set of rules for writing the code, coding is like using LEGOs. You have the building-blocks but you need to decide what to create and how to create it. The process of writing the code requires creativity while following the established best practices.

Problem-solving and Analysis

Programming is basically analyzing and solving problems with code. Depending on your field of choice, those problems will be simpler or more complex but they will all require some level of problem-solving skills and a thorough analysis of the situation.

Questions like:

• What should I build?
• How can I build it?
• What is the best way to build this?

Are part of the everyday routine of a programmer.

Ability to Focus for Long Periods of Time

When you are working on a coding project, you will need to focus on a task for long periods of time. From creating the design, to planning and writing the code, to testing the result, and to fixing bugs (issues with the code), you will dedicate many hours to a particular task. This is why it's essential to be able to focus and to keep your final goal in mind.

Taking Detailed Notes

This skill is very important for programmers, particularly when you are learning how to code. Taking detailed notes can be help you to understand and remember the concepts and tools you learn. This also applies for experienced programmers, since being a programmer involves life-long learning.

Communication

Initially, you might think that programming is a solitary activity and imagine that a programmer spends hundreds of hours alone sitting on a desk.

But the reality is that when you find your first job, you will see that communication is super important to coordinate tasks with other team members and to exchange ideas and feedback.

Open to Feedback

In programming, there is usually more than one way to implement the same functionality. Different alternatives may work similarly, but some may be easier to read or more efficient in terms of time or resource consumption.

When you are learning how to code, you should always take constructive feedback as a tool for learning. Similarly, when you are working on a team, take your colleagues' feedback positively and always try to improve.

Life-long Learning

Programming equals life-long learning. If you are interested in learning how to code, you must know that you will always need to be learning new things as new technologies emerge and existing technologies are updated. Think about it... that is great because there is always something interesting and new to learn!

Open to Trying New Things

Finally, an essential skill to be a successful programmer is to be open to trying new things. Step out of your comfort zone and be open to new technologies and products. In the technology industry, things evolve very quickly and adapting to change is essential.

🔸 Tips for Learning How to Code

Now that you know more about programming, programming languages, and the skills you need to be a successful programmer, let's see some tips for learning how to code.

💡 Tip: these tips are based on my personal experience and opinions.

• Choose one programming language to learn first. When you are learning how to code, it's easy to feel overwhelmed with the number of options and entry paths. My advice would be to focus on understanding the essential computer science concepts and one programming language first. Python and JavaScript are great options to start learning the fundamentals.
• Take detailed notes. Note-taking skills are essential to record and to analyze the topics you are learning. You can add custom comments and annotations to explain what you are learning.
• Practice constantly. You can only improve your problem-solving skills by practicing and by learning new techniques and tools. Try to practice every day.

💡 Tip: There is a challenge called the #100DaysOfCode challenge that you can join to practice every day.

• Always try again. If you can't solve a problem on your first try, take a break and come back again and again until you solve it. That is the only way to learn. Learn from your mistakes and learn new approaches.
• Learn how to research and how to find answers. Programming languages, libraries, and frameworks usually have official documentations that explain their built-in elements and tools and how you can use them. This is a precious resource that you should definitely refer to.
• Browse Stack Overflow . This is an amazing platform. It is like an online encyclopedia of answers to common programming questions. You can find answers to existing questions and ask new questions to get help from the community.
• Set goals. Motivation is one of the most important factors for success. Setting goals is very important to keep you focused, motivated, and enthusiastic. Once you reach your goals, set new ones that you find challenging and exciting.
• Create projects. When you are learning how to code, applying your skills will help you to expand your knowledge and remember things better. Creating projects is the perfect way to practice and to create a portfolio that you can show to potential employers.

🔹 Basic Programming Concepts

Great. If reading this article has helped you confirm that you want to learn programming, let's take your first steps.

These are some basic programming concepts that you should know:

• Variable: a variable is a name that we assign to a value in a computer program. When we define a variable, we assign a value to a name and we allocate a space in memory to store that value. The value of a variable can be updated during the program.
• Constant: a constant is similar to a variable. It stores a value but it cannot be modified. Once you assign a value to a constant, you cannot change it during the entire program.
• Conditional: a conditional is a programming structure that lets developers choose what the computer should do based on a condition. If the condition is True, something will happen but if the condition is False, something different can happen.
• Loop: a loop is a programming structure that let us run a code block (a sequence of instructions) multiple times. They are super helpful to avoid code repetition and to implement more complex functionality.
• Function: a function helps us to avoid code repetition and to reuse our code. It is like a code block to which we assign a name but it also has some special characteristics. We can write the name of the function to run that sequence of instructions without writing them again.

💡 Tip: Functions can communicate with main programs and main programs can communicate with functions through parameters , arguments , and return statements.

• Class: a class is used as a blueprint to define the characteristics and functionality of a type of object. Just like we have objects in our real world, we can represent objects in our programs.
• Bug: a bug is an error in the logic or implementation of a program that results in an unexpected or incorrect output.
• Debugging: debugging is the process of finding and fixing bugs in a program.
• IDE: this acronym stands for Integrated Development Environment. It is a software development environment that has the most helpful tools that you will need to write computer programs such as a file editor, an explorer, a terminal, and helpful menu options.

💡 Tip: a commonly used and free IDE is Visual Studio Code , created by Microsoft.

Awesome! Now you know some of the fundamental concepts in programming. Like you learned, each programming language has a different syntax, but they all share most of these programming structures and concepts.

🔸 Types of Programming Languages

Programming languages can be classified based on different criteria. If you want to learn how to code, it's important for you to learn these basic classifications:

• High-level programming languages: they are designed to be understood by humans and they have to be converted into machine code before the computer can understand them. They are the programming languages that we commonly use. For example: JavaScript, Python, Java, C#, C++, and Kotlin.
• Low-level programming languages: they are more difficult to understand because they are not designed for humans. They are designed to be understood and processed efficiently by machines.

Conversion into Machine Code

• Compiled programming languages: programs written with this type of programming language are converted directly into machine code by a compiler. Examples include C, C++, Haskell, and Go.
• Interpreted programming languages: programs written with this type of programming language rely on another program called the interpreter, which is in charge of running the code line by line. Examples include Python, JavaScript, PHP, and Ruby.

💡 Tip: according to this article on freeCodeCamp's publication:

Most programming languages can have both compiled and interpreted implementations – the language itself is not necessarily compiled or interpreted. However, for simplicity’s sake, they’re typically referred to as such.

There are other types of programming languages based on different criteria, such as:

• Procedural programming languages
• Functional programming languages
• Object-oriented programming languages
• Scripting languages
• Logic programming languages

And the list of types of programming languages continues. This is very interesting because you can analyze the characteristics of a programming language to help you choose the right one for your project.

🔹 How to Contribute to Open Source Projects

Finally, you might think that coding implies sitting at a desk for many hours looking at your code without any human interaction. But let me tell you that this does not have to be true at all. You can be part of a learning community or a developer community.

Initially, when you are learning how to code, you can participate in a learning community like freeCodeCamp. This way, you will share your journey with others who are learning how to code, just like you.

Then, when you have enough skills and confidence in your knowledge, you can practice by contributing to open source projects and join developer communities.

Open source software is defined by Opensource.com as:

Software with source code that anyone can inspect, modify, and enhance.

GitHub is an online platform for hosting projects with version control. There, you can find many open source projects (like freeCodeCamp ) that you can contribute to and practice your skills.

💡 Tip: many open source projects welcome first-time contributions and contributions from all skill levels. These are great opportunities to practice your skills and to contribute to real-world projects.

Contributing to open source projects on GitHub is great to acquire new experience working and communicating with other developers. This is another important skill for finding a job in this field.

Working on a team is a great experience. I totally recommend it once you feel comfortable enough with your skills and knowledge.

You did it! You reached the end of this article. Great work. Now you know what programming is all about. Let's see a brief summary.

🔸 In Summary

• Programming is a very powerful skill. If you learn how to code, you can make your vision come true.
• Programming has many different applications in many different fields. You can find an application for programming in basically any field you choose.
• Programming languages can be classified based on different criteria and they share basic concepts such as variables, conditionals, loops, and functions.
• Always set goals and take detailed notes. To succeed as a programmer, you need to be enthusiastic and consistent.

Thank you very much for reading my article. I hope you liked it and found it helpful. Now you know why you should learn how to code.

🔅 I invite you to follow me on Twitter ( @EstefaniaCassN ) and YouTube ( Coding with Estefania ) to find coding tutorials.

I'm a software developer, technical writer and online instructor. I love writing detailed articles with diagrams and step by step explanations.

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