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desklibai · 25 days ago

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Desklib: Your Smart Academic Companion for Smarter Learning

In today’s digital era, students and educators are no longer limited to traditional textbooks and handwritten notes. The rise of artificial intelligence has transformed how we learn, teach, and evaluate knowledge. At the forefront of this educational revolution is Desklib — an all-in-one academic platform powered by cutting-edge AI tools like AI Grader, AI Code Checker, AI Quiz, AI Answers, AI Paraphraser, Study Documents, AI Detector, and Plagiarism Checker.

Whether you're preparing for exams, writing research papers, coding assignments, or even creating interactive quizzes, Desklib offers a suite of intelligent tools that simplify your learning journey. Let’s dive into how each feature can empower you to study smarter, not harder.

📚 Why Desklib Stands Out in Today’s Academic Landscape

With so many online platforms promising academic success, what makes Desklib different? It’s not just another website—it’s your personal academic assistant. Designed with real users in mind, Desklib blends artificial intelligence with human-centric design, making it easy, intuitive, and effective for learners of all ages.

Let’s explore the powerful tools that make Desklib a must-have for students, teachers, and professionals alike.

✅ AI Grader – Instant Feedback That Helps You Improve

Grading can be time-consuming and subjective—especially when dealing with essays, short answers, or complex problem sets. Enter AI Grader, a smart grading system that evaluates written responses quickly and accurately.

This tool uses natural language processing to understand context, grammar, structure, and content quality. Whether you're a teacher managing a class of 50 or a student practicing essay writing, AI Grader provides:

Instant feedback

Detailed scoring

Suggestions for improvement

Consistent evaluation standards

It’s like having a virtual teaching assistant available 24/7.

💻 AI Code Checker – Debug Like a Pro

For programming students and developers, writing clean, functional code is essential. But even the best coders make mistakes. That’s where the AI Code Checker comes in.

This tool scans your code for syntax errors, logical flaws, and performance issues. It supports multiple languages like Python, Java, C++, and more. What makes it stand out?

Real-time error detection

Intelligent suggestions for optimization

Explanation of common bugs

Integration with popular IDEs

Whether you're working on a university project or prepping for a technical interview, the AI Code Checker ensures your code is clean, efficient, and ready to run.

🧠 AI Quiz – Turn Learning Into a Game

Learning should be fun—and with AI Quiz, it is. This interactive tool transforms your study material into engaging quizzes tailored to your understanding level.

How does it work?

Input your topic or upload a document

Choose quiz type: MCQs, fill-in-the-blanks, true/false

Get instant results with explanations

Perfect for revision, test prep, or classroom engagement, AI Quiz keeps learners motivated and helps reinforce key concepts through gamification.

Teachers can also use this feature to create dynamic assessments and monitor student progress in real-time.

❓ AI Answers – Your Personal Knowledge Assistant

Got a question? Ask AI Answers. Whether it's a tricky math problem, a historical event, or a scientific concept, this tool gives you quick, accurate, and reliable responses based on credible sources.

Unlike generic search engines, AI Answers doesn’t just give you links—it gives you clear, concise explanations. Ideal for:

Homework help

Quick fact-checking

Concept clarification

Research support

Think of it as your 24/7 academic tutor, always ready to assist.

🔄 AI Paraphraser – Reword Without Losing Meaning

Originality is crucial in academic writing. But sometimes, finding the right way to rephrase a sentence without changing its meaning can be tough. That’s where AI Paraphraser shines.

This advanced tool understands context, tone, and intent. It helps you:

Avoid plagiarism

Enhance clarity

Improve readability

Maintain original meaning

Whether you’re rewriting an essay, preparing a presentation, or summarizing research, the AI Paraphraser ensures your work stays authentic and impactful.

🗂️ Study Documents – Organize, Store & Share

Managing study materials can be chaotic. With Study Documents, you can store, categorize, and access all your files in one place. No more lost PDFs or cluttered folders.

Features include:

Cloud-based storage

Easy tagging and search

Collaborative sharing

Offline access

Ideal for group projects, research teams, or individual learners, Study Documents brings order to your academic life.

🔍 AI Detector – Spot AI-Written Content Fast

As AI-generated text becomes more prevalent, maintaining authenticity in academic work is more important than ever. The AI Detector analyzes text to determine if it was written by a human or generated by AI.

Why use it?

Ensure academic integrity

Detect AI-written essays

Maintain fairness in assessments

Promote genuine learning

Educators, institutions, and students can rely on this tool to uphold high standards of originality and critical thinking.

🚫 Plagiarism Checker – Protect Your Original Work

Plagiarism is a serious offense in academia. To ensure your work is truly yours, Desklib offers a powerful Plagiarism Checker that scans your documents against billions of web pages and academic databases.

Key benefits:

Comprehensive similarity reports

Source identification

Multiple file format support

Fast and accurate results

Use it before submitting assignments, publishing research, or presenting at conferences to maintain credibility and avoid unintentional copying.

💬 Real Stories from Real Users

Don’t just take our word for it. Hear from students and educators who’ve made Desklib part of their daily routine.

"The Plagiarism Checker helped me catch accidental duplication in my thesis. I submitted confidently knowing my work was original." – Priya, PhD Candidate

"I use AI Answers every day for quick homework help. It saves me so much time!" – Noah, High School Student

"AI Grader changed how I assess my students. It's fast, fair, and gives them valuable insights." – Mr. Johnson, University Professor

These stories reflect the real impact Desklib has on everyday learning.

📰 Stay Updated with Our Blog

At Desklib, we believe learning never stops. That’s why we regularly publish articles, guides, and expert tips on our blog. From mastering AI tools to improving study habits, there’s always something new to discover.

Check out our latest posts:

“How to Ace Your Coding Assignments Using AI”

“Top 5 Tips for Effective Exam Revision”

“Understanding AI Ethics in Education”

Stay ahead of the curve with expert insights and actionable advice.

🌐 Visit Desklib Today!

Ready to experience the future of learning? Explore everything Desklib has to offer at https://desklib.com/. Whether you're a student, educator, researcher, or professional, our AI-powered tools are designed to support your academic goals.

From AI Grader to Plagiarism Checker, Desklib empowers you to learn smarter, write better, and stay ahead of the competition.

🧩 Final Thoughts: Embrace AI for Better Learning

Artificial Intelligence is no longer a futuristic concept—it's here, and it's transforming education. Tools like AI Grader, AI Code Checker, AI Quiz, AI Answers, AI Paraphraser, Study Documents, AI Detector, and Plagiarism Checker are becoming essential components of modern learning.

By integrating these technologies into your study routine, you open doors to:

Improved efficiency

Deeper understanding

Enhanced creativity

Greater academic success

So why wait? Discover the power of AI with Desklib and unlock your full potential.

👉 Start your journey today at https://desklib.com/. Join thousands of students and educators who are already embracing smarter learning.

#AI Grader #AI Code Checker #AI Quiz #AI Answers #AI Paraphraser #Study Documents #AI Detector #Plagiarism Checker #Desklib

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guide-wire-masters · 4 months ago

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🚀 Quiz Time! 🚀

Think you know Guidewire? 🤓 Let's test your knowledge!

💡 Question: Guidewire is built on which programming language? 🤔

A) Python 🐍 B) C++ 💻 C) JavaScript .JS 🌐 D) Java ☕

💬 Drop your answer in the comments & tag your tech buddies to challenge them! 👇🔥

✅ Want to learn more?

📞 Call us: +91 9885118899

#Guidewire #GuidewireMasters #TechQuiz #Java #InsuranceTech #ITTraining #CodingLife #SoftwareDevelopment

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fromdevcom · 6 months ago

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While learning how to program certainly can be a challenge for many people, there’s a lot of resources available to gain a more in-depth view on the different aspects of C++ programming. It is true, you can learn how to do practically everything online these days, we’ve selected the best platforms to teach you the C++ languages. No one ever learned an in-depth skill simply by reading about it, the true programming experts spend hours upon hours developing new skills. The best way to learn C++ is by utilizing these resources and practicing day after day. Although C++ is a fairly difficult programming language, its one of the most popular languages utilized primarily by application software systems, drivers, and client-server applications. For beginners, it’s wise to start off with a more simple language such as java or python. Once you’ve mastered the basics of these simpler languages you’re ready to plunge into the programming world of C++ and begin learning with these different tools. LearnCpp.com This is an excellent place to start when beginning to learn the C++ language. The tutorials follow a very relevant chronology building slowly upon skills you master along the way. Each tutorial offers plenty of examples and ways to practice the skill. In addition, following each tutorial the site offers you a quiz to confirm you’ve actually mastered the skills in the tutorial. On this site they cover everything from the very basics for people who have never coded in their lives, to more advanced topics for experienced programmers looking to learn more specific functions. CPlusPlus.com While this site does include several different tutorials, it’s best used as more of a point of reference to guide you in your studies. If you get stuck on certain terminology or concepts, you can look up great applied definitions or techniques on this site. That being said, the site isn’t created for beginners so some of the programming jargon used can get a bit complex. Cprogramming.com Cprogramming contains tutorials and a whole wealth of other information for both C language and C++ language. This is a great gateway for you to gain knowledge in both similar languages, the tutorials are guided by the same person so if you’re successful with one language you’ll likely pick up the other pretty easily. Written in relatively easy to understand language this site would also be a great pick for beginners in the programming field. TheNewBoston.com The New Boston contains over 70 different tutorials and a forum of people talking about C++ language answering one another’s questions and helping each other learn. The video tutorials are provided in a way that allows the user to work toward finishing a specific project, keeping you more engaged and attentive throughout the learning process. Users also enjoy the new boston’s technique because it provides humor and more interaction. Coursera.org This site provides lectures that take a different approach to learning the C++ language, if you’ve already become familiar and have a basic understanding of the C language they teach you relevant information to master C++ from where you already stand. They recommend at least one years worth of experience mastering the C language before starting with this program, but they do offer promising results; like the ability to write basic graph algorithms such as the shortest path algorithm. Witbit.net Witbit also offers an apple and android app that features their ‘Wibisodes’ to educate new or experienced programmers on the go. They offer a very easy to use and appealing interface and their premise is complete, comprehensive, and linear classes not to waste the user’s time with repetitive information. The curriculum starts off with a basic knowledge of programming and from there can introduce you to C, C++, C#, or javascript depending on the direction you’d like to take it. Tutorialspoint.com The C++ basics program hosted by Tutorials

Point is created for beginners wanting to learn the language for the first time, and it’s intended to take them all the way through to more advanced concept mastery. The site provides its users with a lot of useful resources and guides in addition to their many tutorials. TopTal Blog Post: How to Learn the C and C++ Languages: The Ultimate List This site has a great list of more resources for C++, not limited to the internet with a fair share of books as wells. Not only do they share resources but they also cite a quite in-depth summary of the history of the language and the systems you need to get started. Great place for entry into the language. Icce.rug.nl These annotations are intended for anyone knowledgeable in C or any other C-like language i.e. perl or java and would like to know more or make the transition to C++. This resource is also used for Frank’s C++ programming courses, and at the University of Groningen. Isocpp.org This resource is a great source for bloggers, beginners with questions with an immense selection of FAQ, and chatters with their easy-to-use forum. This will keep you up to date with the latest news regarding C++ and users can share their mistakes and errors to learn from one another. Boost C++ Libraries This book is an introduction to the Boost C++ Libraries which complement the C++ standard by adding functions helpful in practice. As the Boost C++ Libraries are based on the C++ standard, they are implemented using state-of-the-art C++. They are platform independent and are supported on many operating systems including Windows and Linux by a large developer community. Stroustrup.com Here, you can gain a brief overview about what C++11 has to offer C++ coders. The aim is to help users utilize the full potential of the new facilities, and generally answer any questions about use and what the new features will provide. Yosefk.com This is C++ FQA Lite. C++ is a general-purpose programming language, not necessarily suitable for your special purpose.This is a lite version because it doesn’t yet include some of the newer data regarding C++11, the site manager is always open to new edits, so you can be the first to contribute this information. Cs.rit.edu Another C++ Lite FAQ, this one is offered in multiple different languages, including chinese, french, portuguese, etc. They also have a great embedded search tool so you can easily find what you’re looking for in the massive amount of frequently asked questions. Faqs.org Using their complete comprehensive library selection, you have the ability to browse through tons of content outlining C++ regarding questions people have previously asked, peoples responses, and programs that people can upload themselves. Best C++ PDF and eBooks to Download Beginner's Guide To C++ An exclusive C++ ebook focused on beginners. This ebook is created by udemy and available online for free learning. Object Technology The C++ programming language provides a model of memory and computation that closely matches that of most computers. In addition, it provides powerful and flexible mechanisms for abstraction; that is, language constructs that allow the programmer to introduce and use new types of objects that match the concepts of an application. Matters Computational This is a book for the computationalist, whether a working programmer or anyone interested in methods of computation. The focus is on material that does not usually appear in textbooks on algorithms. Where necessary the underlying ideas are explained and the algorithms are given formally. It is assumed that the reader is able to understand the given source code, it is considered part of the text. We use the C++ programming language for low-level algorithms. C++ Succinctly C++ Succinctly was written to help professional C# developers learn modern C++ programming. The aim of this book is to leverage your existing C# knowledge in order to expand your skills. The C++ language is indeed very complex and it won’t come to you overnight.

No matter which method you select it will take a lot of additional effort and commitment on your part to practicing and comprehending this complex language. With the right amount of dedication and patience you will be fluent in C++ and coding your own programs in no time. Legacy / Removed Resources Archive This section contains the legacy resources that were listed on this page, but not available anymore. Ureddit.com The University of Reddit offers classes and tutorials in C++ as well. Reddit has a University page which allows their users to become knowledgeable in a broad number of fields. Among these is computer science where you can take beginner C++ programming guided tutorials. It also takes you to the Reddit forum, where programmers are talking about C++ where you can learn the basics or ask for answers to your more difficult questions. PenguinProgrammer.co.uk At the Penguin Programmer they believe that C++ isn’t a language for just experienced programmers, in fact they believe it’s an excellent starting point for anyone that wants to get involved in the programming world. They break it down and start with the very basics, i.e. how to get your message up on the screen. From there they guide you through a 20 step process and in the end you’ll be fluent in C++. CppInstitute.org The C++ Institute is comprised of IT professionals, programming specialists, educational establishments, and organizations. Together they have worked with Pearson to create the world’s first C language C and C++ certification tests. With the certification program they ensure that the participant is knowledgeable in the field and complete various tasks. They have both online classes where you can teach yourself as well as academy programs. Gametutorials.com This site shows a comprehensive output text on the screen. You’ll begin with the basics of C++ for gaming like “headerfile” and “main()” and work your way up through the console to more complex features like polymorphism and singletons. Relisoft.com Reliable software begins their windows API tutorial with the most basic windows program and works their way into more generic programs. This tutorial discusses C++ within the context of windows API, used to allow two or more applications to talk to one another. Bloodshed.net This is a great resource for those of you interested in devC++. The graphical interface is easy to use for people who have any experience using Microsoft products or visual C++. The DevC++ package works great for compiling programs for the windows architecture, it can also be configured with other GNU tools. C++ GUI The purpose of this book is to teach you how to write GUI programs using Qt 3. The book starts with “Hello Qt” and quickly moves on to more advanced topics, such as creating custom widgets and providing drag and drop. An Introduction To C++ Programming I intend to teach C++ in a way that makes use of what the language can offer. C++ shares the same low level constructs as C, however, and I will assume some knowledge of C in this course. You might want to have a look at the C introduction course to get up to speed on that language. An Introduction To OOP Using C++ This tutorial is a collection of lectures to be held in the on-line course Introduction to Object-Oriented Programming Using C++ . In this course, object-orientation is introduced as a new programming concept which should help you in developing high quality software. Object-orientation is also introduced as a concept which makes developing of projects easier. How To Think Like A Computer Scientist With C++ The goal of this book is to teach you to think like a computer scientist. I like the way computer scientists think because they combine some of the best features of Mathematics, Engineering, and Natural Science. Like mathematicians, computer scientists use formal languages to denote ideas. A Beginners C++ This e-book will teach you how to "command language" for a computer system, (e.

g. Unix shell or DOS commands), an editor (specialised word processor), a "make" system that organizes the compilation of groups of files, a compiler, a linking-loader and its associated libraries. Programming In C++ Rules And Regulations The purpose of this document is to define one style of programming in C++. The rules and recommendations presented here are not final, but should serve as a basis for continued work with C++. This collection of rules should be seen as a dynamic document; suggestions for improvements are encouraged. C++ In Action The first part teaches C++, the language of choice for general-purpose programming. But it is not your usual C++ tutorial. For the beginner who doesn't know much about C or C++, it just introduces a new object oriented language. Eli Lopian is the Founder and Head of Products & Technology at Typemock. He enjoys a white board, code and transforming developing environments. Secretly his one true love is Unit Testing and he has dedicated his life to making unit testing easier for everyone else. Quizlet: Learn With Flashcards Quizlet is a powerful Flashcard app that can help you memorize new words. Flashcards are common way to memorize words for competitive exams.

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unicminds-codingforkids · 6 months ago

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#Java Quiz

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techgeek001 · 7 months ago

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Python Programming for Beginners: Your Gateway to Coding Success

In today’s tech-driven world, programming is no longer a niche skill—it’s a valuable asset across industries. Among the various programming languages, Python stands out as the perfect starting point for beginners. Known for its simplicity, readability, and versatility, Python has become the go-to language for anyone entering the coding world. Whether you want to build websites, analyze data, or create automation scripts, Python offers endless possibilities. This blog explores why Python is ideal for beginners and how it can set you on the path to coding success.

Why Choose Python as Your First Programming Language?

Simple and Easy to Learn Python’s syntax is clean and straightforward, resembling plain English, which makes it easier for beginners to grasp. Unlike more complex languages like Java or C++, Python allows you to write fewer lines of code to achieve the same result, reducing the learning curve significantly.

Versatility Across Industries Python is a versatile language used in various fields, including web development, data science, artificial intelligence, automation, and more. This broad applicability ensures that once you learn Python, you’ll have numerous career paths to explore.

Large and Supportive Community Python has a massive global community of developers who contribute to its continuous improvement. For beginners, this means access to an abundance of tutorials, forums, and resources that can help you troubleshoot problems and accelerate your learning.

Wide Range of Libraries and Frameworks Python boasts an extensive library ecosystem, which makes development faster and more efficient. Popular libraries like NumPy and Pandas simplify data manipulation, while Django and Flask are widely used for web development. These tools allow beginners to build powerful applications with minimal effort.

Getting Started with Python: A Beginner’s Roadmap

Install Python The first step is to install Python on your computer. Visit the official Python website and download the latest version. The installation process is simple, and Python comes with IDLE, its built-in editor for writing and executing code.

Learn the Basics Begin by mastering basic concepts such as:

Variables and Data Types

Control Structures (if-else statements, loops)

Functions and Modules

Input and Output Operations

Practice with Small Projects Start with simple projects to build your confidence. Some ideas include:

Creating a basic calculator

Building a to-do list app

Writing a program to generate random numbers or quiz questions

Explore Python Libraries Once you’re comfortable with the basics, explore popular libraries like:

Matplotlib: For data visualization

BeautifulSoup: For web scraping

Pygame: For game development

Join Coding Communities Participate in online coding communities such as Stack Overflow, Reddit’s r/learnpython, or join coding bootcamps. Engaging with other learners can provide motivation and helpful insights.

Accelerate Your Learning with Python Training

If you’re serious about mastering Python, consider enrolling in a professional course. For those in Chennai, Python Training in Chennai offers comprehensive programs designed to help beginners and experienced developers alike. These courses provide hands-on training, expert mentorship, and real-world projects to ensure you become job-ready.

Benefits of Learning Python for Your Career

High Demand in the Job Market Python is one of the most in-demand programming languages, with companies seeking developers for roles in web development, data science, machine learning, and automation. Mastering Python can open doors to lucrative job opportunities.

Flexible Work Opportunities Python skills are valuable in both traditional employment and freelance work. Many Python developers work remotely, offering flexibility and the chance to collaborate on global projects.

Foundation for Advanced Technologies Python is the backbone of many emerging technologies like AI, machine learning, and data analytics. Learning Python provides a strong foundation to dive deeper into these cutting-edge fields.

Conclusion

Python programming is more than just a coding language—it’s a gateway to endless opportunities. Its simplicity, versatility, and robust community support make it the ideal language for beginners. By mastering Python, you’ll not only gain valuable technical skills but also open the door to a wide range of career possibilities in the ever-expanding tech industry.

Embark on your coding journey with Python today, and unlock the potential to shape your future in technology!

#python #programming #coding

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spark-solution055 · 9 months ago

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Are You Ready to Be a Software Developer? Take the Ultimate Quiz!

Introduction

The world of software development is booming, with job opportunities and career growth on the rise. But becoming a software developer isn't just about learning a few programming languages. It requires a certain mindset, technical know-how, and the ability to tackle complex problems. So, how do you know if you're ready for this journey?

This quiz is designed to help you figure out if you have the right mix of passion, skills, and work habits to thrive as a software developer. Whether you're just starting to dabble in coding or you've been contemplating a career switch, these questions will help you assess your readiness for the path ahead.

Understanding the Basics of Software Development

What Does a Software Developer Do?

Software developers design, code, and maintain applications that run on computers, mobile devices, and even smart appliances. Whether it's developing a mobile app, creating enterprise software, or maintaining a website’s back-end infrastructure, developers are responsible for transforming ideas into functional software. Their daily tasks can include writing code, debugging software, and collaborating with other developers or designers.

Common Programming Languages

Some of the most popular programming languages include Python, Java, and JavaScript. These languages are widely used across different platforms and industries, making them a great starting point for aspiring developers. Each language has its own strengths; for example, Python is known for its simplicity and readability, while Java is highly regarded for its versatility and performance.

The Importance of Problem-Solving Skills

At its core, software development is about problem-solving. Developers need to break down complex issues and come up with efficient solutions, often by writing code. If you enjoy tackling challenges, analyzing systems, and thinking critically, you're already on the right track.

Quiz Part 1: Do You Have the Right Mindset for Software Development?

Question 1: Are You Passionate About Technology?

Software development isn’t just a job; it’s a commitment to staying on top of ever-evolving technology. Passion is what fuels many developers to continue learning and growing, even after facing obstacles or challenges.

Question 2: Do You Enjoy Problem-Solving?

If you're someone who loves puzzles or finding solutions to tough problems, software development will feel like a natural fit. Developers often need to think creatively and logically to solve coding issues.

Question 3: How Do You Handle Frustration?

Coding can be frustrating, especially when a bug refuses to be squashed. Developers need to be resilient, willing to troubleshoot, and ready to spend hours fixing a seemingly tiny issue.

Quiz Part 2: Assessing Your Technical Knowledge

Question 4: Have You Dabbled in Coding?

If you've already played around with coding—whether through a basic course or self-learning—you're already a step ahead. Early exposure to coding is a great way to gauge if it's something you truly enjoy.

Question 5: Are You Comfortable Learning New Languages?

Software development involves learning and mastering various programming languages. If you're open to continuously learning new technologies, you'll be more adaptable as the industry evolves.

Question 6: Do You Understand Basic Algorithms?

Understanding how algorithms work is crucial for efficient coding. Algorithms help developers write programs that can process data and perform complex calculations quickly and efficiently.

Quiz Part 3: Work Style and Collaboration in Software Development

Question 7: Can You Work Well in Teams?

Software development often involves collaboration. If you can work well with others, including designers, project managers, and fellow developers, you'll find it easier to thrive in team-based projects.

Question 8: Are You Self-Disciplined and Self-Motivated?

While collaboration is essential, developers also need the discipline to work independently. Self-motivation is crucial when debugging code or managing long-term projects.

Question 9: How Do You Handle Feedback?

In software development, feedback is vital. Whether it's from a code review or a project manager, being able to accept and apply constructive criticism is key to improving your skills.

Quiz Part 4: Do You Have the Patience for Long-Term Projects?

Question 10: Are You Comfortable with Delayed Gratification?

Software projects can take weeks, months, or even years to complete. If you're the kind of person who can wait for long-term rewards and stay motivated throughout the process, you'll handle the life of a developer well.

Question 11: Do You Thrive on Continuous Improvement?

The software world is constantly evolving. Developers must be comfortable with continuously refining their work and learning new skills to stay relevant.

Analyzing Your Quiz Results: What Do They Mean?

Scoring Your Results

Now that you've answered all the questions, it's time to analyze your results! Here's how you can interpret your responses:

If you answered "Yes" to 8-11 questions: Congratulations! You're highly likely to succeed as a software developer. You have the right mindset, skills, and work habits needed to thrive in this career. If you're not already coding, now's the perfect time to dive in!

If you answered "Yes" to 5-7 questions: You're well on your way, but there are a few areas you might want to focus on improving. Perhaps it's building your technical skills or developing the patience needed for long-term projects. With a little extra effort, you'll be ready to start your developer journey.

If you answered "Yes" to 4 or fewer questions: You might need to spend some time considering if software development is the right path for you. It's important to love both the process and the challenges. However, don't be discouraged! You can always work on building your skills and mindset over time.

How to Improve Your Software Development Skills

If you're excited about becoming a software developer but feel you need to improve certain areas, don’t worry! There are plenty of ways to boost your readiness.

Developing a Growth Mindset

A growth mindset is all about believing that you can improve your abilities with effort and persistence. In software development, this means embracing failure as a learning opportunity, staying curious, and always looking for ways to grow. Whether you’re facing a bug in your code or struggling with a new concept, remind yourself that learning is part of the process.

Free and Paid Resources to Learn Programming

There are countless resources to help you learn coding, whether you want to dip your toes in with free tutorials or invest in a more structured learning experience. Some popular options include:

Free Resources: Codecademy, freeCodeCamp, and YouTube tutorials.

Paid Courses: Udemy, Coursera, and coding bootcamps like General Assembly or Le Wagon.

Books: Titles like "Eloquent JavaScript," "Clean Code," and "Python Crash Course" are great for deeper learning.

Building Real-World Projects

The best way to learn coding is by doing. Start building small projects, like a personal blog or a simple game, to apply what you’ve learned. Over time, you can tackle more complex applications. These projects will not only boost your confidence but also serve as a portfolio when applying for jobs.

Essential Tools Every Aspiring Developer Should Know

To succeed as a software developer, you'll need to get familiar with a few essential tools. Mastering these will make your workflow smoother and more efficient.

Integrated Development Environments (IDEs)

An IDE is where you write your code. Some popular IDEs include Visual Studio Code, IntelliJ IDEA, and PyCharm. These environments come with features like syntax highlighting, debugging tools, and extensions that help speed up coding and reduce errors.

Version Control with Git and GitHub

Version control allows developers to manage changes in their code and collaborate with others without fear of losing work. Git is the most commonly used version control system, and GitHub is a platform where developers can host their repositories and collaborate on projects. Learning Git and GitHub is essential for working in teams or contributing to open-source projects.

Debugging Tools

No developer writes perfect code on the first try. Debugging is an essential part of the development process. Tools like Chrome DevTools, PyCharm's debugger, and Visual Studio Code’s debugging features will help you identify and fix errors in your code more efficiently.

Career Pathways in Software Development

Once you’ve honed your skills and feel confident in your development abilities, you’ll have various career paths to explore. Let’s take a quick look at some of the common roles within the industry.

Front-End Developer

Front-end developers focus on the user-facing parts of websites and applications. They use technologies like HTML, CSS, and JavaScript to build visually appealing and responsive designs that users interact with. If you love creating smooth, intuitive user experiences, front-end development might be the right path for you.

Back-End Developer

Back-end developers handle the server side of web applications. They work with databases, server logic, and APIs to ensure that everything runs smoothly behind the scenes. Common languages for back-end development include Python, Java, Ruby, and PHP.

Full-Stack Developer

A full-stack developer is skilled in both front-end and back-end development. This role requires a well-rounded knowledge of multiple programming languages, frameworks, and tools. Full-stack developers are often involved in the entire process of creating an application, from design to deployment.

How to Stay Motivated on Your Path to Becoming a Developer

Learning to code and becoming proficient can take time, and it's important to stay motivated throughout the journey. Here are a few tips to help you keep going, even when things get tough.

Setting Long-Term and Short-Term Goals

Break down your learning into smaller, achievable goals. Instead of aiming to "master JavaScript," focus on more tangible milestones, like building a specific feature or completing a course module. Celebrate these wins along the way to stay motivated.

Staying Engaged with the Developer Community

One of the best ways to stay motivated is to surround yourself with like-minded individuals. Join online forums like Stack Overflow, Reddit, or Discord groups where developers share knowledge and help each other out. Attending local or virtual meetups, hackathons, or developer conferences can also inspire you and help build a support network.

Conclusion

So, are you ready to be a software developer? After taking this quiz, you should have a clearer sense of whether you have the passion, mindset, and technical abilities needed to succeed in this fast-paced and rewarding field. Whether you scored highly or see areas for improvement, remember that software development is a journey. With the right resources, motivation, and a willingness to keep learning, you can definitely make it as a developer.

Take the time to develop your skills, build projects, and immerse yourself in the developer community. If you’re determined, you’ll find the path to becoming a software developer not only achievable but also incredibly fulfilling.

#software development #full stack developer #frontenddevelopment #backenddevelopment #python #reactjs #javascript

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iamnikoli · 1 year ago

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AY23/24 Sem 1 Module Reviews

This sem is probably the most difficult sem of my degree acads wise. Since I scored much better than expected in Year 1, I could afford to fully focus on core modules that would teach me useful skills related to my major. Hence, I decided to take 4 core modules, namely CS2040, DSA2101, DSA2102 and MA2311, along with GEN2061X. I did slightly underload to give myself more time for CS2040, which has a very high workload. I was also expecting a drop in GPA since most of the modules I took this sem weren't exactly easy or fluff. Nonetheless, I grew much closer to the friends I worked with in the different mods, and it made all the difference to my mental well-being as well as my academic performance.

CS2040

Module Coordinator & Lecturer: Dr Chong Ket Fah

T/A: Gary (tutorial), Chao Ming (lab), Sourabh (lab)

Lecture Topics/Schedule:

Week 1: Course Admin + Intro to Java, Analysis of Algorithms 1 Week 2: Analysis of Algorithms 2, Sorting 1 Week 3: Sorting 2, List ADT 1 (Array List, Linked List, Stack, Queue) Week 4: List ADT 2 Week 5: Map ADT (HashTable) Week 6: Priority Queue ADT (Binary Heap) Week 7: Disjoint Sets ADT (Union Find Disjoint Set), Ordered Map ADT 1 (Binary Search Tree/AVL Tree) Week 8: Ordered Map ADT 2, Graph Intro + Graph DS Week 9: Graph Traversal and Applications 1 Week 10: Graph Traversal and Applications 2, Minimum Spanning Tree Week 11: Single Source Shortest Path 1 Week 12: Single Source Shortest Path 2, All Pairs Shortest Path Week 13: Revision

Deliverables:

Tutorial attendance/participation - 3% Lab attendance - 2% One-Day Assignments (ODAs) - 1.5% x10 Take Home Assignments (THAs) 1.5% x8 qns, 2 qns per assignment Visualgo Quiz - 4% x2 Midterm - 20% Final Exam - 40%

Other Comments:

Although this module is hard (as you probably already know), I would say I enjoyed it for the most part. First of all, Dr Chong Ket Fah is an amazing lecturer, and he explains things very clearly. This made understanding the difficult concepts a lot easier. Dr Chong is also very nice and understanding towards students, for example, I fell sick one day before a one-day assignment and he extended my ODA deadline to the day after my MC ended which was basically one week later lol. These things might seem insignificant but they are highly appreciated by students (me at least).

There was a lot of content to cover in this module, and frankly, it can sometimes get overwhelming. On paper, there are 3 hours of lectures every week on Zoom exclusively, but Prof Chong often overruns to about 4-5 hours of lecture time a week. Not to worry, the lectures are recorded and you can watch them later. It is paramount that you keep up to pace with the lectures as it's not realistic to cram all of it in reading week, anyway you'll need the lecture content 1-2 weeks later to solve the ODAs and THAs. Also, we're expected to learn Java within the first 2 weeks, as prof does not teach java, he just gave us a learning package/crash course to do on our own. This is very important for students with no Java background like DSA students because we'll be expected to complete all our coding assignments in Java from end of week 2/week 3 onwards.

I attended the tutorial slot by Gary, and Gary is absolutely goated. He is very clear in explaining things, and often talks about potential extensions/modifications to the questions which may come up in the exams. This was very helpful in cultivating the sort of skills and thought process needed in the midterms/finals. Gary is also very chill and dedicated, we can message him on Telegram if we have any questions, and usually the night before the exams, he would stay up all night to answer questions that we had. Where are you gonna find such a dedicated TA HAHAHA please give this man a raise The only not-so-good thing about the tutorials is that the bulk of questions are pseudocode/coming up with algorithm questions, but the majority of questions in the exam are MCQ. I would've liked to see more of the latter in the tutorials as many of us felt unprepared for MCQ-style questions in the exams. From my understanding, the exams used to be a lot heavier in pseudocode questions, which might explain such an emphasis on such questions in the tutorial. If so, the tutorials might need a refresh.

Labs are essentially dedicated to solving ODA questions, and you can ask your lab TAs if you're stuck on either the ODAs or THAs. Apparently, they are also the ones that grade them. For me, I left my whole Friday empty in case I got stuck on an ODA and needed more time to solve it, since you have to complete in 24 hours. I also worked on the problem before my lab slot, like once the assignment opened at 10am. This was to ensure I made full use of my lab TAs expertise during the precious 2 hours if I got stuck, instead of trying to understand the question and come up with a first iteration to solve it. The ODAs in general were not terribly difficult though. As for the lab TAs, most of us preferred to talk to Chao Ming because he was more approachable and helpful. However, we often don't understand each other's algorithm suggestions HAHAHA. On the other hand, Sourabh was very passive. Maybe he was in charge of doing the assignment grading? But my friend asked him questions on telegram and got blue-ticked (I think more than once) so there's that. Oh also, you're required to submit pseudocode before or during the lab which also acts as your lab attendance grade, which is why you should start working on it before the lab because 2 hours to do pseudocode and actually code and debug is very tight.

THAs were more difficult, and I spent about 1-4 days on each question. There were 4 THAs in total, 2 questions in each THA. Discussing algorithms with friends really helps because a lot of these problems are not straightforward and require a good grasp of lecture content along with creativity. Unlike CS1010, your code now has to be efficient and meet the required run-time, otherwise it will not be accepted. Hence, talking to friends to see if there are other more efficient ways of solving the problem is highly efficient on your time needed to solve the THAs. Do note that looking at other people's code is not allowed, as mentioned by the prof so just be careful not to show actual code when discussing. The worst THA though probably has to be the AVL tree one, it was incredibly painful to have to build the AVL tree on your own and do all the rotations. Maybe deforestation isn't so bad after all Nonetheless, you should score full marks for both the ODAs and THAs as most people do after countless tries or discussing algorithms with friends.

Midterms and finals were pretty similar, exams were on Examplify and the bulk of it was MCQ questions, with 2-3 pseudocode/come-up-with-algorithm questions. The midterm tested until hashtables and was apparently harder than finals. As many of you know, Prof Chong sets hard papers so be prepared. Make sure you read the question properly as there's a lot of constraints/things to look out for to get the correct answer. Prof's questions also tend to be very long and confusing so it might take a lot of time and brain-power to understand what's going on in the question. Exams were open-book closed internet, the midterm was 1.5 hours and the final exam was 2 hours. You have to have a good grasp of the various algorithms, how they work, how their time complexities are derived and subsequently in what situations each algorithm works best/worst. I highly recommend working on the pseudocode questions at the end first because they need more time to think and come up with the solution, and if you don't know anything just write something out, and you'll get at least one mark. The MCQs can still be guessed if you run out of time, but try to do them well because they form the bulk of the marks. Do lots of PYPs to get a feel of the MCQ questions and see how the pseudocode questions should be answered. Also, for the pseudocode questions, I observed that writing in paragraphs/essay-style is much better than the usual code style because there's more ambiguity and it's easier for the marker to understand your algorithm's logic compared to code-style which will often be ridden with errors. For finals, prof actually dropped quite a few hints when he was going through the PYPs without answers in Week 13 lectures so do make sure to watch that. My score for the midterm was 58/100 (77th percentile), and the final exam was 75/95 (93rd percentile). Midterm stats 0 39 47 56 95, finals stats 0 41 50 62 91. Finals was originally out of 100, but there was an issue with the time complexity required and getting the correct answer (apparently the solution to solve it in that time complexity results in overcounting) in the last pseudocode questions, so prof re-based it to 5 instead of 10 marks and marked according to the next best algorithm to get the right answer.

Lastly, there were 2 Visualgo quizzes held during lab slots, one in Week 7 and the other in Week 13. Make sure to practise a lot of Visualgo questions in hard mode. I found the week 13 quiz much harder because the later topics were harder, especially MST. As a result, I got 14/15 for it because I got the 2nd best MST question wrong (so saddd). The first quiz was pretty easy though. Most people get full marks for both so.

All in all, I find this module difficult but also rewarding. A lot of the concepts taught are important, for example, I'm working on a project now that makes use of what I learnt in 2040. All the best to those taking it in future sems, rest assured Dr Chong is a very good prof and you're in good hands! Just put in the work and you should stay afloat

TLDR:

High workload, don't overload (in fact try to underload) when taking this mod Leave your Fridays empty to work on the ODAs Learn Java ahead of time if you can to get used to the syntax, don't leave THAs to the last minute because you need time. Discuss with friends to maximise efficiency on coding assignments Do PYPs and understand how each algo works, how the time complexity comes about, when to use what algo Do lots of Visualgo practice for the quizzes

Grades:

Expected grade: A- Actual grade: A

DSA2101

Module Coordinator & Lecturer: Dr Huang Yuting

T/A: Augustine

Lecture Topics:

R programming.

Importing data into R.

Data manipulation with R (Tidyverse)

Principles of data visualization.

Introduction to the grammar of graphics (ggplot2)

Exploring data through visualization.

Deliverables:

Tutorial Attendance - 5% DataCamp assignments - 10% Group project - 15% Midterm - 30% Finals - 40%

Other Comments:

This module has a pretty light workload, and the content is quite straightforward. It's a coding mod about data cleaning and visualisation using R. I thought I would be disadvantaged as I was pre-allocated DSA1101 in Sem 1 last year under Dr Sun, which had little coding emphasis and more stats/math, whereas in Sem 2 Dr Daisy Pham took over and revamped the whole module to essentially be about R coding. However, the first few weeks of lectures were about R coding and it was more than enough time to catch up. Also, it turns out that I'm quite quick at debugging in R, which is a great asset in exams. Dr Huang is a good lecturer in my opinion, she is concise and emphasises on the important things. Lectures are basically her going through slides which show various ways to code using a variety of tools/functions, and often she'll do a live demo to reinforce what was taught in the slides. She encourages us to code alongside her, and for this reason (apart from the fact that lectures are at 8am), I think it's better to watch the recorded lectures as you can pause and try them out yourself before continuing. Prof is also very approachable and quick to reply my emails, even if I ask a barrage of questions.

Tutorials are coding questions for you to try out on your own, and the TA will go through them. Augustine was a good TA, on top of the solutions provided by prof, he would add other methods to get the same result, and he was decent at explaining the code flow and thought process. He also responded to my queries on Telegram for the most part. As for the tutorial questions, I highly recommend trying them out on your own without using chatgpt to debug, because it's good practice for exams.

DataCamp Assignments were 8 x 1.25% online modules/courses? on DataCamp. These are free marks so just make sure you complete them by the deadline. DataCamp honestly isn't very helpful in learning because almost everything is filled in, and they just need you to fill in a few blanks.

The midterm was a 1.5-hour Examplify, open-book but closed internet exam, held in Week 8 at 8am (!!), and this was probably the most difficult part of the course. Most people weren't mentally awake at 8am, and the paper was quite difficult. It is easy to forget a certain function or have syntax errors, and R isn't the easiest language to debug in. It might be tempting to keep working on one part before moving on to the next because each sub-part leads to another, but the grading was very lenient in the sense that even if you miss out on a lot of things, you can still get the bulk of the marks. The key point is to try and complete everything and you should be above the median already. Since you don't have internet access, it is paramount that you do the tutorials as practice without the internet to prepare for the midterm. There were also a lot of small things that tripped people up, such as not being able to read the excel file in R when the excel file is open on your computer, ctrl-c ctrl-v being locked, the question paper on Examplify only taking half of the screen and couldn't be expanded etc. Overall it was a bad experience but luckily the grading was so kind. I got 27.5/30, the median was 21.25/30. Also do note that you have to copy your code from R into Examplify and differences between the R code submitted on Canvas and the Examplify code will be subjected to penalties. However, the Examplify exam does not auto-submit when time is up because there's 15 minutes after the exam to complete all the admin, so make sure your file can knit and all (basically the correct version of your R file) before you copy and paste into Examplify.

The group project was a report where we had to come out with 3 different plots using ggplot to investigate a meaningful question from one of the datasets given. We were allowed to choose our group members regardless of tutorial slot, so be sure to take this mod with friends!! My group did San Francisco Rentals, which a lot of people avoided because there were a lot of observations and variables/columns, but it turned out to be quite easy as we only had to select a few columns to work with. I had other friends who did the Lego dataset which seemed easy at first glance, but turned out to be a nightmare because you had to join a lot of different tables together to get the data you wanted. Unfortunately, I don't know why my group underperformed, I only got 12.5/15, and I assume a lot of people would get 13-15 out of 15 (stats were not released). Anyways just make sure you don't leave the project to the last minute because it can be quite tedious to code and have to write the report.

Finals were a lot easier than midterms. The format was Examplify open-book, closed-internet 2-hour exam, consisting of 25 marks of MCQ/fill-in-the-blank questions and 15 marks of coding. The coding this time around was much simpler, and possibly because we're more experienced by then. The MCQ questions were very easy, and if you were unsure of anything (eg. the definition of tidy data), you could just Ctrl-F. Hence, I recommend collating the lecture slides into one document to more efficiently Ctrl-F. This also helps for the coding questions, as there was 1 data-cleaning and 2 ggplot questions, and if you're unsure of which ggplot function to plot the graph, there's a summary on the lecture slides, alongside an example of the syntax to come up with the plot. Hence, I finished the exam with half an hour to spare and checked through my answers. I think the bell curve for this paper is quite steep because it was relatively easy. There was only one part that tripped some people up, which was removing NAs before or after performing pivot-longer. This will yield different results and affects 2 MCQ questions and the 5 mark coding question. Other than that, the exam is straightforward so be sure not to make careless mistakes.

TLDR:

Practise tutorials without ChatGPT Go through tutorial questions and answers, collate lecture slides into 1 document for easy ctrl-F-ing in the exams In the exams, aim to complete everything rather than perfect certain parts. Move on if you're stuck Don't be careless, read the questions carefully Work with trusted friends for the group project to minimise pain

Grades:

Expected grade: A- Actual grade: A

DSA2102

Module Coordinator & Lecturer: Dr Timothy Wertz

T/A: Tianyun

Lecture Topics:

Week 1: Introduction, Scientific Notation Week 2: Computer Arithmetic, Matrix Operations and Complexity Week 3: Systems of Linear Equations Week 4: Elimination with Pivoting, LU Factorization Week 5: Cholesky Factorization, Linear Least Squares Week 6: Gram-Schmidt Process, Reflections and Rotations Week 7: Singular Value Decomposition Week 8: Eigenvalue Problems Week 9: Power Iteration, QR Iteration Week 10: Singular Value Decomposition Revisited, Interpolation, Practical Interpolation Week 11: Orthogonal Polynomials Week 12: Numerical Integration Week 13: Error Formulas and Composite Quadrature, Other Integration Algorithms, Numerical Differentiation

Deliverables:

Homework - 5% x4 [lowest HW score can be substituted by lecture attendance grade] Midterm - 30% Finals - 50%

Other Comments:

This module is not difficult, but there's just a lot of content to remember. First of all, Dr Wertz is a pretty good lecturer, he is concise in explaining things and he splits his lectures into 3 categories: technical, conceptual, and enrichment. About 40% of the slides are enrichment which is nice to know but not required for the homework or exams. I would've liked to see a labelling of each slide under one of the 3 categories which would have made revising for exams a lot easier. Prof is also very helpful and answers questions at the end of the lecture. However, he also speaks very fast and tends to mumble/have run-off sentences so if your first language is not English, you might have a hard time understanding him.

There were 4 homeworks, each was out of 50. Like most math modules, the homework median is usually close to full marks, except for Homework 2 which had a killer counting operations of banded matrix question. As usual, discuss with friends to check your answers. The homework questions are mostly not tough, they are questions that are covered in lectures. Each homework also has an R coding question, but it's usually quite simple as prof has pseudocode in the slides, you just need to adapt them into actual code. If not, the tutorials also have an R question usually, refer to the tutorials for inspiration. Also, prof took lecture attendance, and while lectures are not compulsory (lectures are recorded too), it can replace your lowest homework grade, whichever is higher. I highly recommend getting the attendance grade as a safety net.

Tutorials were apparently hit-or-miss. My TA, Tianyun, was a pretty good TA and he explained relatively well. Sometimes, I didn't understand him but he was very approachable to me asking him questions after tutorial and he cleared all my doubts. He was also very dedicated, because there was one week that another TA took over him, and damn he kinda sucks because he doesn't explain well and totally skipped the R coding question, which I needed to solve a homework question. After asking the substitute TA about it, he just shrugged and said he doesn't provide R code. However, after I emailed Tianyun about it, he came up with his own R solution to the problem as prof hadn't sent him the solution yet. This sort of proactiveness is appreciated. As for the tutorial questions itself, it's mostly not hard and quite a good reflection of exam questions.

The midterm was a 80-minute pen-and-paper, scientific calculator exam, and we had to bring our own writing paper and scan our answers to upload ala homework-style within 10 minutes. The paper was relatively simple but computationally intensive, so avoid making careless mistakes. We were tested up to Week 6 content, and it was quite right-skewed. I got 41/50, the stats are 0 33 39 43 50. The final exam was a 2-hour pen-and-paper, scientific calculator exam that was out of 50. It was honestly even simpler than the midterm because it was less computationally-intensive, the first question was a bit odd, asking us to consider the number of operations to get the time complexity of some algorithms. The rest of the questions were standard, and mirrored questions from lecture examples, tutorials or the midterm/final practice papers that prof gave. Prof said he sets easier papers by not allowing us to bring cheatsheets in, and I think he kept to his word. The hard part comes in memorising the sheer number of algorithms and ways to solve the questions.

TLDR:

Keep up with tutorials so that you remember the algorithms more easily As usual, check homework answers with friends, attend lectures for safety net/grade boost in case you screw up a HW Try to understand the process of the algorithms to make life easier when studying for exams Don't make careless mistakes in exams

Grades:

Expected grade: B+ Actual grade: A

MA2311

Module Coordinator & Lecturer: Assoc Prof Leung Man Chun

T/A: Shixiao

Lecture Topics:

1. Sequences (Monotone convergence theorem, series, absolute and conditional convergence) 2. Tests of convergence (Power series and interval of convergence, Taylor’s series, differentiation and integration of power series) 3. Vectors in R2 and R3 (Dot product and cross product) 4. Functions of 2 or 3 Variables (Limits and continuity, partial derivatives, directional derivatives, gradients of functions, Taylor’s formula, maximum and minimum, second derivative test) 5. Vector-valued Functions of Several Variables (Chain rule, tangent planes and normal lines to surfaces in R3, Jacobians (change of volume/area element), Lagrange's multiplier method) 6. Multiple Integrals (Iterated integrals, change of order of integration, change of variable formula for multiple integrals)

Deliverables:

Midterms - 20% Finals - 80% (!!)

Other Comments:

Despite my grade for the mod, I can safely say this is the WORST mod I've taken in NUS so far. This prof really sucks, period. Although some math majors were warning ppl about him in the CHS group chat, I thought that since the module content was easy, even if the prof is bad it shouldn't be too big a problem. How wrong I was HAHA (but tbf, I heard Charmaine Sia who's teaching MA2104 isn't that great either and 2104 is tougher so it's not an easy choice). At this point, the module should be renamed to Techniques in Advanced Gambling because I felt like I was throwing a dart blindfolded and seeing what grade I would land. The 80% finals really made it feel like a lottery.

Let's start with the lectures. Someone else mentioned that the lecture slides were bad, and yes it's true. It's just emptiness all around, like very few words and some random diagrams and pictures. I can understand if the prof wants us to take notes, and that's why he left so many blanks. But the problem is that his lectures hardly refer to the slides. 99% of the time he's writing some stuff on paper and showing it to the lecture hall on the visualiser, so no one knows which part he's explaining, especially since he really cannot teach and explain things well to us. I think it's very hard to learn content from his lectures, but I do think there is some value in watching them which I will explain later. I managed to get my hands on the previous prof's lecture slides which helped me to keep up with the tutorials but I didn't watch the lectures from midterms until reading week, as a result, I didn't exactly master the later topics until reading week.

As for the tutorials, Shixiao was a pretty good TA because he would explain things in a way that made sense. He was also helpful despite a lot of dumb questions I asked at the end of each tutorial lol. He was probably the saving grace of this mod. However, the tutorial questions were directly ripped from last AY's MA2311 (this prof was the TA for the mod then) and the prof is so lazy that he didn't even remove the previous prof's name from the tutorial solution slides!! So this means no one really knows what kind of questions the prof will set since there's no reference or anything.

Midterms was a 1-hour pen-and-paper exam held in the lecture hall on Week 8, and it was open-book. Apparently, it was closed-internet but there was nothing to block internet access. Nonetheless, you have access to all your notes and I also downloaded Geogebra offline to check limits lol. We were tested until radius of convergence. 2 questions were directly from the tutorial but just slightly altered, the last question was slightly unorthodox but still doable. I got 19/20, and I think a lot of people did too. We only got back the midterms on the very last lecture in Week 13 so if you realised you screwed up there's honestly not much time to catch up. The average according to the prof was around 18/20.

Finals was your typical 2-hour, pen-and-paper, scientific calculator and 1 A4 double-sided cheatsheet math final exam. (Note: There was 1 part of question 1 that was voided and the paper was re-based to 95 instead of 100.) The fact that finals was 80% was extremely scary, and it was a sink-or-swim situation. I spent the bulk of reading week looking through the textbook and trying out questions from there (answers can be found online if you're resourceful enough), and alongside going through the prev AY's prof notes in more detail I got a better idea of the content. To be fair, most of the content was not difficult except for the part on volume multiple integration. Nonetheless, I still poured a lot of effort and time into this module because I couldn't risk the 80%. After understanding everything, I watched the prof's lectures to see if there was anything I missed out on and also to get some hints. He was emphasising one particular question at the end of the last week 13 lecture which I added wholesale into my cheatsheet, and lo and behold, it came out in the last question of the finals. As for the finals paper itself, I could do most of the questions, it was a relatively even spread across all the topics in both the first and second half but I wasn't sure if I got them correct because even the first question, which was a giveaway L-hopital limit question, I got wrong LOL. I think there were a few questions that felt a bit strange and unfamiliar, but if you know your concepts well it should not be an issue. Overall, some people felt it was easy and some felt it was difficult, which I attribute to whether you know the content and watched his lectures or not. Still though, 80% is crazyyyyyy

TLDR:

Listen to other ppl's advice, don't take this mod under this AY's prof unless you like gambling if you're taking it under him, I wish you all the very best

Grades:

Expected grade: idek Actual grade: A+

#nus #cs2040 #dsa2101 #dsa2102 #ma2311

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