Commit, Push, Repeat: How 100 Days Reshaped My Digital DNA

Introduction 👋

Hello! I’m Mohit Goyal, a sophomore, pursuing a Computer Science degree. I aim to gain knowledge of MERN stack and Machine Learning and land at least one internship before my pre-final year. This post chronicles my 100 Days of Code journey, where I committed to coding every day for 100 days straight. Whether you’re a fellow coder, a curious onlooker, or someone considering their coding challenge, I hope my experiences resonate with and inspire you.

The Beginning 🌱

On Day 1 of this journey, I sat at my desk, a mix of excitement and trepidation coursing through me. The prospect of coding every day for the next 100 days was thrilling and daunting. Armed with nothing but a laptop and an unwavering determination, I embarked on one of my life's most transformative experiences.

My aims?

1. Master the Data structures and Algorithms.
2. Learn about various Machine Learning Algorithms
3. Build a portfolio and a bunch of Projects
4. Attend Community Events and Engage with the Community
5. Get a Good Understanding of Web Technologies ( e.g. React)

The Journey at a Glance 🗺️

• Hours coded: 150+
• Languages/Technologies: JavaScript, React, Node.js, MongoDB, Python, Java
• Projects completed: 5+
• Event Attended: 6+
• Hackathon Participated: 3+

Top 5 Triumphs 🏆

1. Mastered Fundamental Data Structures and Algorithms
2. Designed and launched a personal portfolio website
3. Developed multiple full-stack projects
4. Contributed to open-source projects on GitHub
5. Gained a solid understanding of foundational Machine Learning algorithms

Projects Showcase 🛠️

Throughout my 100 Days of Code journey, I built several projects that helped me apply and reinforce my learning. Here are some highlights:

Paytm Simple Clone | Repo Link

• Technologies used: React, Node.js, MongoDB, ShadCn Ui
• Features: User authentication, CRUD operations, data persistence
• Learning outcome: Gained full-stack development experience

SmartiCalc | Repo Link

• Technologies used: React, TypeScript, Vercel, Git, ShadCn, Mantine, Google’s Gemini API
• Features: interpret and solve complex mathematical problem
• Learning outcome: Learned to work with APIs, TypeScript, and various UI libraries

TextractAI | Repo Link

• Technologies used: React.js, ShadCn UI library, Google’s Gemini API
• Features: PDF upload and text extraction, AI-powered text summarization, and Adjustable summary length (short, medium, long)
• Learning outcomes: Gained hands-on experience with React hooks and functional components, Learned to integrate and work with advanced AI APIs (Gemini) and Enhanced UI/UX design skills

SMS Spam Classifier | Repo Link

• Technologies used: Python, Jupiter NoteBook
• Features: Classify the given text as spam or not
• Learning outcomes: Learned about NLP for processing text data, implemented various machine learning algorithms

Each project presented unique challenges and learning opportunities, contributing significantly to my growth as a developer.

Biggest Challenges and Solutions 💪

1. Challenge: Grasping complex Data Structures and Algorithms concepts Solution: Created visual aids and implemented daily coding practice on platforms like LeetCode and GfG
2. Challenge: Staying consistent with coding daily, especially on busy or low-energy days. Solution: Created a minimal daily goal (e.g., 30 minutes of coding) and built a streak-tracking habit
3. Challenge: Managing the complexity of full-stack projects. Solution: Adopted Agile methodologies and broke projects into smaller, manageable tasks
4. Challenge: Balancing learning new concepts with building projects. Solution: I adopted a project-based learning approach, choosing projects that required me to learn and apply new skills.
5. Challenge: Understanding the math behind Machine Learning algorithms Solution: Revisited fundamental mathematics and statistics, utilizing online courses and visualizations.

Key Learnings 🧠

1. Consistency rules strength: Small daily efforts add to big improvements over time.
2. The power of community: Connecting with fellow coders accelerates learning and provides essential support.
3. Accept mistakes as learning opportunities: Debugging isn’t just about fixing code; It is an opportunity to deepen understanding.
4. How to study: Finding effective study methods is as important as the content.
5. Balancing breadth and depth of learning: Knowing when to dive deep and when to explore is the key to successful growth.
6. Don’t waste time planning: Dive in and start coding. Over-planning can be a form of procrastination.

Most Valuable Resources 📚

1. AtoZ DSA Sheet here.
2. “100 Days of Machine Learning” — By Campus X here.
3. “Chai aur React” — By Hitesh Chaudary here.
4. Machine Learning Specialization by Andrew Ng here.

The Impact on My Career 📈

This challenge has been a catalyst for my professional growth. I’ve gained technical skills, improved my problem-solving abilities, and learned to embrace continuous learning. I’m now actively interviewing for junior developer positions, with a portfolio that showcases my growth and dedication.

Advice for Future Participants 🗣️

1. Start with a plan, but be flexible
2. Progress Step by Step don’t try to jump ahead
3. Don’t compare your day 1 to someone else’s day 100
4. Prefer Consistency over quantity
5. Focus on one thing at a time

What’s Next? 🚀

1. Dive deeper into Typescript and Serverless architecture
2. Contribute more to open-source projects and participate as much as I can
3. Start writing blogs on my pre-existing projects and upcoming projects
4. Deep Dive into Machine Learning and Deep Learning

Final Thoughts 💭

These 100 days have been challenging, rewarding, and utterly transformative. I’ve learned that becoming a developer is not just about coding every day, but about embracing the journey of continuous learning and growth, to anyone considering this challenge: leap. Your future self will thank you.

Connect with Me 🌐

• Twitter: ByteMohit
• GitHub: MohitGoyal09
• LinkedIn: Mohit Goyal