Top 10 coding success stories on Quora

In the world of coding, not everyone can make it to the final ends. There are countless obstacles in the way, but don’t give up. In this article, we’ll take a look at 10 of the most inspiring coding success stories on Quora. These stories will show you that it is possible to achieve your coding goals, no matter where you are starting from.

So whether you’re a complete beginner or you’ve been coding for a while, read on for some inspiration! And who knows, maybe your story will be inspirational to others one day.

1. Nikos Kostagiolas, Undergraduate Research Assistant at NCSR Demokritos

The first story is from Nikos Kostagiolas, an  Undergraduate Research Assistant at NCSR Demokritos. He began his journey into machine learning by taking Andrew Ng’s MOOC on Coursera. This course gave him a solid foundation in the basics of machine learning.

To further his understanding of machine learning theory, Nikos read books such as “Pattern Recognition and Machine Learning” by Christopher Bishop and “Machine Learning” by Tom Mitchell. He also watched online courses on linear algebra, calculus, and statistics.

In addition to his theoretical studies, Nikos also worked on practical machine learning projects. He implemented a solution to a classification problem in Python using the scikit-learn library. He also explored neural networks and deep learning by taking Geoffrey Hinton’s MOOC on Coursera and reading Michael Nielsen’s online book on the topic.

Nikos’s journey into machine learning has helped him gain a solid understanding of the field, enhance his mathematical skills, and explore neural networks and deep learning. He is now a research assistant at a prestigious institution, and he is excited to continue learning and contributing to the field of machine learning.

2. Clem Wang

This is the story of Clem Wang, who had a special talent for noticing unusual things from a young age. He was curious and studied different subjects in college, finally getting a degree in biology. But he realized biology wasn’t for him and switched to computers, focusing on programming.

He got really good at reading complex code and finding problems. Later, he worked at Alta Vista (which got bought by Yahoo) and analyzed many different web pages. Unlike other programmers who tried to simplify things, he had a special ability to see small differences between pages. He started writing code to identify these differences.

His boss supported his unique ideas, and he became a “feature engineer,” working with machine learning experts. He surprised he with his creative ideas. He learned a lot about how machine learning works, especially with boosted trees. He also learned the importance of good features and realized that some machine learning algorithms have limitations.

He used hundreds of features and many training sets to improve his skills. He also took an online class on machine learning, which filled in some gaps in his knowledge. He learned about linear algebra, Python, and a tool called scikit-learn.

He followed the advice of Andrew Ng’s Coursera class on ML on Coursera. With his practical experience and self-guided learning, he became a self-taught machine learning practitioner, using his unique perspective and intuition to make a difference in the field.

Sairam Uppugundla, Founder and CEO, Codegnan IT Solutions OPC Pvt Ltd

Sairam Uppugundla, a self-taught programmer specializing in Machine Learning, shares valuable insights on learning the field online. He emphasizes personalization, practical application, and consistency as essential factors in achieving proficiency.

Sairam suggests starting with a solid foundation in Python, dedicating several months to grasp the language. He encourages learners to create projects and learn through trial and error, emphasizing the value of hands-on experience. Rather than relying solely on structured courses, he advises learners to curate his own learning path based on his interests.

While staying updated is crucial, Sairam emphasizes the importance of striking a balance between research and practical implementation. He urges learners to master foundational concepts before exploring new trends.

Consistency is key, and Sairam compares the learning process to a child acquiring language skills. He encourages learners to maintain a regular and dedicated approach to his studies.

Effective communication and seeking assistance are vital aspects of the learning journey. Sairam encourages learners to actively engage in discussions and collaborate with others to gain insights and solutions.

Lastly, Sairam advises learners to regularly assess his progress and make necessary adjustments. He acknowledges the vastness of the Machine Learning landscape and encourages learners to embrace the continuous learning journey while maintaining motivation.

In summary, Sairam Uppugundla’s advice highlights the significance of personalization, practical application, and consistency in learning Machine Learning online. By focusing on building a strong Python foundation, engaging in hands-on projects, curating personalized learning paths, balancing research with practical implementation, maintaining consistency, seeking assistance when needed, and regularly evaluating progress, learners can progress towards expertise in Machine Learning.

 Roman Trusov, Master’s in Information Technology & Data Science, Skolkovo Institute of Science and Technology

Roman Trusov started his story from an interview for a crash course on data mining. Despite having limited experience and feeling out of place among more experienced candidates, Roman’s passion for coding and statistical models made him confident. The interview went well, and he joined a program with lectures, coding solutions for Kaggle, and writing tech papers. During this time, Roman learned R and Python, experimented with different models like ensembles, Random Forests, and GBMs.

Roman’s interest grew, and he took on a data science internship at a startup, working closely with a knowledgeable mentor. He furthered his learning by reading books on machine learning and math-heavy literature. Siemens provided a brief but valuable experience, where Roman developed a wide range of skills in data science, machine learning, and development. Seeking more knowledge, he engaged in reading academic papers and attended lectures and discussions.

A remote job as an ML engineer allowed Roman to work on various projects, combining data science, ML engineering, and development tasks. He learned primarily through hands-on experience and exploring ideas from papers published by Google and Facebook teams. Writing a paper with a former mentor was a formative experience, teaching Roman the importance of structured work and pushing him towards research.

Participating in a hackathon organized by a new lab in Moscow brought Roman into a great team, emphasizing the importance of learning from people and building things together. The team excelled and won the competition, leading to interactions with influential individuals in the field. Eventually, Roman received an email from Facebook, inviting him to join FAIR (Facebook Artificial Intelligence Research), which provided an exponential growth of knowledge and capabilities.

Roman acknowledges that even after four years, there is still much to learn, but he embraces the continuous pursuit of knowledge. By focusing on interesting ideas and not worrying about trivial matters, he believes it is possible to do something valuable and useful in the field. Roman’s journey has just begun, and he looks forward to further growth and exploration.

Chomba Bupe, Independent Researcher & Entrepreneur

Chomba’s passion for robots and curiosity that started at a young age fueled a lifelong interest in disruptive technologies. His fascination with robots and automatic systems led to a promise to pursue these passions as he grew older. To satisfy his curiosity, Chomba created a Quora profile and engaged in continuous questioning and seeking answers.

While studying electronic engineering at the University of Zambia, Chomba encountered artificial neural networks (ANNs) through a digital signal processing ebook. This encounter reignited his passion, prompting him to explore ANNs and embark on a four-year journey to create his own computer vision system. Along the way, Chomba faced criticism and detractors but remained resilient.

Creating a Quora profile became a valuable learning experience for Chomba, as it allowed him to contribute ideas and validate his knowledge. The exposure to global brands like Google through Quora and the realization of the significance of deep learning motivated Chomba to dive deeper into the subject. He dedicated himselves to reading journals, consuming Quora answers, and watching YouTube videos to expand his knowledge.

Passion and curiosity served as driving forces for Chomba, fueling his pursuit of childhood dreams and desires. Currently, Chomba is developing a new robot operating system and incorporating his knowledge of machine learning as a learning module for these systems. Throughout his journey, Chomba honed his coding skills in C/C++, Java, C#, and Visual Basic, with an ongoing focus on learning Python for TensorFlow integration.

Chomba’s experiences taught him the importance of commitment, patience, confidence in learning abilities, and self-teaching in machine learning. He emphasize the significance of dedicating time to learning, having a clear purpose, completing side projects, and coding everything oneself for practical knowledge acquisition.

Additionally, Chomba’s aspiration to change the world drives him to develop systems and open-source him, recognizing that even a single successful product can make a significant impact. Despite not knowing exactly how to change the world, the potential impact serves as motivation to continue his journey.

Overall, Chomba Bupe’s path in machine learning is shaped by childhood imagination, curiosity, and a commitment to personal growth and making a positive difference.

Steven Ussery, over 30 years as a Silicon Valley software engineer

Steven Ussery is a great example of a late bloomer, when he switched his career to a software engineer at the age of 40.

Steven began his professional journey as a U.S. Navy sailor on a destroyer in the 1970s while also studying engineering. He later transitioned to become a registered professional civil engineer in Texas and California from 1979 to 1989, simultaneously working towards a Master’s degree in Computer Science through night school.

From 1990 to 2021, Steven embarked on a 30-year career as a software engineer in Silicon Valley, working for prominent companies such as Apple, Adobe, eBay, Microsoft, VMWare, Cisco, Logitech, and multiple startups. Notably, he spent around 17 years working at Apple as an employee or contractor.

Currently, at the age of 69, Steven is pursuing his fourth career as a full-time college student at Texas State University—San Marcos. He is working towards a Bachelor’s degree in Music Performance, specializing in Jazz guitar. Despite being the only 69-year-old freshman, Steven actively performs jazz guitar at gigs when not focusing on his studies.

Steven’s story exemplifies the belief that it is never too late to embark on new career paths and achieve success. His personal experiences, as well as the accomplishments of his late mother, serve as inspirations to embrace change and pursue passions at any stage of life. C’est la vie, indeed.

Taylor Beebe, Software Engineer at Microsoft

Another was another successful transformation from other field and overcoming challenges to pursue a successful career in software engineering.

Taylor begins by recounting his struggles in high school, where he achieved a low academic performance and had limited prospects. He enrolled in a junior college to study acting but eventually dropped out in 2011. At this point, Taylor faced issues such as being overweight and lacking social skills.

To break free from his circumstances, Taylor embarked on a solo hitchhiking journey across America, which provided him with newfound confidence and inspired him to lose weight. Motivated by his experiences, he decided to travel extensively by purchasing a one-way ticket to Portugal. Over 45 days, Taylor explored 16 countries on a budget, staying in hostels and enjoying street food.

Subsequently, Taylor enlisted in the Marine Corps as an infantryman and completed multiple deployments. During this time, he found his soulmate and eventually left the Marines at the age of 26. Taylor’s journey took an unexpected turn as he entered a reputable school, pursuing a degree in computer science. Despite his background as an acting major and college dropout, Taylor achieved a 3.7 GPA, with the majority of his courses focused on STEM subjects.

Now 27 years old, Taylor has secured a software engineering internship at Microsoft, specifically in his core operating systems group. Reflecting on the remarkable transformation of his life in just eight years, Taylor emphasizes that it is never too late to learn programming or make significant life changes.

Taylor’s story serves as an inspiring example of personal growth, resilience, and the potential for transformation regardless of past setbacks. He demonstrate that determination, perseverance, and seizing opportunities can lead to remarkable achievements.

Dries Ketels, Application Programmer at Geo-IT

Dries Ketels, the writer shares his journey of transitioning from a mechanical design engineer to a software developer and the positive experiences he have encountered along the way.

Dries Ketels begins his transitioning from a mechanical design engineer to a software developer by mentioning his background as a mechanical design engineer, having worked in the field for eight years. However, he decided to change his career path and pursue software development. With previous experience in programming using Visual Basic for automating tasks in 3D modeling software, Dries recognized his passion for using programming as a tool to simplify his work.

In May of the previous year, Dries started learning Java through an online platform, seeing it as a suitable language for a career in application development. After six months of dedicated learning, he began searching for a job, highlighting his engineering background as an additional asset. Despite initially targeting Java positions, he were offered a job as an application programmer in C# for Autocad software.

Dries embraced the opportunity and began studying C# while working full-time. He dedicated additional hours during the weekends to further his learning. The results of his efforts were well-received by his boss, and he express a genuine enthusiasm for the projects he is involved in.

Reflecting on his journey, Dries emphasizes the vast job market and abundant resources available for aspiring programmers. He encourage others to start studying, enjoy the learning process, and be amazed by the capabilities of software. Dries suggests that solving real-world problems through practical experience is a more efficient learning approach than solely relying on courses. He advise individuals to seek job opportunities as soon as possible, as it can accelerate his learning process.

Dries’ story exemplifies the possibilities of successfully transitioning into a new career through determination, motivation, and a willingness to learn. His positive experiences and advice highlight the potential for growth and fulfillment in the field of software development.

Mario Burgos, M.S from CTU ONLINE Graduated 2017

Mario was an inspiration for those who may feel its too late to embark on a new path, when he start pursuiting computer science at the age of 37.

Mario’s background was diverse, having worked in journalism, professional photography, and comedy writing. He had an unfinished degree in Philosophy and Literature and lacked proficiency in English. After leaving his home country, Mario attempted cabinet making in New York but had no success. It was during his job as a photo lab technician that he purchased a TI994A home computer by Texas Instruments, promoted by Bill Cosby.

With a desire to improve the speed of the video games he programmed in BASIC, Mario reached out to Texas Instruments and learned that using Assembly Language would greatly enhance performance. He purchased the Assembly Language Kit and despite initially struggling to understand the manual, he persevered, continued working with the computer, and started taking courses and reading extensively on the subject.

After 14 years, Mario became the director of software development in a prominent insurance company and worked for notable organizations like Dow Jones and BMW. Upon retirement, he pursued further education, obtaining a Bachelor’s Degree in Management Information Systems at the age of 68 and a master’s in science in Software Engineering at 72.

Now at the age of 73, Mario is retired but eagerly looks forward to starting new endeavors. He plan to become a woodworker and are in the process of setting up his own workshop. Additionally, he is writing a book about democracy and have other projects in mind. Through his experiences, Mario emphasizes that age should not hinder one’s pursuit of success. He reference the story of Noah from the Bible, who undertook a monumental project at the age of 600. Mario sees himselves at 73 as still being in the early stages of his journey, eager to continue exploring new ventures

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