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Working in the IT sector for more than 10 years.
With over 10 -years of freelancing and professional experience taught me all kinds of frameworks and languages, ranging from React, Angular, Vue, Node js, Express js, React Native, Redux, Rx JS, JavaScript, Typescript, WordPress, PHP, MySQL, MongoDB, Firebase, Sqlite, Postgresql, ES5+, Python3, Machine Learning, Deep Learning, RNN, CNN, Android Java/Kotlin, iOS Swift/SwiftUI, C/C#/C++, .Net, Assembly, VBA, VB, Excel Macro, Java, Spring Boot Micro-services, Zoho, Salesforce, Hubspot, R, Shiny, STATA, MATLAB, Google Sheet, App Script, Bubble io, etc.
Over my long career, I have come across all kinds of challenges and gained vast experience with different kinds of industries like portals, medical industry, perception exercise, employee management, etc.
I have good experience with frontend development using React JS along with Typescript, Firebase, GraphQL, React Native, Native Script, React, Material UI, Ionic, Node.js, Web Sockets, and real-time communication.
I have also worked on containerization technologies like Kubernetes, Docker, AWS, GCP, Azure etc.
I am very good with backend technologies as well like Java Spring boot, Microservices, MySQL, Postgres, Elasticsearch, AWS/Google integration.
Please contact me to get the result done in a professional way.
Hello everyone, I have been working in the CS industry for ~10 years. I have mainly been working on back-end and research oriented projects involving image processing. If you are looking for understanding how computers work at a deep level (as far as assembly), or want to know how big tech companies (such as Amazon) scale their projects, then I have knowledge to share with you!
Done a heck of a lot of programming and software design since I wrote my first on a Sinclair ZX spectrum in 1987. Not enough of it has been made open source. 2000+ five star ratings
I am a professional software developer with ~20 years of experience. I have developed software in various platforms from desktop, mobile to web. My current focus is in web development. My education background is in maths.
I am an experienced software developer/researcher with over 7 years of experience (3 years in academia and then 4 years in the industry). I have worked in a diverse set of companies ranging from early stage startups to big internet companies.
I believe I have a good knack of understanding a problem and coming up with a quick solution for it.
Sanyam Khurana, an Open Source contributor who predominantly goes by the moniker "CuriousLearner," achieved summa cum laude distinction upon obtaining a Master's degree in Computer Science from the Georgia Institute of Technology, specializing in Machine Learning and Interactive Intelligence. He is also an AWS certified Solutions Architect.
Sanyam has demonstrated an unwavering commitment to the Open Source community, having served as a GSoC mentor for Debian and an individual member of the Django Software Foundation (DSF). His GitHub profile (https://github.com/CuriousLearner/) is filled with evidence of his contributions to numerous upstream projects.
He has delivered presentations at a variety of international conferences, including PyCon Australia (https://www.youtube.com/watch?v=go7JklZRtrs) and DjangoCon US (https://www.youtube.com/watch?v=aiZ_1gsS4F8).
Sanyam's work has also been instrumental in maintaining and improving CPython, Python's interpreter, as a dedicated bug triager who actively contributes patches upstream.
He has also contributed various patches and bug reports upstream to Mozilla Organization's Gecko Engine, in addition to maintaining several upstream projects across different organizations.
As a vouched Mozillian, Sanyam has earned the distinction of being an official representative of Mozilla, and his contributions have been recognized in the AUTHORS and credits sections of every browser ever released by Mozilla. He served as a mentor for PyDSA during RGSoC 2017.
See the power of our Docker Machine tutors through glowing user reviews that showcase their successful Docker Machine learning journeys. Don't miss out on top-notch Docker Machine training.
“Great session with Anar. He was able to troubleshoot my Docker issues and teach me along the way. Very knowledgeable!“
Aria / Jan 2023
Anar Jafarov
Docker Machine tutor
“I have had sessions with others on this platform, but none were as good as Bilal. Not only knowledge but also his style of teaching. I have had help from two different professors and two other people on this platform, and no one was able to solve my issue. Bilal navigated to the correct solution in a calm, respectful manner. There is not enough praise I can give to him. I've never felt so satisfied with my service from this platform. A++“
Mark Loya / Jan 2025
Bilal Haider
Docker Machine tutor
“Dejan is a great mentor with a strong understanding of algorithms and coding interview preparation. In just one session, he provided clear explanations and helpful strategies that made complex topics easier to understand. His guidance gave me valuable insights into improving my problem-solving skills and preparing for technical challenges. I highly recommend him!“
Jenny Saunders / Jan 2025
Dejan B.
Docker Machine tutor
“Dejan systematically broke down what are the steps I need to take towards building a proper understanding of Data Structures and Algorithms so as to break into the Software Engineering industry in the US. He was very patient and kind with my doubts and is very passionate about coding. His personalized guidance has significantly helped me focus and save time towards cracking the coding interview. I look foraward to seeing him again.“
Varun Pillai / Jan 2025
Dejan B.
Docker Machine tutor
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Frequently asked questions
How to learn Docker Machine?
Learning Docker Machine effectively takes a structured approach, whether you're starting as a beginner or aiming to improve your existing skills. Here are key steps to guide you through the learning process:
Understand the basics: Start with the fundamentals of Docker Machine. You can find free courses and tutorials online that cater specifically to beginners. These resources make it easy for you to grasp the core concepts and basic syntax of Docker Machine, laying a solid foundation for further growth.
Practice regularly: Hands-on practice is crucial. Work on small projects or coding exercises that challenge you to apply what you've learned. This practical experience strengthens your knowledge and builds your coding skills.
Seek expert guidance: Connect with experienced Docker Machine tutors on Codementor for one-on-one mentorship. Our mentors offer personalized support, helping you troubleshoot problems, review your code, and navigate more complex topics as your skills develop.
Join online communities: Engage with other learners and professionals in Docker Machine through forums and online communities. This engagement offers support, new learning resources, and insights into industry practices.
Build real-world projects: Apply your Docker Machine skills to real-world projects. This could be anything from developing a simple app to contributing to open source projects. Using Docker Machine in practical applications not only boosts your learning but also builds your portfolio, which is crucial for career advancement.
Stay updated: Since Docker Machine is continually evolving, staying informed about the latest developments and advanced features is essential. Follow relevant blogs, subscribe to newsletters, and participate in workshops to keep your skills up-to-date and relevant.
How long does it take to learn Docker Machine?
The time it takes to learn Docker Machine depends greatly on several factors, including your prior experience, the complexity of the language or tech stack, and how much time you dedicate to learning. Here’s a general framework to help you set realistic expectations:
Beginner level: If you are starting from scratch, getting comfortable with the basics of Docker Machine typically takes about 3 to 6 months. During this period, you'll learn the fundamental concepts and begin applying them in simple projects.
Intermediate level: Advancing to an intermediate level can take an additional 6 to 12 months. At this stage, you should be working on more complex projects and deepening your understanding of Docker Machine’s more advanced features and best practices.
Advanced level: Achieving proficiency or an advanced level of skill in Docker Machine generally requires at least 2 years of consistent practice and learning. This includes mastering sophisticated aspects of Docker Machine, contributing to major projects, and possibly specializing in specific areas within Docker Machine.
Continuous learning: Technology evolves rapidly, and ongoing learning is essential to maintain and improve your skills in Docker Machine. Engaging with new developments, tools, and methodologies in Docker Machine is a continuous process throughout your career.
Setting personal learning goals and maintaining a regular learning schedule are crucial. Consider leveraging resources like Codementor to access personalized mentorship and expert guidance, which can accelerate your learning process and help you tackle specific challenges more efficiently.
How much does it cost to find a Docker Machine tutor on Codementor?
The cost of finding a Docker Machine tutor on Codementor depends on several factors, including the tutor's experience level, the complexity of the topic, and the length of the mentoring session. Here is a breakdown to help you understand the pricing structure:
Tutor experience: Tutors with extensive experience or high demand skills in Docker Machine typically charge higher rates. Conversely, emerging professionals might offer more affordable pricing.
Pro plans: Codementor also offers subscription plans that provide full access to all mentors and include features like automated mentor matching, which can be a cost-effective option for regular, ongoing support.
Project-based pricing: If you have a specific project, mentors may offer a flat rate for the complete task instead of an hourly charge. This range can vary widely depending on the project's scope and complexity.
To find the best rate, browse through our Docker Machine tutors’ profiles on Codementor, where you can view their rates and read reviews from other learners. This will help you choose a tutor who fits your budget and learning needs.
What are the benefits of learning Docker Machine with a dedicated tutor?
Learning Docker Machine with a dedicated tutor from Codementor offers several significant benefits that can accelerate your understanding and proficiency:
Personalized learning: A dedicated tutor adapts the learning experience to your specific needs, skills, and goals. This personalization ensures that you are not just learning Docker Machine, but exceling in a way that directly aligns with your objectives.
Immediate feedback and assistance: Unlike self-paced online courses, a dedicated tutor provides instant feedback on your code, concepts, and practices. This immediate response helps eliminate misunderstandings and sharpens your skills in real-time, making the learning process more efficient.
Motivation and accountability: Regular sessions with a tutor keep you motivated and accountable. Learning Docker Machine can be challenging, and having a dedicated mentor ensures you stay on track and continue making progress towards your learning goals.
Access to expert insights: Dedicated tutors often bring years of experience and industry knowledge. They can provide insights into best practices, current trends, and professional advice that are invaluable for both learning and career development.
Career guidance: Tutors can also offer guidance on how to apply Docker Machine in professional settings, assist in building a relevant portfolio, and advise on career opportunities, which is particularly beneficial if you plan to transition into a new role or industry.
By leveraging these benefits, you can significantly improve your competency in Docker Machine in a structured, supportive, and effective environment.
How does personalized Docker Machine mentoring differ from traditional classroom learning?
Personalized Docker Machine mentoring through Codementor offers a unique and effective learning approach compared to traditional classroom learning, particularly in these key aspects:
Customized content: Personalized mentoring adapts the learning material and pace specifically to your needs and skill level. This means the sessions can focus on areas where you need the most help or interest, unlike classroom settings which follow a fixed curriculum for all students.
One-on-one attention: With personalized mentoring, you receive the undivided attention of the tutor. This allows for immediate feedback and detailed explanations, ensuring that no questions are left unanswered, and concepts are fully understood.
Flexible scheduling: Personalized mentoring is arranged around your schedule, providing the flexibility to learn at times that are most convenient for you. This is often not possible in traditional classroom settings, which operate on a fixed schedule.
Pace of learning: In personalized mentoring, the pace can be adjusted according to how quickly or slowly you grasp new concepts. This custom pacing can significantly enhance the learning experience, as opposed to a classroom environment where the pace is set and may not align with every student’s learning speed.
Practical, hands-on learning: Mentors can provide more practical, hands-on learning experiences tailored to real-world applications. This direct application of skills is often more limited in classroom settings due to the general nature of the curriculum and the number of students involved.
Personalized mentoring thus provides a more tailored, flexible, and intensive learning experience, making it ideal for those who seek a focused and practical approach to mastering Docker Machine.