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I am Shubham Dokania, Ex-Research Scientist at Mercedes-Benz R&D. My main area of work includes, but not limited to, deep learning for computer vision and artificial intelligence.
https://shubham1810.github.io
More than 3 years experience as Data Scientist including strong foundation with python,big data, hadoop, aws, natural language processing and visualization tools. More than 5 years experience as software engineer. Always ready for the next challenge.
I've done tons of work on systems and backend development. Highlights of my work:
- Automated bare-metal deployment and management of Linux and Solaris systems
- Built a cloud compute platform with a Flask API, Python services, RabbitMQ for messing, and MongoDB for persistence, powered by VMWare vSphere
- Managed thousands of systems with Salt and integrated Salt into said cloud platform
- Operated distributed applications on AWS
- Tested/built/deployed all of the above with CI/CD
Solid background in the Information and Communication Technology field; experience acquired with top market Italian and European players (Telco and Enterprise Market). Specific competence on deployment and placement of value added ICT services and security systems.
Specific technical knowledge in System Integration for OSS (Operational Support Systems); deep knowledge in System and Network infrastructure Design and Planning (for both Physical and Virtualized environments)
Consolidated many-years project management and consulting approach to the customers.
Product marketing and IT architectural design, technical and business development pre-sales
Bid management
Project management on mission critical tasks
Operational procedures
Infrastructure design and planning
Hardware and Software selection and comparison
Solid knowledge of TELCO/ISP environment
O.S.: Linux, RHEL, SUN Solaris, HP-UX, AIX, MP/RAS
HA/Clustering: Linux-HA, OpenAIS/Corosync, Pacemaker, RHCS, DRBD, SUN Cluster, HP MC/SG
Net/Sys MGMT: HP OpenView, IBM Tivoli Netcool, ARUBA Networks AMP (formerly AirWave MP), Cisco CUOM, Zoho ManageEngine Suite, Zenoss, OpenNMS, ZABBIX, Nagios, Bigbrother, Hobbit, Net-SNMP
Performance MGMT: CA Concord eHealth, Cisco Management Software, Cisco NetFlow, Cisco NBAR, MRTG, Cacti
SLA MGMT: Grandsla, CA Business Service Insight (formerly Oblicore Guarantee)
Networking/Security: Ciso IOS, Alteon OS and SLB, pfSense, FreeRADIUS, OpenVPN, IPTables, BSD PF, IPF
SAN: FC, NFS, iSCSI, Brocade SAN Switch, IBM System Storage, Nexsan
Server Virtualization: VMWare vSphere, ESX, ESXi, Parallels Virtuozzo, Oracle Solaris Containers
Desktop Virtualization: VMWare View, Citrix VDI-in-a-Box (formerly Kaviza), VirtualBridges VERDE, Virtualcomputer NxTop (now part of Citrix)
Specialties: Able to find and develop innovative and ingenious solutions
Able to find good alternatives to market leader products
Integration of heterogeneous products
Hello,
I have been working for the Research and Innovation division of a major IT company for 8 years now. Here is use Python, R and SQL to build Machine Learning-based solutions for analyzing scientific data and generate valuable actionable insights.
See the power of our Cluster Analysis tutors through glowing user reviews that showcase their successful Cluster Analysis learning journeys. Don't miss out on top-notch Cluster Analysis training.
“As always, my session with Isaac was excellent. He is so knowledgeable and straight to the point. We are coming to the end of our development of my first app, with his skills and experience, the app is looking great. I will definitely be continuing future work with him, developing my Power Platform skills.“
Faisal Khayer / Oct 2024
Isaac Eduardo Krauss Moreno
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“Amazing job. Had a complex installation to complete on a massive Angular application with many npm and other technical stuff to navigate and Opeoluwa was able to figure everything out and get my application running. I learned a lot and will continue to work with him.“
Jai Waterman / Nov 2024
Opeoluwa Lanre
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“Vijaya was so helpful! He helped me with a Power Automate flow that I had been stuck on for a couple of days, and helped me to get it working perfectly in a couple of hours. Very familiar with Power Automate, and very detail oriented / makes sure that everything is working before leaving you.“
Ali / Nov 2024
Vijaya Bhaskar
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“Amazing support, guidance and overal mentorship from Anup. A true expert with Power BI - I've learned so much in our call, and progress more than weeks worth of solo effort in a short span of time. I plan to reach out and ask for mentorship again for any and all Power BI troubeshooting.“
Amir Ali / Nov 2024
Anup Mistry
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Frequently asked questions
How to learn Cluster Analysis?
Learning Cluster Analysis 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 Cluster Analysis. 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 Cluster Analysis, 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 Cluster Analysis 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 Cluster Analysis through forums and online communities. This engagement offers support, new learning resources, and insights into industry practices.
Build real-world projects: Apply your Cluster Analysis skills to real-world projects. This could be anything from developing a simple app to contributing to open source projects. Using Cluster Analysis in practical applications not only boosts your learning but also builds your portfolio, which is crucial for career advancement.
Stay updated: Since Cluster Analysis 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 Cluster Analysis?
The time it takes to learn Cluster Analysis 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 Cluster Analysis 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 Cluster Analysis’s more advanced features and best practices.
Advanced level: Achieving proficiency or an advanced level of skill in Cluster Analysis generally requires at least 2 years of consistent practice and learning. This includes mastering sophisticated aspects of Cluster Analysis, contributing to major projects, and possibly specializing in specific areas within Cluster Analysis.
Continuous learning: Technology evolves rapidly, and ongoing learning is essential to maintain and improve your skills in Cluster Analysis. Engaging with new developments, tools, and methodologies in Cluster Analysis 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 Cluster Analysis tutor on Codementor?
The cost of finding a Cluster Analysis 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 Cluster Analysis 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 Cluster Analysis 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 Cluster Analysis with a dedicated tutor?
Learning Cluster Analysis 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 Cluster Analysis, 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 Cluster Analysis 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 Cluster Analysis 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 Cluster Analysis in a structured, supportive, and effective environment.
How does personalized Cluster Analysis mentoring differ from traditional classroom learning?
Personalized Cluster Analysis 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 Cluster Analysis.