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WAHEGURU….!

IBM Quantum Course Application

My Passion for advanced technologies has grown tremendously from the day my father brought Pentium-3 Intel-based computer at home, I was 14 years old at that time. My curiosity had taken me to complete graduation in Information-Technology and working in the field of Software-Development since 2013. I have taken multiple courses in my graduation like Advanced Data Structures, Machine learning, Discrete Mathematics, Microprocessor and assembly language programming, Digital Circuits, and Logic Design.

My Github Profile Link: https://github.com/arshpreetsingh

Over the past years, I have worked in multiple roles in the Software industry and taught myself various Programming languages like Python, Julia, C, C++, Scala, and Go-Lang. I have industry-wide experience in Software development, Database-management, System-architecture, Data Operations, and Automated Tests. I always concentrate on using Open-Source technologies to cut down costs and making great use of Automation to decrease the cost across different areas.

I have contributed to Open Source Projects as well like TuxMath, TuxBlocks, Plyer, FreeCAD, and Open Street Mapping

Some of my featured Articles on Python, Julia, and Quantitative Finance has been published at medium.com as well.

[Python3 for Text Processing]
https://medium.com/@arshpreetsingh/python-for-text-processing-e8fa81802a71

[Guide to Julia Programming]
https://medium.com/@arshpreetsingh/julia-15da0fb911d6

[Hacker’s Guide to Quantitative Finance]
https://medium.com/@arshpreetsingh/hackers-guide-to-quantitative-trading-algorithmic-trading-part-1-ea479ab2e790

I am working in Finance-Industry and using Machine-learning, Statistics, Applied Mathematics to build financial models since 2017.
The finance industry is already using Pythsics and Applied Mathematics; few Examples are Bolinger Band, Black-Scholes-Merton model, Binomial Distributions, and Bayesian Statistics. Quantum Computing will be more efficient than classical computers to find patterns in data such will lead to the development of better Algorithms.

The detection of fraudulent activities using pattern recognization will be faster using Quantum computers in the financial world. Data will be more secure once encapsulated using quantum-cryptography techniques. One cannot read data encoded in quantum states because they shapeshift by changing states and as such prevent eavesdropping, Usage of quantum computers for “ML and AI models” could lead to more optimized models and will be able to improve the accuracy of the model. I have explored the Applications of Quantum-Technology in Portfolio-optimisation, Credit Risk Analysis, and Time-Series Analysis using Qiskit-Tutorials from Github using this link(https://github.com/Qiskit/qiskit-tutorials/tree/master/tutorials/finance). Apart from that, I have also completed Qiskit-Foundations on youtube taught by Abraham Asfaw.

Using Quantum Computer technology, I want to develop useful Algorithms for Arbitrage and Portfolio-Rebalance, Which I am considering as the first goal in the journey of learning Quantum Computers.

Looking forward to diving into the Quantum Realm and coming out with new forms of life.

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