1st lesson free
Sonny's profile and their contact details have been verified by our experts
Sonny
- Rate $17
- Response 1h
-
Students2
Number of students Sonny has accompanied since arriving at Superprof
Number of students Sonny has accompanied since arriving at Superprof
$17/hr
Contact
1st lesson free
- Physics
Quantum Reality - Full Stack AI enablement. GPU + Qubit + DWAVE -/+ IonQ π= Quantum Actuality
- Physics
Lesson location
Recommended
Sonny is a respected tutor in our community. He is highly recommended for his commitment and the quality of his lessons. An excellent choice to progress with confidence.
About Sonny
Target Audience and Prerequisites
Audience:
Software engineers, data scientists, researchers, or students exploring quantum advantage in hybrid settings.
Prerequisites: Basic linear algebra, probability, Python programming. Familiarity with classical ML or HPC is helpful but not required.
No prior quantum experience needed—foundational modules build it.
Course Duration and Format
Length:
5 Student Minimum
2 one hour lectures with 1 hour Q&A weekly
12 weeks (or self-paced equivalent), with 4-6 hours/week.
- Format: Lectures + hands-on labs (using simulators and real cloud access via IonQ, Rigetti, or open platforms), assignments, and a capstone hybrid project.
-Tools/Platforms: Qiskit, Cirq, PennyLane (for hybrid differentiable programming), pyQuil/Forest (Rigetti), Ocean (D-Wave), Azure Quantum or Amazon Braket for hybrid sessions, classical HPC elements (e.g., GPU integration).
See more
About the lesson
- Primary
- High School
- NCEA Level 1
- +5
levels :
Primary
High School
NCEA Level 1
NCEA Level 2
NCEA Level 3
Adult education
Masters
Doctorate
- English
All languages in which the lesson is available :
English
Course Objectives
By the end of the course, participants will be able to:
- Explain core quantum principles (superposition, entanglement, measurement) and their limitations in real hardware.
- Design, simulate, and execute hybrid quantum-classical algorithms (e.g., variational quantum algorithms, quantum machine learning).
- Navigate the full quantum-classical stack: hardware control, compilers, runtime, middleware, and application layers.
- Integrate quantum backends (cloud or simulators) with classical frameworks like PyTorch/TensorFlow for end-to-end workflows.
- Evaluate trade-offs in hybrid models for applications in optimization, chemistry, ML, and materials science.
- Discuss scalability challenges, error correction, and future fault-tolerant integration.
- Quantum control engineering
- Full Stack orchestration using Qiskit and Cirq frameworks
Quantum-Classical Entanglement:
Leveraging Full-Stack Hybrid Models".
This course bridges quantum and classical computing, focusing on hybrid systems where quantum processors (leveraging superposition, entanglement, and interference) collaborate tightly with classical hardware and software.
It emphasizes practical "full-stack" integration—from hardware to high-level applications—drawing on platforms from companies like IonQ (trapped-ion, first publicly traded pure-play quantum firm), Rigetti (superconducting), and D-Wave (annealing with hybrid solvers), alongside broader ecosystems like IBM Qiskit, PennyLane, and HPC-QC frameworks.
The course targets intermediate learners (e.g., computer science, physics, or engineering backgrounds) interested in NISQ-era (Noisy Intermediate-Scale Quantum) realities and near-term hybrid workflows.
It highlights how classical systems handle orchestration, error mitigation, optimization loops, and data preprocessing, while quantum components accelerate intractable subproblems via entanglement-enabled parallelism.
See more
Recommendations
Recommendations come from relatives, friends and acquaintances of the teacher
3
Worked with Sonny to tighten my understanding of storage and infrastructure as I prep for some of the newer large-scale data center environments coming online. He focuses on how systems actually behave under load—latency, bottlenecks, failure modes—not just surface-level concepts. That translated directly to how I evaluate and think through infrastructure decisions. Straightforward, technical, and useful. If you’re aiming at modern data center or AI-adjacent roles, he’s worth the time.
Sonny is among the best people i have ever met. A military trained genius with a heart of gold. Sonny is an ambitious go getter, with patience and compassion. I highly recommend my friend as a super tutor.
I met Sonny in 2026 on a chairlift at Beaver Creek Ski Resort in Colorado. When we realized that we attended the same church, we became fast friends.
Sonny is intelligent, high energy and always exudes a positive vibe. He is a loyal friend and adds value to the lives of those who know him.
View more recommendations
See more
Rates
Rate
- $17
Pack prices
- 5h: $85
- 10h: $170
online
- $17/h
free lessons
The first lesson with Sonny will allow you to get to know each other and discuss your needs for future lessons.
- 1hr
Similar Physics tutors in Austin
Aref
Auckland & online
- $80/h
- 1st lesson free
Kian
Auckland & online
- $79/h
- 1st lesson free
Kajana
Auckland & online
- $95/h
Eman
Auckland & online
- $60/h
- 1st lesson free
Patrick
Auckland & online
- $40/h
Luka
Auckland & online
- $60/h
Mr M P
Auckland & online
- $80/h
Panduka
Auckland & online
- $50/h
- 1st lesson free
Olivia
Paraparaumu & online
- $35/h
- 1st lesson free
Paul
Auckland & online
- $79/h
Anojit
Auckland & online
- $45/h
- 1st lesson free
Osama
Auckland & online
- $35/h
- 1st lesson free
Max
Dunedin & online
- $90/h
- 1st lesson free
Harshita
Auckland & online
- $40/h
- 1st lesson free
Tom
Tauranga & online
- $85/h
Wenya
Auckland & online
- $50/h
- 1st lesson free
Jiya
Auckland & online
- $35/h
- 1st lesson free
Drishya
Dunedin & online
- $200/h
- 1st lesson free
Sagar
Wellington & online
- $25/h
- 1st lesson free
Yosa
Auckland & online
- $75/h
-
See Physics tutors
