Course Description
This course is designed to understand the core principles of quantum computing for curious minds with a technical or scientific background. Covering the fundamentals—like qubits, superposition, entanglement, and quantum gates—this course builds a strong conceptual foundation. Learners will explore how quantum algorithms differ from classical ones and understand real-world applications in cryptography, optimization, and machine learning.
Course Curriculum
-
1
From History to Modern-Day Computing
- Why Learn Quantum Computing The-Motivation
- Syllabus
- Essentials Terms in Quantum Computing
- History of Quantum Computing
- Quantum Computing vs Classical Computing
- Quantum Mechanics & Quantum Computing
- What Really is Quantum Computing?
- Applications of Quantum Computing
- Quiz
- Disclaimer
- Mathematical Foundations of Quantum Computing
-
2
Quantum Mechanics to Quantum Circuits
- Duality of Matter
- Introducing Quantum Bits Qubits
- BraKet-Notation
- Understanding BraKet Notation
- Visualizing Single Qubits The Bloch Sphere and Basis-States
- Super position and Interference
- Interferometer
- Entanglement
- Quiz
-
3
Core Concepts in Quantum Computing
- Logic gates Single-qubits
- Logic Gates - Bits to Qubits
- Logic gates Multi-qubits
- Circuit construction
- Hands-On: Quantum Computing Simulators
- Building Quantum Circuits: The Role of Logic Gates
- Shor's Algorithm
- Introductory Hands-on Notebook using IBM Qiskit
- Quantum Hardware
- More on Quantum Hardware
- Reading Material: Fundamentals of Quantum Mechanics
- Feynman's Vision
- Quiz
- Resources
Who Should Enroll?
-
Students and professionals with a background in computer science, physics, or mathematics
-
Software developers and engineers curious about next-gen computing
-
Tech enthusiasts exploring the frontier of quantum technologies
-
Researchers and analysts seeking foundational knowledge in quantum computing
Key Takeaways
-
Understand fundamental concepts such as qubits, superposition, and entanglement
-
Learn how quantum gates and circuits work in theory and simulation
-
Explore key quantum algorithms like Grover’s and Shor’s
-
Discover real-world applications of quantum computing in various domains
Course Instructor
Srinjoy Ganguly - PhD Researcher in Quantum Technologies @ UCL | Ex-Lead Quantum AI Scientist @ Fractal
Srinjoy Ganguly is a dynamic product leader with a strong background in engineering, analytics, and AI-driven innovation. With experience spanning organizations like Fractal and Mu Sigma, he has led impactful data and AI products across domains such as CPG, healthcare, and financial services. Srinjoy excels at blending technical expertise with strategic thinking to build scalable, user-centric solutions that drive business value.
Course Instructor
Shalini Devendrababu - Lead Quantum AI Researcher, Fractal
Shalini is a quantum AI researcher dedicated to exploring and advancing the frontiers of quantum algorithms, particularly in quantum chemistry and quantum machine learning. With a unique blend of academic rigor and corporate acumen, she is a passionate about leveraging the uncharted potentials of quantum technologies to solve complex problems.
FAQ
-
Is any programming required?
Basic familiarity with programming is helpful, but the course focuses more on concepts than coding.
-
What’s the difference between classical and quantum computing covered in the course?
The course explains this difference clearly, especially how quantum principles enable new computing capabilities.
-
What industries benefit from quantum computing?
The course highlights applications in cryptography, pharma, logistics, finance, and AI.
-
Will I get to work with real quantum systems?
You’ll interact with simulators and beginner-friendly platforms to model quantum circuits, such as IBM Q Experience.
-
Is a certificate provided?
Yes, you will receive a certificate upon successful completion of the course.