Module
7
|
25
mins

Quantum Control to Quantum Intelligence: Error Correction, Computation and AI Synergy

ES Academy
Left Arrow
Right Arrow
ES Academy
DLT Tokenisation Course
Introduction to AI
Quantum Computing
Introduction to Hedera
Digital Identities
Foundations of Neural Networks and Deep Learning
Quantum Control to Quantum Intelligence: Error Correction, Computation and AI Synergy
Module
1
16
mins

DLT Tokenisation Course

START THE MODULE
Module
2
43
mins

Introduction to AI

START THE MODULE
Module
3
28
mins

Quantum Computing

START THE MODULE
Module
4
29
mins

Introduction to Hedera

START THE MODULE
Module
5
24
mins

Digital Identities

START THE MODULE
Module
6
40
mins

Foundations of Neural Networks and Deep Learning

START THE MODULE
Module
7
25
mins

Quantum Control to Quantum Intelligence: Error Correction, Computation and AI Synergy

START THE MODULE

Professor

Prof. Paolo Tasca

The module is taught by Prof. Paolo Tasca, digital economist, Co-founder and Executive Chairman of Exponential Science and experienced blockchain entrepreneur and advisor to global institutions, including the United Nations and central banks.

Professor

Prof. Nikhil Vadgama

This module is taught by Prof. Nikhil Vadgama, Programme Director of the MSc Financial Technology at UCL and Director of Exponential Science, with extensive experience in fintech and collaborating with governments, industry, and central banks worldwide.

What you’ll learn

1. Quantum noise and why qubits are fragile

2. No-Cloning Theorem and the measurement problem

3. Environmental vs intrinsic quantum noise

4. Decoherence, bit-flip and phase-flip errors

5. Principles of quantum error correction

6. Physical vs logical qubits and error-correction codes

7. Fault-tolerant quantum computing and surface code

8. Quantum hardware approaches and the NISQ era

9. Quantum optimisation, simulation, machine learning

10. Variational Quantum Circuits and quantum-AI interaction

Key takeaways:

  1. Quantum information cannot be copied or directly observed without disturbance
  2. Noise is fundamental in quantum systems, arising from the environment and qubit dynamics
  3. Decoherence causes qubits to lose quantum behaviour and revert towards classical states
  4. Quantum error correction protects information indirectly without measuring the quantum state
  5. Logical qubits are built from many physical qubits to achieve stability and fault tolerance
  6. Current quantum hardware is powerful but noisy, defining the NISQ era
  7. Near-term value lies in optimisation, simulation and hybrid quantum machine learning
  8. AI accelerates quantum progress, while quantum computing may reshape future AI workloads
Published:
12 Aug 2024
Created:
13 Aug 2025
Edited:
12 Aug 2024

Related materials

Interested in learning more from Exponential Science?
Aug 14
Quantum Cryptography: Securing Cryptographic Communication and Digital Security

Module 1

Tokenisation

Module 2

Introduction to AI

Module 3

Quantum Computing

Module 4

Introduction to Hedera

Module 5

Digital Identities

Module 6

Foundations of Neural Networks and Deep Learning
complete the course & get certified
Module
1
16
mins

DLT Tokenisation Course

START THE MODULE
Module
2
43
mins

Introduction to AI

START THE MODULE
Module
3
28
mins

Quantum Computing

START THE MODULE
Module
4
29
mins

Introduction to Hedera

START THE MODULE
Module
5
24
mins

Digital Identities

START THE MODULE
Module
6
40
mins

Foundations of Neural Networks and Deep Learning

START THE MODULE
Module
7
25
mins

Quantum Control to Quantum Intelligence: Error Correction, Computation and AI Synergy

START THE MODULE