Post-Quantum Security for AI: Resilient Digital Security in the Age of Artificial General Intelligence and Technological Singularity (Video Course)

Description

Futureproof your cybersecurity strategy with practical defenses against AGI and quantum computing threats.

As Artificial General Intelligence (AGI) and quantum computing rapidly reshape the digital landscape, todays security practices are no longer enough. This course demystifies both technologies in plain, accessible language and shows how they intersect to create new vulnerabilities--and new opportunities for protection. Through hands-on examples, real-world scenarios, and expert-led instruction, learners will discover how to build resilient, quantumsafe systems and safeguard digital identities, data, and infrastructure from emerging highimpact threats.

By taking this course you will:

• Understand how AGI and quantum computing change the cybersecurity threat landscape.
• Gain confidence implementing quantumresistant and AIresilient security strategies.
• Learn to protect sensitive data and digital identities against nextgeneration attacks.
• Apply real-world exercises to strengthen organizational security posture.

Skill Level:

• Intermediate

Learn How To:

• Identify and evaluate security risks introduced by AGI and quantum computing.
• Apply postquantum cryptographic techniques, including latticebased methods.
• Use blockchain, zeroknowledge proofs, and decentralized identity models for resilient protection.
• Develop strategies to defend systems from intelligent, adaptive AI-driven exploits.

Course Requirement:

A foundational understanding of cybersecurity principles or equivalent professional experience is recommended.

Who Should Take This Course:

Cybersecurity practitioners, cryptographers, IT and technology leaders, infrastructure security teams, academic researchers, and policymakers preparing to navigate the next era of digital risk--particularly those responsible for protecting sensitive data and setting long-term security strategies.

Sample Content

Table of Contents

Introduction

Module 1: Introduction to Technological Threats

Lesson 1: The Path to the Technological Singularity

Learning objectives

1.1 Historical background and conceptual foundations

1.2 Current research trajectories and indicators

1.3 Security implications of accelerated AI development

Lesson 2: Quantum Computing and the Security Horizon

Learning objectives

2.1 Fundamentals of quantum speed-up and cryptographic risks

2.2 Timelines and global quantum research roadmaps

2.3 Early warning signs for cryptographic obsolescence

Module 2: Digital Security by Design

Lesson 3: Strength and Fragility of Current Security Architectures

Learning objectives

3.1 Evaluation of digital security system efficacy

3.2 Systemic risks and domino-effect failures

3.3 Interconnected infrastructure vulnerabilities

Lesson 4: Artificial General Intelligence in Cybersecurity

Learning objectives

4.1 Potential for AI-enhanced defensive capabilities

4.2 Emerging risks of AGI-driven offensive operations

4.3 Balancing opportunity and existential risk

Module 3: Quantum-Resistant Cryptography

Lesson 5: Post-Quantum Cryptography and NIST Standards

Learning objectives

5.1 Why existing cryptography fails under quantum attack

5.2 Overview of NIST PQC standards (Kyber, Dilithium, Falcon, SPHINCS+)

5.3 Global adoption and compliance strategies

Lesson 6: Implementing Quantum-Safe Cryptographic Solutions

Learning objectives

6.1 Migration strategies and hybrid deployments

6.2 Performance and implementation considerations

6.3 Risk assessments, audits, and regulatory alignment

Module 4: Defending Against AGI Threats

Lesson 7: AI-Driven Defense and Threat Mitigation

Learning objectives

7.1 Reliability and limitations of AI-driven cybersecurity

7.2 Case studies of AI-enabled defense mechanisms

7.3 Future trends in automated security orchestration

Lesson 8: Protecting Digital Identity (after AGI)

Learning objectives

8.1 Quantum-safe digital identity frameworks

8.2 AI in decentralized identity and authentication

8.3 Reinforcement learning and AI agents for identity protection

Module 5: The Future of Digital Security

Lesson 9: Building Future-Proof Security Architectures

Learning objectives

9.1 Designing systems resilient to quantum attacks

9.2 Anticipating AGI-level adversarial strategies

9.3 Standards, policy, and governance readiness

Lesson 10: Preventing a Runaway Technological Singularity

Learning objectives

10.1 Ethical and existential risks of uncontrolled AGI

10.2 Proactive countermeasures and policy frameworks

10.3 Global coordination and long-term resilience

Summary

Updates

Submit Errata