Genetic Algorithms Courses

International Centre for Theoretical Sciences

Multi-Agent Reinforcement Learning - Theory, Algorithms, and Future Directions - Lecture 2

Explore multi-agent reinforcement learning theory and algorithms with Eric Mazumdar in this advanced lecture covering theoretical foundations and future research directions.

• YouTube
• 1 hour 16 minutes
• Self-Paced
• Free Video

International Centre for Theoretical Sciences

Multi-Agent Reinforcement Learning - Theory, Algorithms, and Future Directions - Lecture 1

Explore multi-agent reinforcement learning fundamentals, covering theoretical foundations, algorithmic approaches, and emerging research directions in this comprehensive lecture.

• YouTube
• 1 hour 42 minutes
• Self-Paced
• Free Video

Milken Institute

Algorithms to Outcomes - AI's Impact in Finance

Explore how AI transforms finance through predictive analytics, machine learning models, and decision-making processes across asset management, private credit, and wealth management sectors.

• YouTube
• 58 minutes
• Self-Paced
• Free Video

Tech with Tim

How I Mastered Data Structures and Algorithms

Master data structures and algorithms efficiently with proven strategies, language selection tips, theory fundamentals, practice techniques, and mock interview preparation.

• YouTube
• 11 minutes
• Self-Paced
• Free Video

Squid: Schools for Quantum Information Development

Quantum Algorithms

Explore quantum algorithms with expert Ronald de Wolf in this comprehensive 2.5-hour lecture from the University of Zurich's summer school on quantum computing.

• YouTube
• 2 hours 36 minutes
• Self-Paced
• Free Video

BIMSA

Exploring Potential Transcription Factors and Their Regulatory Relationships Based on Asymmetric Covariance Natural Vector Encoding Method and Machine Learning Algorithms

Discover advanced machine learning algorithms and asymmetric covariance natural vector encoding methods for identifying transcription factors and their regulatory networks.

• YouTube
• 52 minutes
• Self-Paced
• Free Video

BIMSA

Structure-Preserving Algorithms for the Bethe-Salpeter Eigenvalue Problem

Discover structure-preserving algorithms for solving the Bethe-Salpeter eigenvalue problem in computational physics and quantum many-body theory.

• YouTube
• 1 hour
• Self-Paced
• Free Video

BIMSA

Algorithms for Sparse LPN and LSPN Against Low-noise

Explore advanced algorithms for solving Sparse Learning Parity with Noise and Learning Sparse Parity with Noise problems in low-noise cryptographic scenarios.

• YouTube
• 51 minutes
• Self-Paced
• Free Video

Qiskit

Practical Quantum Techniques - Variational Quantum Algorithms and Their Challenges

Explore variational quantum algorithms, their foundations, key challenges like barren plateaus, and recent research addressing scalability limitations in near-term quantum computing.

• YouTube
• 59 minutes
• Self-Paced
• Free Video

Qiskit

Practical Quantum Algorithms - From Problem Mapping to Hardware Execution

Explore quantum algorithm implementation from problem mapping to hardware execution, focusing on error mitigation techniques for extracting reliable results from noisy quantum devices.

• YouTube
• 58 minutes
• Self-Paced
• Free Video

CppNow

Extending std::execution - Implementing Custom Algorithms with Senders and Receivers

Discover how to extend std::execution by implementing custom algorithms using the Senders & Receivers model through practical when_all_range examples.

• YouTube
• 1 hour 18 minutes
• Self-Paced
• Free Video

TheIACR

Using Formally Verified Post-Quantum Algorithms at Scale

Discover how formally verified post-quantum algorithms are being implemented at scale, exploring real-world applications and deployment challenges in cryptographic systems.

• YouTube
• 20 minutes
• Self-Paced
• Free Video

DevConf

Implementing Post Quantum Algorithms in PKCS #11

Explore post-quantum cryptography implementation in PKCS #11, covering NIST's new algorithms, KEMs, and signature primitives to prepare for quantum computing threats.

• YouTube
• 27 minutes
• Self-Paced
• Free Video

INI Seminar Room 2

From Learning Differential Operators to Learning Algorithms

Discover how differential operators connect to machine learning algorithms in this advanced mathematical exploration by Professor Houman Owhadi from Caltech.

• YouTube
• 1 hour 39 minutes
• Self-Paced
• Free Video

Institute for Pure & Applied Mathematics (IPAM)

Scalable Algorithms for Bayesian Deep Learning via Stochastic Gradient Monte Carlo and Beyond

Discover advanced Monte Carlo methods for Bayesian deep learning, focusing on replica exchange SGMCMC algorithms that overcome scalability challenges in big data neural network training.

• YouTube
• 32 minutes
• Self-Paced
• Free Video