Computational Complexity Courses and Certifications

UofU Data Science

Advanced Algorithms (Fall 2019)

Master sophisticated algorithmic techniques and computational problem-solving strategies through comprehensive university-level lectures covering advanced topics in algorithm design and analysis.

• YouTube
• 1 day 10 hours 46 minutes
• On-Demand
• Free Video

IAS | PCMI Park City Mathematics Institute

Quantum Computation - The 2023 IAS-PCMI Graduate Summer School

Dive into advanced quantum computing mathematics through expert-led minicourses covering quantum learning, error correction, complexity theory, and near-term quantum device analysis.

• YouTube
• 1 day 19 hours 46 minutes
• On-Demand
• Free Video

Institute for Pure & Applied Mathematics (IPAM)

Computational vs Statistical Gaps in Learning and Optimization

Explore computational vs statistical gaps in machine learning through expert talks on optimization, privacy, robustness, and algorithmic fairness challenges.

• YouTube
• 17 hours 9 minutes
• On-Demand
• Free Video

Complexity Explorer

Computation in Complex Systems

Explore computational complexity theory through algorithms, P vs NP problems, phase transitions, and universal computation models like Turing machines and cellular automata.

• YouTube
• 6 hours 46 minutes
• On-Demand
• Free Video

Introdução à Ciência da Computação com Python Parte 2

1570 ratings at Coursera

Aprofundamento em Python: matrizes, strings, POO, algoritmos de busca e ordenação, complexidade computacional e recursão. Desenvolvimento do raciocínio para resolução de problemas computacionais.

• Coursera
• 1 day 4 hours 48 minutes
• On-Demand
• Paid Course

International Centre for Theoretical Sciences

Why Do Simple Models Work? Partial Answers from Information Geometry - Lecture 1

Explores information geometry to understand why simple models effectively describe complex systems, focusing on statistical mechanics, renormalization, and model reduction in physics and biology.

• YouTube
• 1 hour 33 minutes
• On-Demand
• Free Video

International Centre for Theoretical Sciences

From Information Theory to Learning via Statistical Physics - Introduction

Explore connections between information theory, statistical physics, and learning. Delve into classical statistics, high-dimensional problems, and Bayesian approaches, with applications in signal processing and regression.

• YouTube
• 1 hour 33 minutes
• On-Demand
• Free Video

Joint Mathematics Meetings

Groups, Graphs and Algorithms

Explore the intersection of group theory, graph theory, and algorithms with László Babai, delving into topics like graph irregularity, canonical coloring, and string isomorphism.

• YouTube
• 50 minutes
• On-Demand
• Conference Talk

Yannic Kilcher

RWKV- Reinventing RNNs for the Transformer Era

Explore RWKV, a novel architecture combining Transformer and RNN strengths. Learn about its linear attention mechanism, scalability, and performance in NLP tasks.

• YouTube
• 1 hour 2 minutes
• On-Demand
• Free Video

IEEE

Understanding Deep Learning - Challenges for Statistical Learning Theory

Explore statistical learning theory challenges in deep learning, focusing on key concepts and recent developments in this complex field.

• YouTube
• 1 hour 28 minutes
• On-Demand
• Free Video

Neso Academy

Time Complexity of Loops - Solved Problem 5

Analyze time complexity of loops through a GATE 2013 problem. Master algorithm efficiency evaluation techniques for improved problem-solving skills.

• YouTube
• 18 minutes
• On-Demand
• Free Video

Neso Academy

Time Complexity of Loops - Solved Problem 6

Analyze time complexity of loops through a GATE 2023 problem, enhancing algorithm understanding and problem-solving skills for computer science students.

• YouTube
• 21 minutes
• On-Demand
• Free Video

IPhT-TV

Mathematical Problems in Machine Learning - Part 1 of 4

Explore mathematical foundations of machine learning with Andrea Montanari, focusing on key problems and theoretical concepts in the field.

• YouTube
• 1 hour 5 minutes
• On-Demand
• Free Video

USC Probability and Statistics Seminar

Are Neural Networks Optimal Approximation Algorithms for Constraint Satisfaction Problems?

Explore neural networks' capability to solve NP-hard optimization problems, focusing on constraint satisfaction and their potential as optimal approximation algorithms.

• YouTube
• 40 minutes
• On-Demand
• Free Video

Google TechTalks

Accelerating Transformers via Kernel Density Estimation - Google TechTalk

Explore efficient Transformer acceleration using kernel density estimation. Learn innovative techniques for handling long sequences and improving performance in deep learning models.

• YouTube
• 53 minutes
• On-Demand
• Free Video