Optimization Problems Courses and Certifications

Dynamic Programming

Explore dynamic programming techniques for solving complex algorithmic problems efficiently, including coin change, knapsack, and longest common subsequence.

• YouTube
• 3 hours 30 minutes
• On-Demand
• Free Video

Great Learning

Linear Programming for Data Science - Data Science Tutorial

This video explains Linear Progression for Data Science with a variety of demonstrations & examples to help you learn this topic effectively and efficiently.

• YouTube
• 2 hours 30 minutes
• On-Demand
• Free Video

How to Master Calculus

Master essential Calculus 1 concepts: derivatives, integrals, optimization, and more. Comprehensive explanations and examples for each topic, with practice problems to reinforce understanding.

• YouTube
• 1 hour 30 minutes
• On-Demand
• Free Video

Paul Hand

Theory of GANs for Compressed Sensing

Explore the theory of GAN priors in compressed sensing, covering key concepts, proofs, and optimization problems. Gain insights into visual representation and set restricted eigen value conditions.

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

IEEE

Adversarial Bandits with Knapsacks

Explore dynamic pricing and bandits with knapsacks in adversarial settings, covering algorithms, challenges, and future research directions in this field.

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

IEEE

Low-Degree Hardness of Random Optimization Problems

Explore the challenges of random optimization problems, focusing on low-degree hardness and its implications for various mathematical models and algorithms.

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

IEEE

Sum-of-Squares Lower Bounds for Sherrington-Kirkpatrick via Planted Affine Planes

Explore optimization techniques for Sherrington-Kirkpatrick problems using sum-of-squares lower bounds and planted affine planes, with insights on certification and hierarchies.

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

Krista King

AP Calculus AB and BC - Analytical Applications of Differentiation

Comprehensive review of analytical applications of differentiation, covering key theorems, extrema analysis, graphing techniques, and optimization problems for AP Calculus AB/BC preparation.

• YouTube
• 1 hour 22 minutes
• On-Demand
• Free Video

Calculus I

Comprehensive introduction to calculus, covering limits, derivatives, integrals, and applications. Develop problem-solving skills and gain a solid foundation in mathematical concepts essential for advanced studies.

• YouTube
• 11 hours
• On-Demand
• Free Video

Ryan O'Donnell

Approximation Algorithms

Explore approximation algorithms for NP-hard problems, focusing on vertex cover, k-coverage, and traveling salesperson. Learn greedy approaches and their limitations, as well as more advanced techniques.

• YouTube
• 1 hour 14 minutes
• On-Demand
• Free Video

Ryan O'Donnell

Great Ideas in Theoretical Computer Science - Approximation Algorithms

Explore approximation algorithms for NP-hard problems, focusing on Vertex Cover, k-Coverage, and Traveling Salesperson. Learn techniques to find near-optimal solutions efficiently.

• YouTube
• 1 hour 20 minutes
• On-Demand
• Free Video

Association for Computing Machinery (ACM)

An Improved Approximation Algorithm for ATSP

Explore an advanced approximation algorithm for the Asymmetric Traveling Salesman Problem, covering linear programming relaxation, reductions, and recursive techniques to improve solution quality.

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

USENIX

Heterogeneity-Aware Cluster Scheduling Policies for Deep Learning Workloads

Explores heterogeneity-aware scheduling for deep learning workloads, introducing Gavel to optimize resource allocation in clusters with diverse accelerators, improving efficiency and performance.

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

Pascal Poupart

Inverse RL

Explore inverse reinforcement learning, its applications, and key concepts like feature matching and maximizing margins. Learn implementation techniques and policy induction.

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

Pascal Poupart

Partially Observable RL

Explore partially observable reinforcement learning, covering Markov decision processes, hidden Markov models, and belief monitoring in this comprehensive lecture.

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