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Learn Optimism online: university courses, full YouTube courses, and courses with free certificates, from the IITs, MIT, Harvard, Google, Microsoft and more.
Harvard University
Learn to use machine learning in Python in this introductory course on artificial intelligence.
IIT Bombay
Computer Science and Engineering course by Prof. Mayank Baranwal.
Stanford Online
The primary topics in this part of the specialization are: greedy algorithms (scheduling, minimum spanning trees, clustering, Huffman codes) and dynamic programming (knapsack, sequence alignment, optimal search trees).
DeepLearning.AI
In the second course of the Deep Learning Specialization, you will open the deep learning black box to understand the processes that drive performance and generate good results systematically. By the end, you will learn the best practices to train and develop test sets and analyze bias/variance for…
IISc Bangalore
Computer Science and Engineering course by Prof. Sumit K. Mandal.
MIT OpenCourseWare
This course covers concepts of computation used in analysis of engineering systems. It includes the following topics: data structures, relational database representations of engineering data, algorithms for the solution and optimization of engineering system designs (greedy, dynamic programming, br…
Microsoft
Managing and optimizing AI agent investments on Azure is now more streamlined and powerful with the built-in observability capabilities in Microsoft Foundry. These tools provide enterprise-grade observability, governance, and performance optimization capabilities essential for deploying intelligent…
MIT OpenCourseWare
6.374 examines the device and circuit level optimization of digital building blocks. Topics covered include: MOS device models including Deep Sub-Micron effects; circuit design styles for logic, arithmetic and sequential blocks; estimation and minimization of energy consumption; interconnect models…
Microsoft
Choose this module if you want to optimize model training by tuning hyperparameters with sweep jobs in Azure Machine Learning.
Microsoft
Tune pgvector configuration, select vector indexes, design efficient data layouts, and scale Azure Database for PostgreSQL for high-performance AI workloads.
Microsoft
Diagnose and fix semantic model and report performance issues. Use Performance analyzer to identify bottlenecks, optimize DAX calculations, reduce cardinality, and implement aggregations to improve query speed.
MIT OpenCourseWare
This course is an introduction to linear optimization and its extensions emphasizing the underlying mathematical structures, geometrical ideas, algorithms and solutions of practical problems. The topics covered include: formulations, the geometry of linear optimization, duality theory, the simplex…
Microsoft
Microsoft Azure offers multiple services that enable developers to build amazing AI-powered solutions. Proper planning and preparation involves identifying the services you'll use and creating an optimal working environment for your development team.
Microsoft
Learn the essentials of Azure SQL Database deployment and migration. Explore its benefits, exclusive features, and migration options while optimizing performance and application connections for a smooth transition to the cloud.
MIT OpenCourseWare
This course relies on primary readings from the database community to introduce graduate students to the foundations of database systems, focusing on basics such as the relational algebra and data model, schema normalization, query optimization, and transactions. It is designed for students who hav…
Stanford University
This self-paced course will discuss the major ideas used today in the implementation of programming language compilers, including lexical analysis, parsing, syntax-directed translation, abstract syntax trees, types and type checking, intermediate languages, dataflow analysis, program optimization,…
Microsoft
Learn how to evaluate and optimize AI agents systematically through structured experiments that measure quality, cost, and performance. Design evaluation metrics, apply Git-based workflows, create consistent scoring rubrics, and make evidence-based optimization decisions.
Microsoft
Optimize multi-agent performance and cost in Microsoft Foundry. Design model routing strategies across agent ecosystems, implement multi-level caching architectures, optimize token usage and context management across agent chains, and systematically analyze quality-cost-latency trade-offs.
MIT OpenCourseWare
6.172 is an 18-unit class that provides a hands-on, project-based introduction to building scalable and high-performance software systems. Topics include performance analysis, algorithmic techniques for high performance, instruction-level optimizations, caching optimizations, parallel programming,…
00:00:00 - Introduction 00:00:15 - Optimization 00:01:20 - Local Search 00:07:24 - Hill Climbing 00:29:43 - Simulated Annealing 00:40:43 - Linear Programming 00:51:03 - Constraint Satisfaction 00:59:17 - Node Consistency 01:03:03 - Arc Consistency 01:16:53 - Backtracking Search This course explores…
