Algorithmes

Les cours Algorithmes développent vos capacités à articuler des processus pour résoudre des problèmes et à mettre en œuvre ces processus de façon efficace au moyen de logiciels. Vous apprendrez à concevoir des algorithmes pour la recherche, le tri et l'optimisation, et vous les utiliserez pour répondre à des questions pratiques.

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Deep Learning

Deep Learning

deeplearning.ai
Spécialisation
Noté 4.8 sur cinq étoiles.
Natural Language Processing

Natural Language Processing

deeplearning.ai
Spécialisation
Noté 4.6 sur cinq étoiles.
Algorithms

Algorithms

Stanford University
Spécialisation
Noté 4.8 sur cinq étoiles.
AI Foundations for Everyone

AI Foundations for Everyone

IBM
Spécialisation
Noté 4.7 sur cinq étoiles.
Reinforcement Learning

Reinforcement Learning

University of Alberta
Spécialisation
Noté 4.7 sur cinq étoiles.
Accelerated Computer Science Fundamentals

Accelerated Computer Science Fundamentals

University of Illinois at Urbana-Champaign
Spécialisation
Noté 4.7 sur cinq étoiles.
Data Structures and Algorithms

Data Structures and Algorithms

University of California San Diego
Spécialisation
Noté 4.6 sur cinq étoiles.
Introduction to Discrete Mathematics for Computer Science

Introduction to Discrete Mathematics for Computer Science

National Research University Higher School of Economics
Spécialisation
Noté 4.5 sur cinq étoiles.
Excel/VBA for Creative Problem Solving

Excel/VBA for Creative Problem Solving

University of Colorado Boulder
Spécialisation
Noté 4.9 sur cinq étoiles.
Introduction to Programming in C

Introduction to Programming in C

Duke University
Spécialisation
Noté 4.5 sur cinq étoiles.
Bioinformatics

Bioinformatics

University of California San Diego
Spécialisation
Noté 4.5 sur cinq étoiles.
Coding for Everyone: C and C++

Coding for Everyone: C and C++

University of California, Santa Cruz
Spécialisation
Noté 4.5 sur cinq étoiles.
Algorithms for Battery Management Systems

Algorithms for Battery Management Systems

University of Colorado System
Spécialisation
Noté 4.8 sur cinq étoiles.
Probabilistic Graphical Models

Probabilistic Graphical Models

Stanford University
Spécialisation
Noté 4.6 sur cinq étoiles.
Fundamentals of Computing

Fundamentals of Computing

Rice University
Spécialisation
Noté 4.8 sur cinq étoiles.
Machine Learning and Reinforcement Learning in Finance

Machine Learning and Reinforcement Learning in Finance

New York University
Spécialisation
Noté 3.7 sur cinq étoiles.

    Questions fréquentes sur Algorithmes

  • An algorithm is a step-by-step process used to solve a problem or reach a desired goal. It's a simple concept; you use your own algorithms for everyday tasks like deciding whether to drive or take the subway to work, or determining what you need from the grocery store. Software programs are an example of much more powerful algorithms, with computing resources used to execute multiple complex algorithms in parallel to solve much higher-level problems.

    As computers become more and more powerful, algorithms are helping them take on a life of their own - literally! Machine learning techniques rely on algorithms that learn and improve over time without need for a programmer's guidance. These techniques can be used to train algorithms for relatively simple tasks like image recognition or the automation and optimization of business workflows. And at their most complex, these algorithms are at the core of building the deep learning and artificial intelligence capabilities that many experts expect will transform our world even more than the advent of the internet!