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Deep Learning courses 745

Learn Deep Learning online: university courses, full YouTube courses, and courses with free certificates, from the IITs, MIT, Harvard, Google, Microsoft and more.

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Alison

Introduction to Artificial Intelligence (AI)

3.4826 ratings

Embark on an exciting journey into the world of artificial intelligence (AI) with our comprehensive course from IBM experts that demystifies the technologies shaping our future. Learn what AI is, its fascinating history, and how concepts like machine learning, deep learning, and generative AI are t…

  • Alison
  • 5 hours
  • Self-paced
  • Free course
  • Paid certificate
  • Beginner

Alison

Machine Learning and Advanced AI Techniques

3.1147 ratings

Have you ever wondered how Amazon or Netflix knows exactly which product or show to recommend to you? The answer lies in the adoption of machine learning (ML) in business. In this course, we'll explore, through real-world examples, the various applications of machine learning and deep learning acro…

  • Alison
  • 3 hours
  • Self-paced
  • Free course
  • Paid certificate
  • Advanced

Northeastern University

Machine Learning for Engineers: Algorithms and Applications

This course covers practical algorithms and the theory for machine learning from a variety of perspectives. Topics include supervised learning (generative, discriminative learning, parametric, non-parametric learning, deep neural networks, support vector Machines), unsupervised learning (clustering…

  • Coursera
  • 2-5 hours/week
  • Self-paced
  • Paid certificate

Northeastern University

Generative AI Part 1

Introduces the theoretical foundations and advanced concepts of neural networks, generative models, transformers, and large language models. Students will explore how these AI systems create new data, process information, and learn through feedback, while analyzing their applications across various…

  • Coursera
  • 2-4 hours per week
  • Self-paced
  • Paid certificate

Northeastern University

Generative AI Part 2

Introduces the theoretical foundations and advanced concepts of neural networks, generative models, transformers, and large language models. Students will explore how these AI systems create new data, process information, and learn through feedback, while analyzing their applications across various…

  • Coursera
  • 2-4 hours per week
  • Self-paced
  • Paid certificate

Northeastern University

Statistical Learning for Engineering Part 1

This course covers practical algorithms and the theory for machine learning from a variety of perspectives. Topics include supervised learning (generative, discriminative learning, parametric, non-parametric learning, deep neural networks, support vector Machines), unsupervised learning (clustering…

  • Coursera
  • 7 weeks, 2-6 hours/week
  • Self-paced
  • Paid certificate

University of Glasgow

Capstone Assignment

This capstone course gives you the opportunity to bring everything you have learned in the Informed Clinical Decision Making using Deep Learning Specialization together in one hands-on, practical project. You will work with real-world critical care data from the MIMIC-III database and tackle a clin…

  • Coursera
  • 3 hours/week
  • Self-paced
  • Paid certificate

University of Glasgow

Deep Learning in Electronic Health Records

Overview of the main principles of Deep Learning along with common architectures. Formulate the problem for time-series classification and apply it to vital signals such as ECG. Applying this methods in Electronic Health Records is challenging due to the missing values and the heterogeneity in EHR,…

  • Coursera
  • 5-6 hours/week
  • Self-paced
  • Paid certificate

Northeastern University

Statistical Learning for Engineering Part 2

This course covers practical algorithms and the theory for machine learning from a variety of perspectives. Topics include supervised learning (generative, discriminative learning, parametric, non-parametric learning, deep neural networks, support vector Machines), unsupervised learning (clustering…

  • Coursera
  • 7 weeks, 2-6 hours/week
  • Self-paced
  • Paid certificate

University of the Arts London

Introduction to Creative AI

This course is an introduction to Creative AI, a growing field at the intersection of machine learning and artistic practice. During the course, you’ll learn how neural networks work, how they are trained, and how they can be applied. Exploring how artificial intelligence can be used as a transform…

  • Coursera
  • 5 hours
  • Self-paced
  • Paid certificate

Northeastern University

Generative AI: Foundations and Concepts

This course provides an overview of some different concepts underpinning Generative AI, their mathematical principles, and their applications in engineering. The focus will be on the practical implementation of generative AI including, neural networks, attention mechanism, and advanced deep learnin…

  • Coursera
  • 22 hours
  • Self-paced
  • Paid certificate

Northeastern University

Deep Learning for AI Part 1

This is Part 1 of a two-part graduate sequence in deep learning. It establishes the foundations of modern deep learning and the core neural architectures behind today's AI systems. You will build from how neural networks learn—through forward propagation and backpropagation—to convolutional network…

  • Coursera
  • 4-6 hrs / week
  • Self-paced
  • Paid certificate

Northeastern University

NLP in Engineering: Concepts & Real-World Applications

This course provides an overview of some different Natural Language Processing (NLP) techniques, their underlying principles, and their applications in engineering. The focus will be on the practical implementation of NLP methods such as word embeddings, neural networks, attention mechanisms, and a…

  • Coursera
  • 14 hours
  • Self-paced
  • Paid certificate

Northeastern University

Deep Learning for AI Part 2

This is Part 2 of a two-part graduate sequence in deep learning. Building on the foundations from Part 1, it focuses on advanced generative modeling. You will study autoregressive models, diffusion models, energy-based models, and normalizing flows; see how these techniques converge in multimodal t…

  • Coursera
  • 3-5 hours / week
  • Self-paced
  • Paid certificate

Universidades Anáhuac

Deep Learning

En este curso aprenderás que es una red neuronal, como crear una red neuronal, entrenar una red neuronal con un conjunto de imágenes.

  • edX
  • 4 weeks, 6 - 8 hours per week
  • Self-paced
  • Free to audit
  • Paid certificate
  • Advanced

Universidad del Rosario

Introducción a Machine Learning

4.05 ratings

Conoce los conceptos básicos del aprendizaje automático de máquinas, usando un acercamiento algebraico. Aborda problemas de regresión, clasificación y agrupamiento, desde modelos lineales hasta modelos no-lineales utilizando redes neuronales artificiales.

  • edX
  • Self-paced
  • Free to audit
  • Paid certificate
  • Beginner

Coursera

Mining Quality Prediction Using Machine & Deep Learning

4.870 ratings

In this 1.5-hour long project-based course, you will be able to: - Understand the theory and intuition behind Simple and Multiple Linear Regression. - Import Key python libraries, datasets and perform data visualization - Perform exploratory data analysis and standardize the training and testing da…

  • Coursera
  • 1.5 hours
  • Self-paced
  • Paid certificate

Google Cloud

Build, Train and Deploy ML Models with Keras on Google Cloud - Français

Ce cours porte sur la création de modèles de ML à l'aide de TensorFlow et Keras, l'amélioration de la précision des modèles de ML et l'écriture de modèles de ML pour une utilisation évolutive.

  • Coursera
  • 4 semaines d'étude, 8 à 10 heures/semaine
  • Self-paced
  • Paid certificate

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