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Pytorch Courses

PyTorch courses can help you learn neural network design, model training, and deep learning techniques. You can build skills in data preprocessing, hyperparameter tuning, and implementing convolutional and recurrent networks. Many courses introduce tools like TensorBoard for visualization and Jupyter Notebooks for interactive coding, showcasing how these skills are applied in projects involving image recognition, natural language processing, and other areas of artificial intelligence (AI).


Popular Pytorch Courses and Certifications


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    Pearson

    Programming Generative AI: Unit 1

    Skills you'll gain: Generative AI, PyTorch (Machine Learning Library), Generative Model Architectures, Multimodal Prompts, Artificial Neural Networks, Deep Learning, Large Language Modeling, Tensorflow, Convolutional Neural Networks

    Intermediate · Course · 1 - 4 Weeks

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    Pearson

    Programming Generative AI: Unit 2

    Skills you'll gain: Generative AI, Large Language Modeling, Generative Model Architectures, Image Analysis, Autoencoders, Hugging Face, Embeddings, Computer Vision, Convolutional Neural Networks, PyTorch (Machine Learning Library), LLM Application, Natural Language Processing

    Intermediate · Course · 1 - 4 Weeks

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    Imperial College London

    Probabilistic Deep Learning with TensorFlow 2

    Skills you'll gain: Tensorflow, Autoencoders, Generative Model Architectures, Deep Learning, Applied Machine Learning, Image Analysis, Bayesian Statistics, Probability Distribution, Unsupervised Learning, Sampling (Statistics)

    4.7
    Rating, 4.7 out of 5 stars
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    109 reviews

    Advanced · Course · 1 - 3 Months

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    Coursera

    Sentiment Analysis with Deep Learning using BERT

    Skills you'll gain: Model Evaluation, Data Preprocessing, PyTorch (Machine Learning Library), Transfer Learning, Model Deployment, Performance Tuning, Deep Learning, Natural Language Processing, Machine Learning

    4.4
    Rating, 4.4 out of 5 stars
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    398 reviews

    Intermediate · Guided Project · Less Than 2 Hours

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    Coursera

    Tweet Emotion Recognition with TensorFlow

    Skills you'll gain: Recurrent Neural Networks (RNNs), Tensorflow, Python Programming, Natural Language Processing, Data Preprocessing, Applied Machine Learning, Text Mining, Machine Learning Algorithms, Deep Learning, Classification Algorithms, Machine Learning

    4.5
    Rating, 4.5 out of 5 stars
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    174 reviews

    Intermediate · Guided Project · Less Than 2 Hours

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    DeepLearning.AI

    Natural Language Processing with Attention Models

    Skills you'll gain: Natural Language Processing, Transfer Learning, Recurrent Neural Networks (RNNs), PyTorch (Machine Learning Library), Applied Machine Learning, Keras (Neural Network Library), Embeddings, Model Evaluation

    4.4
    Rating, 4.4 out of 5 stars
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    1.1K reviews

    Intermediate · Course · 1 - 4 Weeks

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    DeepLearning.AI

    Build Basic Generative Adversarial Networks (GANs)

    Skills you'll gain: Generative Adversarial Networks (GANs), Generative Model Architectures, PyTorch (Machine Learning Library), Image Analysis, Deep Learning, Convolutional Neural Networks, Responsible AI, Artificial Neural Networks, Data Ethics, Unsupervised Learning

    4.7
    Rating, 4.7 out of 5 stars
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    2K reviews

    Intermediate · Course · 1 - 4 Weeks

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    Packt

    Advanced Machine Learning and Deep Learning

    Skills you'll gain: Autoencoders, Shiny (R Package), Deep Learning, Recurrent Neural Networks (RNNs), Transfer Learning, Convolutional Neural Networks, Image Analysis, PyTorch (Machine Learning Library), Artificial Neural Networks, Artificial Intelligence and Machine Learning (AI/ML), Applied Machine Learning, Tensorflow, Predictive Modeling, Dimensionality Reduction, Classification Algorithms, Time Series Analysis and Forecasting, Model Evaluation

    Advanced · Course · 1 - 3 Months

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    Packt

    RNN Architecture and Sentiment Classification

    Skills you'll gain: Recurrent Neural Networks (RNNs), PyTorch (Machine Learning Library), Text Mining, Artificial Neural Networks, Natural Language Processing, Classification Algorithms, Deep Learning, Applied Machine Learning, Network Architecture, Machine Learning

    Intermediate · Course · 1 - 4 Weeks

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    Databricks

    Introduction to Computational Statistics for Data Scientists

    Skills you'll gain: Bayesian Statistics, Databricks, Sampling (Statistics), Statistical Modeling, Probability, Applied Machine Learning, Jupyter, Regression Analysis, Statistical Programming, Predictive Modeling, Statistical Analysis, Model Evaluation, Probability Distribution, Data Science, Logistic Regression, Markov Model, Statistics, Statistical Methods, Simulations, Python Programming

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    Rating, 4 out of 5 stars
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    109 reviews

    Beginner · Specialization · 1 - 3 Months

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    Pearson

    Learning Deep Learning: Unit 3

    Skills you'll gain: Large Language Modeling, Prompt Engineering, Image Analysis, Model Deployment, PyTorch (Machine Learning Library), Deep Learning, Vision Transformer (ViT), Tensorflow, Convolutional Neural Networks, LLM Application, Transfer Learning, Computer Vision, Responsible AI, Generative AI, Multimodal Prompts, Artificial Neural Networks, Artificial Intelligence, Performance Tuning

    Intermediate · Course · 1 - 4 Weeks

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    Coursera

    Optimize TensorFlow Models For Deployment with TensorRT

    Skills you'll gain: Keras (Neural Network Library), Tensorflow, Applied Machine Learning, Deep Learning, Performance Tuning, Convolutional Neural Networks, Model Deployment, Python Programming

    4.5
    Rating, 4.5 out of 5 stars
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    76 reviews

    Intermediate · Guided Project · Less Than 2 Hours

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In summary, here are 10 of our most popular pytorch courses

  • Programming Generative AI: Unit 1: Pearson
  • Programming Generative AI: Unit 2: Pearson
  • Probabilistic Deep Learning with TensorFlow 2: Imperial College London
  • Sentiment Analysis with Deep Learning using BERT: Coursera
  • Tweet Emotion Recognition with TensorFlow: Coursera
  • Natural Language Processing with Attention Models: DeepLearning.AI
  • Build Basic Generative Adversarial Networks (GANs): DeepLearning.AI
  • Advanced Machine Learning and Deep Learning: Packt
  • RNN Architecture and Sentiment Classification: Packt
  • Introduction to Computational Statistics for Data Scientists: Databricks

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