Search – talk-data.com

Title & Speakers	Event
Fundamentals of Deep Learning: NVIDIA DLI Certification Workshop for Academia 2025-10-25 · 08:30 https://www.nvidia.com/en-eu/training/instructor-led-workshops/fundamentals-of-deep-learning/ Deep Learning with PyTorch Workshop In this workshop, you’ll learn how deep learning works through hands-on exercises in computer vision and natural language processing. You’ll train deep learning models from scratch, learning tools and tricks to achieve highly accurate results. You’ll also learn to leverage freely available, state-of-the-art pre-trained models to save time and get your deep learning application up and running quickly. Learning Objectives By participating in this workshop, you’ll: Learn the fundamental techniques and tools required to train a deep learning model Gain experience with common deep learning data types and model architectures Enhance datasets through data augmentation to improve model accuracy Leverage transfer learning between models to achieve efficient results with less data and computation Build confidence to take on your own project with a modern deep learning framework Download workshop datasheet (PDF, 318 KB) Preparation for the Workshop Fill in the form at https://forms.gle/8iNZN3PToUh6iveC9 to gain access codes to the event (will be emailed shortly before it) Install Google Chrome or Mozilla Firefox to use the NVIDIA DLI Environment Create an account at https://learn.nvidia.com/ Mechanics of Deep Learning Explore the fundamental mechanics and tools involved in successfully training deep neural networks: Train your first computer vision model to learn the process of training Introduce convolutional neural networks to improve accuracy of predictions in vision applications Apply data augmentation to enhance a dataset and improve model generalization Pre-trained Models Leverage pre-trained models to solve deep learning challenges quickly. Train recurrent neural networks on sequential data: Integrate a pre-trained image classification model to create an automatic doggy door Leverage transfer learning to create a personalized doggy door that only lets in your dog Assessment Challenge: Image Classification Apply computer vision to create a model that distinguishes between fresh and rotten fruit: Create and train a model that interprets color images Build a data generator to make the most out of small datasets Improve training speed by combining transfer learning and feature extraction Discuss advanced neural network architectures and recent areas of research where students can further improve their skills Final Review Review key learnings and answer questions Complete the assessment and earn a certificate Complete the workshop survey Learn how to set up your own AI application development environment	Fundamentals of Deep Learning: NVIDIA DLI Certification Workshop for Academia
Fundamentals of Deep Learning: NVIDIA DLI Certification Workshop for Academia 2025-10-18 · 08:30 https://www.nvidia.com/en-eu/training/instructor-led-workshops/fundamentals-of-deep-learning/ Deep Learning with PyTorch Workshop In this workshop, you’ll learn how deep learning works through hands-on exercises in computer vision and natural language processing. You’ll train deep learning models from scratch, learning tools and tricks to achieve highly accurate results. You’ll also learn to leverage freely available, state-of-the-art pre-trained models to save time and get your deep learning application up and running quickly. Learning Objectives By participating in this workshop, you’ll: Learn the fundamental techniques and tools required to train a deep learning model Gain experience with common deep learning data types and model architectures Enhance datasets through data augmentation to improve model accuracy Leverage transfer learning between models to achieve efficient results with less data and computation Build confidence to take on your own project with a modern deep learning framework Download workshop datasheet (PDF, 318 KB) Preparation for the Workshop Fill in the form at https://forms.gle/8iNZN3PToUh6iveC9 to gain access codes to the event (will be emailed shortly before it) Install Google Chrome or Mozilla Firefox to use the NVIDIA DLI Environment Create an account at https://learn.nvidia.com/ Mechanics of Deep Learning Explore the fundamental mechanics and tools involved in successfully training deep neural networks: Train your first computer vision model to learn the process of training Introduce convolutional neural networks to improve accuracy of predictions in vision applications Apply data augmentation to enhance a dataset and improve model generalization Pre-trained Models Leverage pre-trained models to solve deep learning challenges quickly. Train recurrent neural networks on sequential data: Integrate a pre-trained image classification model to create an automatic doggy door Leverage transfer learning to create a personalized doggy door that only lets in your dog Assessment Challenge: Image Classification Apply computer vision to create a model that distinguishes between fresh and rotten fruit: Create and train a model that interprets color images Build a data generator to make the most out of small datasets Improve training speed by combining transfer learning and feature extraction Discuss advanced neural network architectures and recent areas of research where students can further improve their skills Final Review Review key learnings and answer questions Complete the assessment and earn a certificate Complete the workshop survey Learn how to set up your own AI application development environment	Fundamentals of Deep Learning: NVIDIA DLI Certification Workshop for Academia
April 5-6: FREE 2-Day Deep Learning Fundamentals NVIDIA DLI Certification Course 2025-04-05 · 08:00 Register for the FREE 2 day training course. Deep Learning Fundamentals with PyTorch and FiftyOne NVIDIA DLI Certification Workshop for Academia April 5-6\, 2025 \\| 10 AM – 5 PM CET About the Workshop Note: This course is only available to university students, researchers and teaching staff. A valid university email address is required to obtain a certificate. This two day workshop is an extension of NVIDIA’s DLI Deep Learning Fundamentals Course. Learn to implement neural networks for image classification from scratch using PyTorch. Learn about stochastic gradient descent, multilayer perceptrons, convolutional neural networks, and transformers. We will explore data augmentation, workflow management, and dataset curation using FiftyOne, a powerful open source tool for image dataset curation. On the first day we will focus on building and training neural networks with PyTorch. On the second day we will focus on visual dataset curation with FiftyOne and iterative improvement of image classification models. Instructor Antonio Rueda-Toicen, an AI Engineer in Berlin, has extensive experience in deploying machine learning models and has taught over 300 professionals. He is currently a Research Scientist at the Hasso Plattner Institute. Antonio is a certified instructor of deep learning and diffusion models at NVIDIA’s Deep Learning Institute. Prerequisites Programming Prerequisites: Python fundamentals Mathematics Prerequisites: Statistics and probability, linear algebra, calculus Technologies Used in the Workshop Python Jupyter PyTorch Pandas FiftyOne Google Colab Github Codespaces Assessment Type Skills-based coding assessments evaluate students’ ability to train a deep learning model to classify images with high accuracy. Certificate Upon successful completion of the coding assessment, participants will receive an NVIDIA DLI certificate to recognize their subject matter competency and support professional career growth. Hardware Requirements Desktop or laptop computer capable of running the latest version of Chrome or Firefox. Each participant will be provided with dedicated access to a fully configured, GPU-accelerated server in the cloud. Language English	April 5-6: FREE 2-Day Deep Learning Fundamentals NVIDIA DLI Certification Course
April 5-6: FREE 2-Day Deep Learning Fundamentals NVIDIA DLI Certification Course 2025-04-05 · 08:00 Register for the FREE 2 day training course. Deep Learning Fundamentals with PyTorch and FiftyOne NVIDIA DLI Certification Workshop for Academia April 5-6\, 2025 \\| 10 AM – 5 PM CET About the Workshop Note: This course is only available to university students, researchers and teaching staff. A valid university email address is required to obtain a certificate. This two day workshop is an extension of NVIDIA’s DLI Deep Learning Fundamentals Course. Learn to implement neural networks for image classification from scratch using PyTorch. Learn about stochastic gradient descent, multilayer perceptrons, convolutional neural networks, and transformers. We will explore data augmentation, workflow management, and dataset curation using FiftyOne, a powerful open source tool for image dataset curation. On the first day we will focus on building and training neural networks with PyTorch. On the second day we will focus on visual dataset curation with FiftyOne and iterative improvement of image classification models. Instructor Antonio Rueda-Toicen, an AI Engineer in Berlin, has extensive experience in deploying machine learning models and has taught over 300 professionals. He is currently a Research Scientist at the Hasso Plattner Institute. Antonio is a certified instructor of deep learning and diffusion models at NVIDIA’s Deep Learning Institute. Prerequisites Programming Prerequisites: Python fundamentals Mathematics Prerequisites: Statistics and probability, linear algebra, calculus Technologies Used in the Workshop Python Jupyter PyTorch Pandas FiftyOne Google Colab Github Codespaces Assessment Type Skills-based coding assessments evaluate students’ ability to train a deep learning model to classify images with high accuracy. Certificate Upon successful completion of the coding assessment, participants will receive an NVIDIA DLI certificate to recognize their subject matter competency and support professional career growth. Hardware Requirements Desktop or laptop computer capable of running the latest version of Chrome or Firefox. Each participant will be provided with dedicated access to a fully configured, GPU-accelerated server in the cloud. Language English	April 5-6: FREE 2-Day Deep Learning Fundamentals NVIDIA DLI Certification Course
April 5-6: FREE 2-Day Deep Learning Fundamentals NVIDIA DLI Certification Course 2025-04-05 · 08:00 Register for the FREE 2 day training course. Deep Learning Fundamentals with PyTorch and FiftyOne NVIDIA DLI Certification Workshop for Academia April 5-6\, 2025 \\| 10 AM – 5 PM CET About the Workshop Note: This course is only available to university students, researchers and teaching staff. A valid university email address is required to obtain a certificate. This two day workshop is an extension of NVIDIA’s DLI Deep Learning Fundamentals Course. Learn to implement neural networks for image classification from scratch using PyTorch. Learn about stochastic gradient descent, multilayer perceptrons, convolutional neural networks, and transformers. We will explore data augmentation, workflow management, and dataset curation using FiftyOne, a powerful open source tool for image dataset curation. On the first day we will focus on building and training neural networks with PyTorch. On the second day we will focus on visual dataset curation with FiftyOne and iterative improvement of image classification models. Instructor Antonio Rueda-Toicen, an AI Engineer in Berlin, has extensive experience in deploying machine learning models and has taught over 300 professionals. He is currently a Research Scientist at the Hasso Plattner Institute. Antonio is a certified instructor of deep learning and diffusion models at NVIDIA’s Deep Learning Institute. Prerequisites Programming Prerequisites: Python fundamentals Mathematics Prerequisites: Statistics and probability, linear algebra, calculus Technologies Used in the Workshop Python Jupyter PyTorch Pandas FiftyOne Google Colab Github Codespaces Assessment Type Skills-based coding assessments evaluate students’ ability to train a deep learning model to classify images with high accuracy. Certificate Upon successful completion of the coding assessment, participants will receive an NVIDIA DLI certificate to recognize their subject matter competency and support professional career growth. Hardware Requirements Desktop or laptop computer capable of running the latest version of Chrome or Firefox. Each participant will be provided with dedicated access to a fully configured, GPU-accelerated server in the cloud. Language English	April 5-6: FREE 2-Day Deep Learning Fundamentals NVIDIA DLI Certification Course
April 5-6: FREE 2-Day Deep Learning Fundamentals NVIDIA DLI Certification Course 2025-04-05 · 08:00 Register for the FREE 2 day training course. Deep Learning Fundamentals with PyTorch and FiftyOne NVIDIA DLI Certification Workshop for Academia April 5-6\, 2025 \\| 10 AM – 5 PM CET About the Workshop Note: This course is only available to university students, researchers and teaching staff. A valid university email address is required to obtain a certificate. This two day workshop is an extension of NVIDIA’s DLI Deep Learning Fundamentals Course. Learn to implement neural networks for image classification from scratch using PyTorch. Learn about stochastic gradient descent, multilayer perceptrons, convolutional neural networks, and transformers. We will explore data augmentation, workflow management, and dataset curation using FiftyOne, a powerful open source tool for image dataset curation. On the first day we will focus on building and training neural networks with PyTorch. On the second day we will focus on visual dataset curation with FiftyOne and iterative improvement of image classification models. Instructor Antonio Rueda-Toicen, an AI Engineer in Berlin, has extensive experience in deploying machine learning models and has taught over 300 professionals. He is currently a Research Scientist at the Hasso Plattner Institute. Antonio is a certified instructor of deep learning and diffusion models at NVIDIA’s Deep Learning Institute. Prerequisites Programming Prerequisites: Python fundamentals Mathematics Prerequisites: Statistics and probability, linear algebra, calculus Technologies Used in the Workshop Python Jupyter PyTorch Pandas FiftyOne Google Colab Github Codespaces Assessment Type Skills-based coding assessments evaluate students’ ability to train a deep learning model to classify images with high accuracy. Certificate Upon successful completion of the coding assessment, participants will receive an NVIDIA DLI certificate to recognize their subject matter competency and support professional career growth. Hardware Requirements Desktop or laptop computer capable of running the latest version of Chrome or Firefox. Each participant will be provided with dedicated access to a fully configured, GPU-accelerated server in the cloud. Language English	April 5-6: FREE 2-Day Deep Learning Fundamentals NVIDIA DLI Certification Course

Fundamentals of Deep Learning: NVIDIA DLI Certification Workshop for Academia 2025-10-25 · 08:30

https://www.nvidia.com/en-eu/training/instructor-led-workshops/fundamentals-of-deep-learning/

Deep Learning with PyTorch Workshop

In this workshop, you’ll learn how deep learning works through hands-on exercises in computer vision and natural language processing. You’ll train deep learning models from scratch, learning tools and tricks to achieve highly accurate results. You’ll also learn to leverage freely available, state-of-the-art pre-trained models to save time and get your deep learning application up and running quickly.

Learning Objectives

By participating in this workshop, you’ll:

Learn the fundamental techniques and tools required to train a deep learning model
Gain experience with common deep learning data types and model architectures
Enhance datasets through data augmentation to improve model accuracy
Leverage transfer learning between models to achieve efficient results with less data and computation
Build confidence to take on your own project with a modern deep learning framework

Download workshop datasheet (PDF, 318 KB)

Preparation for the Workshop

Fill in the form at https://forms.gle/8iNZN3PToUh6iveC9 to gain access codes to the event (will be emailed shortly before it)
Install Google Chrome or Mozilla Firefox to use the NVIDIA DLI Environment
Create an account at https://learn.nvidia.com/

Mechanics of Deep Learning Explore the fundamental mechanics and tools involved in successfully training deep neural networks:

Train your first computer vision model to learn the process of training
Introduce convolutional neural networks to improve accuracy of predictions in vision applications
Apply data augmentation to enhance a dataset and improve model generalization

Pre-trained Models Leverage pre-trained models to solve deep learning challenges quickly. Train recurrent neural networks on sequential data:

Integrate a pre-trained image classification model to create an automatic doggy door
Leverage transfer learning to create a personalized doggy door that only lets in your dog

Assessment Challenge: Image Classification Apply computer vision to create a model that distinguishes between fresh and rotten fruit:

Create and train a model that interprets color images
Build a data generator to make the most out of small datasets
Improve training speed by combining transfer learning and feature extraction
Discuss advanced neural network architectures and recent areas of research where students can further improve their skills

Final Review

Review key learnings and answer questions
Complete the assessment and earn a certificate
Complete the workshop survey
Learn how to set up your own AI application development environment

Fundamentals of Deep Learning: NVIDIA DLI Certification Workshop for Academia

Fundamentals of Deep Learning: NVIDIA DLI Certification Workshop for Academia 2025-10-18 · 08:30

https://www.nvidia.com/en-eu/training/instructor-led-workshops/fundamentals-of-deep-learning/

Deep Learning with PyTorch Workshop

In this workshop, you’ll learn how deep learning works through hands-on exercises in computer vision and natural language processing. You’ll train deep learning models from scratch, learning tools and tricks to achieve highly accurate results. You’ll also learn to leverage freely available, state-of-the-art pre-trained models to save time and get your deep learning application up and running quickly.

Learning Objectives

By participating in this workshop, you’ll:

Learn the fundamental techniques and tools required to train a deep learning model
Gain experience with common deep learning data types and model architectures
Enhance datasets through data augmentation to improve model accuracy
Leverage transfer learning between models to achieve efficient results with less data and computation
Build confidence to take on your own project with a modern deep learning framework

Download workshop datasheet (PDF, 318 KB)

Preparation for the Workshop

Fill in the form at https://forms.gle/8iNZN3PToUh6iveC9 to gain access codes to the event (will be emailed shortly before it)
Install Google Chrome or Mozilla Firefox to use the NVIDIA DLI Environment
Create an account at https://learn.nvidia.com/

Mechanics of Deep Learning Explore the fundamental mechanics and tools involved in successfully training deep neural networks:

Train your first computer vision model to learn the process of training
Introduce convolutional neural networks to improve accuracy of predictions in vision applications
Apply data augmentation to enhance a dataset and improve model generalization

Pre-trained Models Leverage pre-trained models to solve deep learning challenges quickly. Train recurrent neural networks on sequential data:

Integrate a pre-trained image classification model to create an automatic doggy door
Leverage transfer learning to create a personalized doggy door that only lets in your dog

Assessment Challenge: Image Classification Apply computer vision to create a model that distinguishes between fresh and rotten fruit:

Create and train a model that interprets color images
Build a data generator to make the most out of small datasets
Improve training speed by combining transfer learning and feature extraction
Discuss advanced neural network architectures and recent areas of research where students can further improve their skills

Final Review

Review key learnings and answer questions
Complete the assessment and earn a certificate
Complete the workshop survey
Learn how to set up your own AI application development environment

Fundamentals of Deep Learning: NVIDIA DLI Certification Workshop for Academia

April 5-6: FREE 2-Day Deep Learning Fundamentals NVIDIA DLI Certification Course 2025-04-05 · 08:00

Register for the FREE 2 day training course.

Deep Learning Fundamentals with PyTorch and FiftyOne NVIDIA DLI Certification Workshop for Academia

April 5-6\, 2025 \| 10 AM – 5 PM CET

About the Workshop

Note: This course is only available to university students, researchers and teaching staff. A valid university email address is required to obtain a certificate.

This two day workshop is an extension of NVIDIA’s DLI Deep Learning Fundamentals Course.

Learn to implement neural networks for image classification from scratch using PyTorch. Learn about stochastic gradient descent, multilayer perceptrons, convolutional neural networks, and transformers. We will explore data augmentation, workflow management, and dataset curation using FiftyOne, a powerful open source tool for image dataset curation.

On the first day we will focus on building and training neural networks with PyTorch.

On the second day we will focus on visual dataset curation with FiftyOne and iterative improvement of image classification models.

Instructor

Antonio Rueda-Toicen, an AI Engineer in Berlin, has extensive experience in deploying machine learning models and has taught over 300 professionals. He is currently a Research Scientist at the Hasso Plattner Institute. Antonio is a certified instructor of deep learning and diffusion models at NVIDIA’s Deep Learning Institute.

Prerequisites

Programming Prerequisites: Python fundamentals
Mathematics Prerequisites: Statistics and probability, linear algebra, calculus

Technologies Used in the Workshop

Python
Jupyter
PyTorch
Pandas
FiftyOne
Google Colab
Github Codespaces

Assessment Type

Skills-based coding assessments evaluate students’ ability to train a deep learning model to classify images with high accuracy.

Certificate

Upon successful completion of the coding assessment, participants will receive an NVIDIA DLI certificate to recognize their subject matter competency and support professional career growth.

Hardware Requirements

Desktop or laptop computer capable of running the latest version of Chrome or Firefox. Each participant will be provided with dedicated access to a fully configured, GPU-accelerated server in the cloud.

Language

English

April 5-6: FREE 2-Day Deep Learning Fundamentals NVIDIA DLI Certification Course

April 5-6: FREE 2-Day Deep Learning Fundamentals NVIDIA DLI Certification Course 2025-04-05 · 08:00

Register for the FREE 2 day training course.

Deep Learning Fundamentals with PyTorch and FiftyOne NVIDIA DLI Certification Workshop for Academia

April 5-6\, 2025 \| 10 AM – 5 PM CET

About the Workshop

Note: This course is only available to university students, researchers and teaching staff. A valid university email address is required to obtain a certificate.

This two day workshop is an extension of NVIDIA’s DLI Deep Learning Fundamentals Course.

Learn to implement neural networks for image classification from scratch using PyTorch. Learn about stochastic gradient descent, multilayer perceptrons, convolutional neural networks, and transformers. We will explore data augmentation, workflow management, and dataset curation using FiftyOne, a powerful open source tool for image dataset curation.

On the first day we will focus on building and training neural networks with PyTorch.

On the second day we will focus on visual dataset curation with FiftyOne and iterative improvement of image classification models.

Instructor

Antonio Rueda-Toicen, an AI Engineer in Berlin, has extensive experience in deploying machine learning models and has taught over 300 professionals. He is currently a Research Scientist at the Hasso Plattner Institute. Antonio is a certified instructor of deep learning and diffusion models at NVIDIA’s Deep Learning Institute.

Prerequisites

Programming Prerequisites: Python fundamentals
Mathematics Prerequisites: Statistics and probability, linear algebra, calculus

Technologies Used in the Workshop

Python
Jupyter
PyTorch
Pandas
FiftyOne
Google Colab
Github Codespaces

Assessment Type

Skills-based coding assessments evaluate students’ ability to train a deep learning model to classify images with high accuracy.

Certificate

Upon successful completion of the coding assessment, participants will receive an NVIDIA DLI certificate to recognize their subject matter competency and support professional career growth.

Hardware Requirements

Desktop or laptop computer capable of running the latest version of Chrome or Firefox. Each participant will be provided with dedicated access to a fully configured, GPU-accelerated server in the cloud.

Language

English

April 5-6: FREE 2-Day Deep Learning Fundamentals NVIDIA DLI Certification Course

April 5-6: FREE 2-Day Deep Learning Fundamentals NVIDIA DLI Certification Course 2025-04-05 · 08:00

Register for the FREE 2 day training course.

Deep Learning Fundamentals with PyTorch and FiftyOne NVIDIA DLI Certification Workshop for Academia

April 5-6\, 2025 \| 10 AM – 5 PM CET

About the Workshop

Note: This course is only available to university students, researchers and teaching staff. A valid university email address is required to obtain a certificate.

This two day workshop is an extension of NVIDIA’s DLI Deep Learning Fundamentals Course.

Learn to implement neural networks for image classification from scratch using PyTorch. Learn about stochastic gradient descent, multilayer perceptrons, convolutional neural networks, and transformers. We will explore data augmentation, workflow management, and dataset curation using FiftyOne, a powerful open source tool for image dataset curation.

On the first day we will focus on building and training neural networks with PyTorch.

On the second day we will focus on visual dataset curation with FiftyOne and iterative improvement of image classification models.

Instructor

Antonio Rueda-Toicen, an AI Engineer in Berlin, has extensive experience in deploying machine learning models and has taught over 300 professionals. He is currently a Research Scientist at the Hasso Plattner Institute. Antonio is a certified instructor of deep learning and diffusion models at NVIDIA’s Deep Learning Institute.

Prerequisites

Programming Prerequisites: Python fundamentals
Mathematics Prerequisites: Statistics and probability, linear algebra, calculus

Technologies Used in the Workshop

Python
Jupyter
PyTorch
Pandas
FiftyOne
Google Colab
Github Codespaces

Assessment Type

Skills-based coding assessments evaluate students’ ability to train a deep learning model to classify images with high accuracy.

Certificate

Upon successful completion of the coding assessment, participants will receive an NVIDIA DLI certificate to recognize their subject matter competency and support professional career growth.

Hardware Requirements

Desktop or laptop computer capable of running the latest version of Chrome or Firefox. Each participant will be provided with dedicated access to a fully configured, GPU-accelerated server in the cloud.

Language

English

April 5-6: FREE 2-Day Deep Learning Fundamentals NVIDIA DLI Certification Course

April 5-6: FREE 2-Day Deep Learning Fundamentals NVIDIA DLI Certification Course 2025-04-05 · 08:00

Register for the FREE 2 day training course.

Deep Learning Fundamentals with PyTorch and FiftyOne NVIDIA DLI Certification Workshop for Academia

April 5-6\, 2025 \| 10 AM – 5 PM CET

About the Workshop

Note: This course is only available to university students, researchers and teaching staff. A valid university email address is required to obtain a certificate.

This two day workshop is an extension of NVIDIA’s DLI Deep Learning Fundamentals Course.

Learn to implement neural networks for image classification from scratch using PyTorch. Learn about stochastic gradient descent, multilayer perceptrons, convolutional neural networks, and transformers. We will explore data augmentation, workflow management, and dataset curation using FiftyOne, a powerful open source tool for image dataset curation.

On the first day we will focus on building and training neural networks with PyTorch.

On the second day we will focus on visual dataset curation with FiftyOne and iterative improvement of image classification models.

Instructor

Antonio Rueda-Toicen, an AI Engineer in Berlin, has extensive experience in deploying machine learning models and has taught over 300 professionals. He is currently a Research Scientist at the Hasso Plattner Institute. Antonio is a certified instructor of deep learning and diffusion models at NVIDIA’s Deep Learning Institute.

Prerequisites

Programming Prerequisites: Python fundamentals
Mathematics Prerequisites: Statistics and probability, linear algebra, calculus

Technologies Used in the Workshop

Python
Jupyter
PyTorch
Pandas
FiftyOne
Google Colab
Github Codespaces

Assessment Type

Skills-based coding assessments evaluate students’ ability to train a deep learning model to classify images with high accuracy.

Certificate

Upon successful completion of the coding assessment, participants will receive an NVIDIA DLI certificate to recognize their subject matter competency and support professional career growth.

Hardware Requirements

Desktop or laptop computer capable of running the latest version of Chrome or Firefox. Each participant will be provided with dedicated access to a fully configured, GPU-accelerated server in the cloud.

Language

English

April 5-6: FREE 2-Day Deep Learning Fundamentals NVIDIA DLI Certification Course

Activities & events