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Learn Deep Learning online: university courses, full YouTube courses, and courses with free certificates, from the IITs, MIT, Harvard, Google, Microsoft and more.
Coursera
Production ML models failing your latency targets? Learn how to make them run 3-5x faster without losing accuracy. This course helps ML engineers and data scientists optimize neural network inference for real-world deployment—across mobile, edge, and cloud environments. If you face slow model infer…
Coursera
In Deep Learning Model Engineering and Optimization, you’ll learn to choose the right architecture, build a strong PyTorch baseline, and systematically optimize models for accuracy and generalization. This course is organized around real job tasks. You’ll start by checking what you already know, th…
Coursera
In this 2-hour long guided project, we are going to create a recurrent neural network and train it on a tweet emotion dataset to learn to recognize emotions in tweets. The dataset has thousands of tweets each classified in one of 6 emotions. This is a multi class classification problem in the natur…
Board Infinity
"This intermediate-level course takes you beyond AI theory into the practical world of Natural Language Processing (NLP) powered by Transformer architectures. You’ll trace the evolution of language models—from traditional statistical methods and recurrent networks to attention-based systems like BE…
Board Infinity
Master advanced deep learning architectures and efficient training techniques using PyTorch Lightning, timm, ConvNeXt, Vision Transformers, RoPE, SwiGLU, RMSNorm, and Weights & Biases. This course equips you to design, train, and benchmark modern backbones on limited GPU hardware for real-world pro…
Coursera
You've learned how to use Tensorflow. You've learned the important functions, how to design and implement sequential and functional models, and have completed several test projects. What's next? It's time to take a deep dive into activation functions, the essential function of every node and layer…
Coursera
In this 2-hour project-based course, you will be able to : - Understand the Massachusetts Roads Segmentation Dataset and you will write a custom dataset class for Image-mask dataset. Additionally, you will apply segmentation domain augmentations to augment images as well as its masks. For image-mas…
Coursera
In this hands-on project, we will train machine learning and deep learning models to predict the % of Silica Concentrate in the Iron ore concentrate per minute. This project could be practically used in Mining Industry to get the % Silica Concentrate at much faster rate compared to the traditional…
Coursera
Neural networks power the intelligent systems transforming industries today—from autonomous vehicles to personalized recommendations. This Short Course was created to help data analysts accomplish the critical transition from traditional machine learning to deep learning architectures. By completin…
Coursera
The goal of this project is to introduce beginners to the basic concepts of machine learning using TensorFlow. The project will include, how to set up the tool and get started as well as understanding the fundamentals of machine learning/neural network model and its key concepts. Learning how to us…
Coursera
This is a hands-on, guided project on optimizing your TensorFlow models for inference with NVIDIA's TensorRT. By the end of this 1.5 hour long project, you will be able to optimize Tensorflow models using the TensorFlow integration of NVIDIA's TensorRT (TF-TRT), use TF-TRT to optimize several deep…
Coursera
In this 2-hour long guided project, we will use Keras Tuner to find optimal hyperparamters for a Keras model. Keras Tuner is an open source package for Keras which can help machine learning practitioners automate Hyperparameter tuning tasks for their Keras models. The concepts learned in this proje…
Coursera
Building and Optimizing AI Models introduces the foundational engineering practices required to design, train, and optimize machine learning models for modern AI systems. In this course, you will explore statistical machine learning methods, neural network architectures, and deep learning optimizat…
Coursera
In this 2-hour long guided project, we will use a ResNet-18 model and train it on a COVID-19 Radiography dataset. This dataset has nearly 3000 Chest X-Ray scans which are categorized in three classes - Normal, Viral Pneumonia and COVID-19. Our objective in this project is to create an image classif…
Edureka
This course guides you through the foundational principles behind neural networks and computer vision systems, focusing on how forward propagation, backpropagation, optimization, and convolutional architectures enable modern AI applications. Through hands-on demonstrations and practical exercises,…
Coursera
Advance your Java expertise to build intelligent, production-grade systems for enterprise decision-making. This course deepens your machine learning skills within the Java ecosystem, covering supervised and unsupervised learning, classification, regression, clustering, and neural networks. You’ll u…
Coursera
In this 90-min long project-based course you will learn how to use Tensorflow to construct neural network models. Specifically, we will design, execute, and evaluate a neural network model to help a retail company with their marketing campaign by classifying images of clothing items into 10 differe…
Coursera
In this project, learners will gain the skill of building and evaluating machine learning models using TensorFlow Decision Forests to accurately classify penguin species based on physical measurements. They will construct a comprehensive machine learning model under the guidance of the instructor.…
Coursera
In this guided project, we are going to create a neural network and train it on a small dataset of superhero names to learn to generate similar names. The dataset has over 9000 names of superheroes, supervillains and other fictional characters from a number of different comic books, TV shows and mo…
Coursera
In this project-based course, we will build, train and test a machine learning model to detect diabetes with XG-boost and Artificial Neural Networks. The objective of this project is to predict whether a patient has diabetes or not based on their given features and diagnostic measurements such as n…
