Deep learning 25+ Free & Low cost online certification courses

Deep learning - All Coursera's Deep learning certification training Courses

1. › Deep Learning Specialization | Offered by "DeepLearning.AI" (Coursera)

Become a Machine Learning expert. Master the fundamentals of deep learning and break into AI.

Build and train deep neural networks, identify key architecture parameters, implement vectorized neural networks and deep learning to applications.

Build a CNN and apply it to detection and recognition tasks, use neural style transfer to generate art, and apply algorithms to image and video data.

Deep Learning Specialization

2. › DeepLearning.AI TensorFlow Developer Professional Certificate | Offered by "DeepLearning.AI" (Coursera)

• Best practices for TensorFlow, a popular open-source machine learning framework to train a neural network for a computer vision applications.
• Build natural language processing systems using TensorFlow.
• Handle real-world image data and explore strategies to prevent overfitting, including augmentation and dropout.

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3. › Neural Networks and Deep Learning | Offered by "DeepLearning.AI" (Coursera)

In the first course of the Deep Learning Specialization, you will study the foundational concept of neural networks and deep learning.

By the end, you will be familiar with the significant technological trends driving the rise of deep learning; build, train, and apply fully connected deep neural networks; implement efficient (vectorized) neural networks; identify key parameters in a neural network’s architecture; and apply deep learning to your own applications.

Course Link: learn/neural-networks-deep-learning

4. › TensorFlow 2 for Deep Learning Specialization | Offered by "Imperial College London" (Coursera)

This Specialization is intended for machine learning researchers and practitioners who are seeking to develop practical skills in the popular deep learning framework TensorFlow.

The first course of this Specialization will guide you through the fundamental concepts required to successfully build, train, evaluate and make predictions from deep learning models, validating your models and including regularisation, implementing callbacks, and saving and loading models.

specializations-tensorflow2-deeplearning

Deep learning - Best edx's Deep learning Courses tutorial

1. › Deep Learning Professional Certificate from "IBM" (edx)

Fundamental concepts of Deep Learning, including various Neural Networks for supervised and unsupervised learning.

Build, train, and deploy different types of Deep Architectures, including Convolutional Networks, Recurrent Networks, and Autoencoders.

Application of Deep Learning to real-world scenarios such as object recognition and Computer Vision, image and video processing, text analytics, Natural Language Processing, recommender systems, and other types of classifiers.

Link: Deep Learning Professional Certificate

2. › Deep Learning Fundamentals with Keras from "IBM" (edx)

In this course, you will learn What is deep learning, How do neural networks learn and what are activation functions, What are deep learning libraries and how do they compare to one another.

Start with this course, that will not only introduce you to the field of deep learning but give you the opportunity to build your first deep learning model using thepopular Keras library.

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3. › Deep Learning with Python and PyTorch from "IBM" (edx)

• This course is the second part of a two-part course on how to develop Deep Learning models using Pytorch.
• In the first course, you learned the basics of PyTorch, learn how to build deep neural networks in PyTorch.
• Also, you will learn how to train these models using state of the art methods.

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4. › Deep Learning with Tensorflow from "IBM" (edx)

In this TensorFlow course, you will learn the basic concepts of TensorFlow, the main functions, operations and the execution pipeline.

Much of theworld's data is unstructured. Think images, sound, and textual data. Learn how to apply Deep Learning with TensorFlow to this type of data to solve real-world problems.

Course Link: deep-learning-with-tensorflow

5. › Introduction to Deep Learning from "Purdue university" (edx)

Learn how deep learning algorithms can be used to solve important engineering problems.

You will will gain a principled understanding of the motivation, justification, and design considerations of the deep neural network approach to machine learning and will complete hands-on projects using TensorFlow and Keras.

Link: introduction-to-deep-learning-2

Top Linkedin's Deep learning online certification

1. › Advance Your Skills in Deep Learning and Neural Networks (Linkedin)

This learning path is your entryway into the tools, concepts, and finer points of computer vision, natural language processing, and more.

The hottest new frontier in the universe of AI and machine learning is in deep learning and neural networks.

Link: advance-your-skills-in-deep-learning-and-neural-networks

2. › Deep Learning Foundations: Natural Language Processing with TensorFlow (Linkedin)

In this course, instructor Harshit Tyagi provides a complete guide to understanding NLP using recurrent neural networks (RNNs).

You will learn how you can train RNNs to predict the next word in a sentence, which in turn allows you to generate some original text.

Link: deep-learning-foundations-natural-language-processing-with-tensorflow

3. › Deep Learning: Image Recognition (Linkedin)

In this course, learn how to build a deep neural network that can recognize objects in photographs.

Find out how to adjust state-of-the-art deep neural networks to recognize new objects, without the need to retrain the network.

Link: deep-learning-image-recognition

4. › Understand deep learning (Linkedin)

In this hands-on course, learn how to use the Python scientific stack to complete common data science tasks.

You can effectively process data with the Python scientific stack, including Pandas for data crunching, matplotlib for data visualization, NumPy for numeric computation, and more.

Link: data-science-foundations-python-scientific-stack

5. › Building and Deploying Deep Learning Applications with TensorFlow (Linkedin)

In this course, learn how to install TensorFlow and use it to build a simple deep learning model. After he shows how to get TensorFlow up and running, instructor Adam Geitgey demonstrates how to create and train a machine learning model, as well as how to leverage visualization tools to analyze and improve your model.

Online class Link: building-and-deploying-deep-learning-applications-with-tensorflow

Deep learning - Best Udacity's Deep learning Courses tutorial

1. › Deep Learning | NANODEGREE PROGRAM (Udacity)

Learn to build the deep learning models that are revolutionizing artificial intelligence.

Become an expert in neural networks, and learn to implement them using the deep learning framework PyTorch. Build convolutional networks for image recognition, recurrent networks for sequence generation, generative adversarial networks for image generation, and learn how to deploy models accessible from a website.

Link: Deep Learning NANODEGREE PROGRAM

2. › Become a Machine Learning Engineer (Udacity)

Learn advanced machine learning techniques and algorithms, including deployment to a production environment.

Learn advanced machine learning techniques and algorithms and how to package and deploy your models to a production environment. Gain practical experience using Amazon SageMaker to deploy trained models to a web application and evaluate the performance of your models.

Link: Become a Machine Learning Engineer

Top Futurelearn's Deep learning Courses training

1. › Deep Learning on Azure with Python: Introduction to Deep Learning (Futurelearn)

In this hands-on introduction to deep learning, you will learn about different neural network types. You’ll develop your understanding of key deep learning vocabulary, concepts, and algorithm, enabling you to understand how deep learning frameworks work.

Discover deep learning with Python using Microsoft Cognitive Toolkit, and explore deep learning algorithms and neural networks.

Course Link: deep-learning-explained

2. › Deep Learning and Python Programming for AI with Microsoft Azure (Futurelearn)

Discover deep learning in Azure in this ExpertTrack covering AI fundamentals, machine learning, and deep learning with Python.

This ExpertTrack offers advanced training in artificial intelligence and deep learning for AI professionals, students, analysts and engineers looking to take their AI skills and career to a higher level.

Link: advanced-ai-microsoft-azure

3. › Deep Learning on Azure with Python: AI for Beginners (Futurelearn)

This course is an introduction to artificial intelligence, using Microsoft Cognitive Services, with Python programming language as the medium.

Start your deep learning journey with this introductory Python-based course, exploring some of the fundamental applications of AI.

Link: introducton-to-ai-deep-learning