Deep Learning courses

487 Courses

Deep Learning Prerequisites: The Numpy Stack in Python (V2+)

Course Provider: Udemy Enhance your data analysis skills and lay a solid foundation for advanced artificial intelligence applications with this comprehensive course on the Numpy stack. Dive into the practical applications of Numpy, Scipy, Pandas, and Matplotlib to seamlessly transition into the realms of deep learning and machine learning. Cours.
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Master Computer Vision™ OpenCV4 in Python with Deep Learning

Develop your computer vision expertise with the "Master Computer Vision™ OpenCV4 in Python with Deep Learning" course. Dive into the world of OpenCV4 and enhance your skills in Dlib and deep learning using Keras, TensorFlow, and Caffe. This comprehensive program offers you 21 real-life projects that bolster your understanding and application of.
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Neural Networks in Python: Deep Learning for Beginners

Embark on your journey into the world of Artificial Neural Networks with our comprehensive beginner's course, "Neural Networks in Python: Deep Learning for Beginners." Designed for aspiring data scientists and AI enthusiasts, this course will guide you through the fundamentals of neural networks using Python. Throughout this course, you will le.
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Deep Learning: Convolutional Neural Networks in Python

Embark on a comprehensive journey into the realm of Deep Learning with our course on Convolutional Neural Networks (CNNs) using Python. Dive into TensorFlow 2 and empower your skills in fields such as Computer Vision and Natural Language Processing (NLP). Ideal for those interested in Data Science and Machine Learning, this course will enhance y.
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Deep Learning with TensorFlow 2.0

Advance your technical skills with our specialised course on Deep Learning with TensorFlow 2.0. This course offers a comprehensive guide to building sophisticated deep learning algorithms, immersing you in the world of neural networks. Learn from Udemy's seasoned instructors through hands-on projects and real-world business case applications..
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Generative AI, from GANs to CLIP, with Python and Pytorch

Expand your knowledge and skills in artificial intelligence by diving into the world of generative models. Our Udemy course, "Generative AI, from GANs to CLIP, with Python and Pytorch," offers a comprehensive guide to understanding and implementing cutting-edge AI architectures. Designed for those passionate about AI development, this course.
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The Data Science Course: Complete Data Science Bootcamp 2024

Discover a complete training path in Data Science with the Data Science Bootcamp 2024 offered by Udemy. This extensive course covers essential topics from basic mathematics and statistics to advanced concepts in Python programming, machine learning, and deep learning. Whether you're starting your journey in data science or looking to.
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Learn Machine learning & AI [Beginner to advanced content]

Embark on your journey to master Machine Learning and Artificial Intelligence with our expertly designed course, perfect for beginners and advanced learners alike. Offered through Udemy, this program provides an in-depth understanding of crucial AI and Machine Learning concepts. What sets this course apart is its focus on hands-on projects, desi.
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H2O ai Large Language Models (LLMs) - Level 1

Embark on your journey with Large Language Models (LLMs) through our Level 1 course, crafted for both novices and individuals with some machine learning background. Gain a deep understanding of critical concepts and techniques in language modeling, guided by Andreea Turcu, an AI education specialist from H2O ai. Discover the essence of langu.
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Artificial intelligence is moving towards becoming on the same level as the living human mind. In such dangerous proximity to the execution of one of the futurological scenarios, it becomes a little scary, but at the same time very interesting. Artificial intelligence is nurtured by machine learning specialists. In the last decade, the deep learning method has been developing, and its results are already impressive.

What is deep learning?

“Deep learning” – literally “deep learning”. This is about artificial intelligence and increasing its abilities through training, based not on artificial codes, but on principles similar to the development of human intelligence. Deep learning methods make it possible to make machines self-learning.

The term itself and developments in this area appeared 40 years ago, but until 2012 they could not be applied in practice, as they were limited by insufficient technical capacity. Now there are already published works by the pioneers of deep learning, and textbooks and training courses in this specialty are gradually appearing.

Deep learning on your fingers: The ability of a machine to find an answer using calculations is called artificial intelligence. A machine can be taught to learn independently by building appropriate algorithms - this is called machine learning. With this approach, coded algorithms will no longer be needed to solve problems. The process of acquiring and using skills imitates human thinking and is called deep learning.

What tasks can be performed using deep learning right now?

If at the dawn of automation machines learned to do mechanical work for humans, now machines are learning to do routine intellectual work for us. The further progress we make, the more tasks we can shift to them, freeing up time for what really matters.

Officially, the main task of deep learning is the automation of complex tasks in various areas of human activity. It's like a computer, only of a different century and a different level.

But of particular interest is the neural network’s assistance in creating programs for solving cognitive problems.

Enough general phrases, let's move on to examples:

It’s hard to even imagine what awaits us in the future if people outside of IT have just heard about deep machine learning, and it has already produced such amazing results.

Why study deep learning?

To earn twice as much as ordinary IT specialists. Progress in the field of information technology is not just walking, but actually running, and it’s time to benefit from it. The sphere is not yet oversaturated, and oversaturation will not happen soon. Still, creating neural networks is not as simple as filing nails or maintaining Instagram accounts. But now is the time to start studying in order to develop along with your specialty and, perhaps, soon become someone who develops it.

Deep learning courses that currently exist are divided into four categories. Decide for yourself which one is for you:

  1. Trainings are highly specialized classes for practicing specific skills. Suitable for those who need to form an understanding of the basic principles of machine thinking.

  2. Long courses - for AI specialists and those involved in database analysis. Long-term deeplearning ai courses are not for everyone and require patience and time.

  3. University programs - for maximum immersion in the subject. They may be too difficult for beginners, although the application of effort will give results that should not be expected from short courses.

  4. A short best deep learning course on technology in business - general information for managers who will not be doing it themselves, but need to have an understanding of the subject.

You will have to put in a lot of effort, but the result is worth it. Just for fun, you can look at vacancies for deep learning specialists on sites with job offers and evaluate upcoming prospects. Not everyone needs deep learning experience yet, and soon all the sweet jobs will require several years of practice. So, if you have the ability to train soulless machines that are almost equal to us in intelligence, hurry up to take up vacant positions after a deep learning online course from AI Eeducation!