Deep Learning courses

635 Courses

Coursera

Introduction to AI and Machine Learning

Welcome to the Introduction to AI and Machine Learning Course—a crucial step in the 3-course specialization for AWS Certified AI Practitioner. This course is perfect for beginners or those looking to enhance their AI skills. Immerse yourself into essential AI topics, including major machine learning algorithms and practical applications. Key.

Coursera

Distributed Computing & AI with Spark

Join our course to explore the intersection of distributed computing and artificial intelligence. Build your skills by implementing and training models with TensorFlow and Keras, from simple networks to advanced pre-trained models using transfer learning. Engage in a hands-on mini-project on image classification and benefit from personalized gui.

Coursera

AI Strategy for Business Leaders with ChatGPT, ML & DL

Unlock the power of AI to transform your business strategy with our comprehensive course designed for business leaders. Equip yourself with the knowledge to harness AI, including ChatGPT, machine learning (ML), and deep learning (DL), to gain a competitive advantage. Gain a solid foundation in AI fundamentals, debunk common myths, and explore th.

Coursera

Introduction to AI

Discover the fundamental concepts behind artificial intelligence (AI) and machine learning in this engaging introductory course. Dive into the various types of AI, consider ethical implications, and explore key machine learning models that are the backbone of contemporary AI systems. Whether you aim to directly work with AI, enhance your softw.

Coursera

Google Cloud Skills Boost

Gen AI: Unlock Foundational Concepts

Google Cloud Skills Boost

Northeastern University

Generative AI: Foundations and Concepts

Unlock the world of Generative AI with this comprehensive course offered by Northeastern University through Coursera. Gain an understanding of the key concepts and mathematical principles that form the backbone of Generative AI. Delve into practical applications in engineering, with a focus on neural networks, attention mechanisms, and advance.

Coursera

Udemy

AI & ML Made Easy: From Basic to Advanced (2025)

Join our comprehensive course, AI & ML Made Easy: From Basic to Advanced (2025), where you will learn the fundamentals of Artificial Intelligence and Machine Learning, progressing to advanced deep learning techniques. Taught by industry experts on Udemy, this course offers a hands-on approach through real-world projects. Categories: Artific.

Udemy

60 PDUs for your next PMP Renewal 2.0

Refresh your PMP Certification with our comprehensive course designed to provide you with the 60 Professional Development Units (PDUs) required by the Project Management Institute (PMI). Offered by Udemy, this program ensures you meet all necessary standards while gaining enhanced skills in key sectors. Dive into a diverse range of subjects th.

Udemy

Complete Generative AI for upskilling & learning initiatives

Unlock the potential of Generative AI in the realm of personalized learning and upskilling with our dedicated course. Offered by Udemy, this program is tailored for individuals eager to delve into the nuances of Generative AI models. Whether you're looking to enhance your machine learning skills, explore deep learning, or understand the intri.

Udemy

GenAI and Cybersecurity – Frameworks and Best Practices 2025

Embark on a comprehensive journey into the world of GenAI and cybersecurity with our upcoming course, "GenAI and Cybersecurity – Frameworks and Best Practices 2025." Gain insights into the adoption of GenAI technologies within enterprises, guided by proven tools and frameworks. This course offers an in-depth exploration of real-world case stu.

Udemy

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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:

Face recognition by the DeepFace system is about 97%, and this result is about the same as that of the average person.

Imitation of human speech by the WaveNet system. This is not reading the text, but composing sentences with accents, without errors in stress and without unnatural pauses.

Making medical diagnoses. For example, determining diabetic retinopathy from photographs of the eyes. The technology is already being used in US medical institutions.

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:

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.

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.

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.

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!