Deep Learning courses

591 Courses

AWS Skill Builder

AWS ML Engineer Associate Curriculum Overview (Korean)

AWS ML 엔지니어 어소시에이트 교육 과정의 이 입문자용 과정에서는 기계 학습(ML) 관련 기본 사항을 복습하고 ML 및 AI의 발전 상황을 살펴봅니다. 비즈니스 목표를 파악하고 ML 문제를 공식화하며 Amazon SageMaker에 대해 알아봅니다. 과정 수준: 고급 소요 시간: 45분 참고: 이 과정의 동영상에는 한국어 트랜스크립트 또는 자막이 지원됩니다. 자막을 표시하.

University of California, Davis

AI for Knowledge Workers

Enroll Now - Enhance your skills in AI with the University of California, Davis through Coursera. This beginner-friendly course is your gateway to understanding AI, from Machine Learning to Generative AI, enabling you to transform your approach to both creative and critical thinking tasks in the workplace. Learn to harness AI technologies like.

Coursera

AI and Machine Learning Algorithms and Techniques

Delve into the essential algorithms and methodologies at the heart of AI and Machine Learning with this in-depth course. Discover how pre-trained large-language models (LLMs) and various learning paradigms like supervised, unsupervised, and reinforcement learning come together to solve complex business challenges. Gain hands-on experience in.

Coursera

IBM AI Engineering

Coursera AI technology is anticipated to expand by 37.3% by the year 2030, according to Forbes. The IBM AI Engineering Professional Certificate, offered through Coursera, equips data scientists, machine learning engineers, software engineers, and technical specialists with skills to excel as AI engineers. Throughout the program, participa.

Coursera

Advanced AI and Machine Learning Techniques and Capstone

Join our Advanced AI and Machine Learning Techniques and Capstone course to explore high-level AI & ML strategies. This course culminates in a capstone project where you'll utilize comprehensive skills to tackle a real-world challenge. Throughout, you'll encounter state-of-the-art machine learning methods and delve into the ethical consider.

Udemy

Machine Learning, Data Science and Generative AI with Python

Join our comprehensive, hands-on tutorial to delve into the realms of Machine Learning, Data Science, and Generative AI with Python. This course provides a deep dive into essential technologies and tools such as TensorFlow, GPT, OpenAI, and neural networks. Perfect for those seeking practical experience and aiming to advance their skills in m.

Udemy

Data Science: Modern Deep Learning in Python

Immerse yourself in the world of data science with our course on Modern Deep Learning in Python. Designed for both beginners and experienced practitioners, this course offers a comprehensive exploration of cutting-edge deep learning methods using popular Python libraries like TensorFlow, Theano, Keras, PyTorch, CNTK, and MXNet. Leverage the.

Udemy

Deep Learning with Keras

Join the Deep Learning with Keras course on Udemy to enhance your understanding of deep learning concepts using the powerful Keras library. Dive into models, layers, and modules, and get hands-on experience in building a neural network along with an image classification model. Perfect for aspiring data scientists looking to specialize in neur.

XuetangX

AI TIME PhD ICLR专场七

参与AI TIME PhD ICLR专场七，探索人工智能研究的最新突破。这次中文会议由国际学习表征会议（ICLR）的博士生主讲，讲述关于人工智能和机器学习领域的尖端发展和创新方法。本次会议为所有对人工智能、机器学习和计算机科学有兴趣的学者和研究人员提供了绝佳机会。您将获得权威的信息和见解，深入了解深度学习和神经网络方面的最新研究动向。主办单位：学堂在线 (Xueta.

XuetangX

AI TIME PhD 华南理工实验室专场二

Join an exclusive academic session that delves into pioneering research and discussions from the AI TIME PhD program at South China University of Technology laboratory. This event focuses on the latest advancements in artificial intelligence and technological innovations.

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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!