Free Online Deep Learning Courses and Certifications 2024
Deep Learning is a branch of Artificial Intelligence that uses algorithms to model high-level abstractions in data. It is used in various fields such as computer vision, natural language processing, and robotics. People with knowledge in mathematics, computer science, and statistics are suitable for courses related to Deep Learning.
Popular Courses
MIT's Introduction to Deep Learning 6.S191 is a comprehensive course for those interested in learning the foundations of deep learning. Led by Alexander Amini, the course covers topics such as the perceptron, neural networks, loss functions, training and gradient descent, backpropagation, setting the learning rate, batched gradient descent, and regularization. With slides and lab materials available at http://introtodeeplearning.com/, this course is perfect for those looking to gain a better understanding of deep learning. Subscribe to stay up to date with new lectures or follow @MITDeepLearning on Twitter and Instagram to stay connected!
Learn MoreDeep learning is a powerful tool for AI-powered technologies. This course provides an intuitive approach to building complex models that can solve real-world problems with human-like intelligence. Learn how to use the Microsoft Cognitive Toolkit to harness the intelligence within massive datasets through deep learning with speed, accuracy, and scalability. Financial assistance is available for those who need it. Enroll now and unlock the power of deep learning!
Learn MoreThis 7-week course is designed to help coders with at least one year of experience and some knowledge of high-school math to learn practical deep learning. From setting up a GPU server to creating state-of-the-art models for computer vision, natural language processing, and recommendation systems, this course covers it all. With around 20 hours of lessons, it requires about 10 hours of work per week for 7 weeks to complete. The course is based on lessons from the first certificate course at The Data Institute at USF and Part 2 will be available online in May 2017.
Learn MoreThis specialization in Deep Learning for Healthcare is designed for those interested in applying machine learning to medical applications. It covers topics such as health data analysis, different types of neural networks, and training and application of neural networks on real-world medical scenarios. Whether you are a machine learning expert or a medical professional, this specialization will provide you with the knowledge and skills to make a difference in healthcare.
Learn MoreDiscover the power of deep learning and apply it to real-world problems with this introductory course. Learn from Google's Principal Scientist and technical lead in the Google Brain team, Vincent Vanhoucke, and gain the skills to build your own deep learning models. Start your journey today!
Learn MoreExplore the power of deep learning and transform your teaching with this innovative course. Join now and become an education leader in the 21st century.
Learn MoreThis course is perfect for beginners who want to learn CATIA part design from scratch. It covers all the fundamentals of CATIA from A to Z. You will learn how to create 3D models, use the tools and features of CATIA, and apply the best practices for part design. By the end of the course, you will be able to design 3D models with confidence.
Learn MoreThis tutorial provides an introduction to modern deep convolutional neural networks and their implementation with PyTorch. It covers advanced deep learning and representation learning techniques for image recognition.
Learn MoreThis course provides an introduction to the Numpy stack in Python, essential tools for deep learning, machine learning, and artificial intelligence. It covers the fundamentals of Numpy, Scipy, Pandas, and Matplotlib, providing a comprehensive overview of the capabilities of each library.
Learn MoreThe integration of blockchain and deep learning technologies is set to revolutionize the future of Artificial Intelligence. This will create new job opportunities and require specialized training to ensure the workforce is prepared.
Learn MoreThis course provides an introduction to the exciting world of deep learning and neural networks, giving learners the tools to become proficient in AI. With hands-on exercises and real-world examples, learners can gain the skills necessary to become an AI expert.
Learn MoreThis course from Yonsei University provides an introduction to Deep Learning (DL) and its applications in business. Students will learn how DL is used in modern devices such as smartphones, smartwatches, and automobiles, and explore the potential of DL for future self-learning capabilities.
Learn MoreThis Deep Learning program is the perfect opportunity to join the next generation of AI-powered talent. You will learn cutting-edge topics such as neural networks, convolutional neural networks, recurrent neural networks, and generative adversarial networks. This program will help you define a highly beneficial future for the world. Don't miss out on this chance to become a leader in the field of deep learning.
Learn MoreThis course provides an introduction to deep learning, a powerful set of algorithms used in machine learning. It covers the fundamentals of deep learning, such as gradient descent and backpropagation, as well as design constructs of neural networks and how to optimize them for accuracy and robustness. The course combines theory and practice, with PyTorch code to reinforce both. It is suitable for anyone interested in learning the fundamentals of deep learning.
Learn MoreThis course is perfect for anyone looking to learn the fundamentals of deep learning and machine learning with Keras and Python. It covers the basics of the Keras library and how to use it to create powerful deep learning models. With practical examples and hands-on activities, this course will help you gain the skills and knowledge you need to start building your own deep learning models. Sign up now and start your journey into the world of deep learning and machine learning with Keras and Python.
Learn MoreThis comprehensive online tutorial is perfect for anyone looking to learn Deep Learning and Convolutional Neural Network using Python and Keras. From beginners to professionals, this course offers a comprehensive guide to understanding the fundamentals of Deep Learning and Neural Networks. Sign up now and start your journey to becoming an expert in this field!
Learn More Deep Learning Courses
Career Trends
Career Prospects
| Average Salary | Position Overview
|
Deep Learning Engineer | $187,585 per year
| Deep learning engineers develop and maintain machine learning models, working in conjunction with a team of data scientists, software engineers, and other experts. They are tasked with building new AI-powered systems capable of performing advanced functions, such as image recognition and natural language processing. |
Computer Vision Engineer | $162, 028 per year | As a Computer Vision Engineer, your responsibilities include developing, testing, debugging, deploying, and maintaining computer vision algorithms and hardware for various environments. You will also be tasked with developing automated vision algorithms, particularly for use with robots and autonomous hardware systems. |
Software Engineer | $166,416 per year | Software engineering is a field within computer science that focuses on the process of designing, developing, testing, and maintaining software applications. This involves using principles of engineering and expertise in programming languages to create effective and efficient software solutions for end-users. |
Data Scientist | $186,585 per year | Data scientists are professionals who identify the important questions to be answered and locate the relevant data sources. They possess both business knowledge and analytical expertise, along with the ability to extract, clean, and present data effectively. Companies rely on data scientists to handle and analyze large amounts of unstructured data. |
Research Engineer | $138,695 per year | As a Research Engineer, your role involves building prototypes, products, and systems for testing purposes. You will design testing procedures and coordinate with others to identify problems and solutions. You will also collaborate on standards for procedures and component requirements, and coordinate and communicate work efforts. |
Educational Paths
1. Online courses: Platforms like Coursera, Udemy, and edX offer online courses on Deep Learning from top universities and industry experts.
2. Certifications: Professional certifications like TensorFlow Developer Certificate or NVIDIA Deep Learning Institute Certification can help you demonstrate your skills and knowledge in Deep Learning.
3. Master's degree: Pursuing a Master's degree in Computer Science or Artificial Intelligence with a focus on Deep Learning can provide in-depth knowledge and hands-on experience.
4. PhD: For those interested in research and academia, pursuing a PhD in Computer Science or Machine Learning can be a good option.
5. Bootcamps: Bootcamps like Springboard or Metis offer intensive training programs in Deep Learning, often with a focus on practical applications and job placement assistance.
Frequently Asked Questions and Answers
Q1: What Deep Learning courses can I find on AZ Class?
On this page, we have collected free or certified 85 Deep Learning online courses from various platforms. The list currently only displays up to 50 items. If you have other needs, please contact us.
Q2: Can I learn Deep Learning for free?
Yes, If you don’t know Deep Learning, we recommend that you try free online courses, some of which offer certification (please refer to the latest list on the webpage as the standard). Wish you a good online learning experience!
