Improve your AI skills with the help of our Best Deep Learning Courses. Certificates of completion are available to prove your expertise in creating sophisticated AI models.
Key Takeaways
- Learn comprehensive deep-learning concepts.
- Access to hands-on projects to build AI models.
- Certificates are available to validate your skills.
What do deep learning courses with certificates entail?
These courses teach advanced AI techniques along with practical model building. Certificates are available that endorse your expertise in artificial intelligence.
In order to help our readers in taking a knowledgeable learning decision, TakeThisCourse.net has introduced a metric to measure the effectiveness of an online course. Learn more about how we measure an online course effectiveness. Deep Learning Courses Evaluation & Selection Criteria
This list has been curated after assessing the curriculum depth, expertise of the instructors in AI, and the prominence of the issuing institution. Other factors were learner feedback, certifications provided, and the inclusion of practical projects.
Best Deep Learning Classes with Certificates
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- Dan Becker via DataCamp
- 04 hours of effort required!
- 214,481+ already enrolled!
In this course, you will be getting hands-on practical knowledge of how deep learning can be used with Keras 2.0 which is the latest version of a cutting-edge library for deep learning in Python.
- The reason why we chose this course is its focus on explaining how you can optimize the predictions that we generate by neural networks. With that, the course also teaches the backward propagation method in detail.
- This course is for those who wish to learn to optimize their deep learning models in Keras.
Related: Best Python Machine Learning Courses
More Deep Learning Courses with Certificates
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- DeepLearning.AI via Coursera
- 684,393+ already enrolled!
- ★★★★★ (123,377 Ratings)
This specialization will help you master the fundamentals of deep learning and also break into AI in the best possible manner.
- The best thing about this specialization is its focus on explaining how to build a CNN and then apply it to detection and recognition tasks.
- This specialization is for those who wish to learn to build and train deep neural networks.
All the five courses in the specialization have taught me the deep learning fundamentals in detail. Each course had something unique to offer. The best part was the explanation on deep learning black box. Other topics like structuring machine learning projects and what convolutional neural networks are etc were also fun to learn. (Anonymous learner, ★★★★★)
Deep Learning Professional Certification [No more Available]
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- IBM via edX
- 07 months (2-4 hrs/week) of effort required!
- Study Type: Self-paced
This “Deep Learning Professional Certification” is all about explaining the fundamental concepts of deep learning which includes various neural networks for supervised and unsupervised learning.
- The reason why we chose this course is its focus on explaining how to build, train, and deploy several deep architecture types including Convolutional networks, autoencoders and recurrent networks.
- This course is for those who wish to master deep learning art scale along with accelerated hardware and GPUs.
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- Imperial College London via Coursera
- 14,229+ already enrolled!
- ★★★★★ (448 Ratings)
Online Course Effectiveness Score |
Content | Engagement | Practice | Career Benefit |
Excellent ★★★★★ | Excellent ★★★★★ | Good ★★★★☆ | Good ★★★★☆ |
In this specialization, you will understand the fundamental concepts which are required to build, train, evaluate, and make a prediction from deep learning models.
- The best thing about this specialization is its focus on deepening your knowledge and skills with TensorFlow.
- This specialization is for all the machine learning researchers and practitioners out there who wish to develop practical skills in the most popular deep learning framework which is TensorFlow.
Related: End-to-End Machine Learning with TensorFlow on GCP
This is a great specialization that teaches you in detail about the deep learning models. How you can validate your models and understand the probabilistic approach to deep learning are my most favorite topics from the specialization. (Anonymous learner, ★★★★★)
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- MIT via edX
- 15 months (10-14 hrs/week) of effort required!
- Study Type: Instructor-paced
This “Machine Learning with Python” training will help you understand the principles behind machine learning problems like regression, reinforcement learning, classification, clustering, etc.
- The reason why we chose this training is its focus on explaining how to implement and analyze different models including linear models, kernel machines, neural networks, and more.
- This training is for those who wish to learn to implement and organize machine learning projects in detail.
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- Miguel Esteban via DataCamp
- 04 hours of effort required!
- 23,258+ already enrolled!
This course will help you learn what regression is and how to save the earth by predicting asteroid trajectories.
- The best thing about this course is its focus on explaining how to apply binary classification for differentiating between real and fake dollar bills.
- This course is for those who wish to learn to use neural networks for reconstructing noisy images and much more.
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- Zachary Deane-Mayer via DataCamp
- 04 hours of effort required!
- 23,721+ already enrolled!
In this deep learning course, the instructor will show you how to solve several problems using versatile Keras functional API.
- The best thing about this course is its focus on explaining how to build models with multiple inputs and a single output as well.
- This course is for those who wish to learn to train a network that could do both classification and regression.
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- DeepLearning.AI via Coursera
- 1,074,782+ already enrolled!
- ★★★★★ (113,669 Ratings)
Online Course Effectiveness Score |
Content | Engagement | Practice | Career Benefit |
Excellent ★★★★★ | Excellent ★★★★★ | Good ★★★★☆ | Good ★★★★☆ |
This course is all about exploring the foundational concepts of neural networks and deep learning.
- The best thing about this course is its focus on explaining the technological trends driving the rise of deep learning. You will also understand the capabilities, challenges, and consequences of deep learning.
- This course is for those who wish to learn to identify the key parameters in a neural network’s architecture and apply deep learning to applications.
This was a very interesting course. All the lecture videos were equally great and engaging. The tips on avoiding the possible bugs due to shapes was the best part for me. I was also impressed by the accent of the instructor. Professor Ng is without any doubt the best instructor I ever got to learn from. (Wu Y, ★★★★★)
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- Adam Geitgey via LinkedIn
- 44,009+ already enrolled!
- ★★★★★ (268 Ratings)
Online Course Effectiveness Score |
Content | Engagement | Practice | Career Benefit |
Good ★★★★☆ | Good ★★★★☆ | Fair ★★★☆☆ | Fair ★★★☆☆ |
In this deep learning class, you will learn to build a neural network that has the ability to recognize objects in any photograph.
- The best thing about this class is its focus on explaining how you can adjust state-of-the-art deep neural networks for recognizing new objects.
- This class is for those who wish to explore the cloud-based image recognition APIs that can be used as an alternative to build your own system.
This class is not only interesting but engaging as well and teaches you in detail how to use Colab of PyCharm for avoiding the initial setup. I have found this class to be well-structured as well. (Joshua Wilson, ★★★★★)
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- CloudSwyft via FutureLearn
- 04 weeks (05 hrs/week) of effort required!
- Study Type: Self-paced
This course is all about discovering deep learning with Python and that too using Microsoft Cognitive toolkit. Here you will also explore deep learning algorithms and understand what neural networks are.
- The best thing about this course is its focus on exploring the common frameworks for neural networks.
- This course is for all those who wish to gain practical experience in Python for deep learning.
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- Jose Portilla via Udemy
- 16,439+ already enrolled!
- ★★★★★ (92,303 Ratings)
Online Course Effectiveness Score |
Content | Engagement | Practice | Career Benefit |
Excellent ★★★★★ | Good ★★★★☆ | Fair ★★★☆☆ | Fair ★★★☆☆ |
In this complete guide, you will be taught how to use Google’s deep learning framework in detail. Here you will also understand how neural networks work.
- The reason why we chose this course is its focus on explaining how you can use TensorFlow for classification and regression tasks.
- This course is for those who wish to understand how to build a neural network from scratch and that too using Python.
I believe this was a detail course that had detailed explanation on how to build neural network. With that, the step-by-step coding was also helpful in understanding the different concepts and codes. Plus the concise reviews at the end of each video were also quite helpful in grasping the concepts. (FDS T, ★★★★★)
LinkedIn Learning offers top deep learning courses to help you advance your career in this field. Whether you wish to gain skills in deep learning or understand what neural networks are. Want to understand deep learning fundamentals or know what data-driven learning design is, whatever you wish to learn about deep learning, there is a course for you all that is available at LinkedIn Learning. So visit the site today and find the right deep learning course for yourself today.
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- DeepLearning.AI via Coursera
- 146,385+ already enrolled!
- ★★★★★ (18,506 Ratings)
Online Course Effectiveness Score |
Content | Engagement | Practice | Career Benefit |
Excellent ★★★★★ | Excellent ★★★★★ | Good ★★★★☆ | Good ★★★★☆ |
In this specialization, you will get to handle real-world image data and explore the different strategies which are used for preventing overfitting which includes augmentation and dropout.
- The best thing about this specialization is its focus on explaining how to build natural language processing systems using TensorFlow.
- This specialization is for those who wish to understand the best practices for TensorFlow and learn to train a neural network for computer vision applications.
This specialization has 4 courses and each course has engaging content to share. The second course was quite engaging where the instructor explains how to build scalable AI-powered algorithms. The rest of the courses were also very engaging and thus this specialization is worth one’s time and effort. (Anonymous learner, ★★★★★)
Online Course Effectiveness Score |
Content | Engagement | Practice | Career Benefit |
Good ★★★★☆ | Good ★★★★☆ | Fair ★★★☆☆ | Fair ★★★☆☆ |
This certification course is all about helping you master popular algorithms like CNN, RCNN, RNN, LSTM, RBM and many more using the latest “TensorFlow 2.0” package in Python. Here you will also get to work on real-time projects like emotion and gender detection, auto image captioning using CNN and LSTM and so much more.
This was a very well-structured course that explained really well about deep learning. Would definitely recommend it to all those learners out there who are interested in deep learning. (Anonymous learner, ★★★★★)
Final Thoughts
We can conclude by saying deep learning is certainly the most effective AI technology for numerous applications and it for sure has a great future. Therefore, start your journey in deep learning today and never stop learning.