Keras is a high-level library that’s built on top of Theano or TensorFlow. And Keras provides a scikit-learn type API for building Neural Networks. By using Keras, you can easily build neural networks without worrying about the mathematical aspects of tensor algebra, numerical techniques, and optimization methods. That’s why in this article, I am gonna discuss the 7 Best Keras Online Courses.
So give your few minutes and find out the best keras online course. Before discussing the best keras online courses, I would like to mention a few reasons to learn Keras.
- Keras provides Multi-GPU and strong distributed support. So you can run your deep learning models on large GPU clusters.
- Keras has a simple API and that’s why it is the most easy-to-use library for machine learning for beginners.
- It has strong backend support. Keras acts as a wrapper that allows us to use either TensorFlow, theano, or any other framework.
- Due to its Pythonic nature, Keras need less code and it is easy to debug and easy to deploy.
So these are a few reasons to choose Keras. Now let’s move to the Keras online courses.
Best Keras Online Courses
Courses List-
- 1. Introduction to Deep Learning & Neural Networks with Keras- Coursera
- 2. Deep Learning- Udacity
- 3. Advanced Deep Learning with Keras- Datacamp
- 4. Deep Learning Fundamentals with Keras- edX
- 5. Applied AI with DeepLearning- Coursera
- 6. Complete Tensorflow 2 and Keras Deep Learning Bootcamp- Udemy
- 7. TensorFlow 2 for Deep Learning Specialization- Coursera
- Conclusion
1. Introduction to Deep Learning & Neural Networks with Keras– Coursera
Rating- 4.7/5
Provider- IBM
Time to Complete- 8 hours
This course is best for beginners who are planning to start their careers in deep learning. In this course, you will learn the basics of deep learning and get to know about deep learning and artificial neural networks.
This course will teach you how to build your first deep learning model with the Keras library. If you are an absolute beginner, then you should begin your deep learning journey with this course.
Now, let’s see the syllabus of the course-
Syllabus of the Course-
- Introduction to Neural Networks and Deep Learning
- Artificial Neural Networks
- Keras and Deep Learning Libraries
- Deep Learning Models
- Course Project
Extra Benefits-
- You will get a Course Certificates upon completion.
- Along with this, you will get Course Videos & Readings, Practice Quizzes, Graded Assignments with Peer Feedback, Graded Quizzes with Feedback, Graded Programming Assignments.
Who Should Enroll?
- Who is absolute beginner in deep learning.
Interested to Enroll?
2. Deep Learning- Udacity
Rating- 4.7/5
Time to Complete- 4 months(If you spend 12 hours per week)
This Nano-Degree program from Udacity will give you a complete understanding of Deep Learning. In this program, you will build convolutional networks for image recognition, recurrent networks for sequence generation, generative adversarial networks for image generation. You will build projects in Keras and NumPy, in addition to TensorFlow PyTorch.
Now, let’s see the topics covered in that program-
Topics Covered-
- Introduction to Deep Learning.
- Neural Networks
- Convolutional Neural Networks
- Recurrent Neural Networks
- Generative Adversarial Networks
- Deploying a Sentiment Analysis Model
Extra Benefits-
- You will get a chance to work on Real-world projects.
- You will get Technical mentor support.
- Along with that, you will get Career Services.
Who Should Enroll?
- Who has intermediate-level Python programming knowledge, and experience with NumPy and pandas.
- Who has math knowledge, including- algebra and some calculus.
- It’s a beginner-friendly program only Python knowledge is mandatory.
Interested to Enroll?
3. Advanced Deep Learning with Keras– Datacamp
Time to Complete- 4 hours
This is an advanced-level course that will teach you how to solve different problems using the versatile API of Keras. The course starts with multi-layer dense networks and then moves to the more advanced concepts like building deep learning models, understanding the architecture, multiple-output networks, category embeddings, etc.
There are 4 chapters in this course-
- The Keras Functional API
- Two Input Networks Using Categorical Embeddings, Shared Layers, and Merge Layers
- Multiple Inputs: 3 Inputs and Beyond!
- Multiple Outputs
Who Should Enroll?
- Who already knows basics of deep learning.
Interested to Enroll?
4. Deep Learning Fundamentals with Keras– edX
Provider- IBM
Time to Complete- 5 Weeks
This course provides the fundamentals of deep learning, the basics of neural networks, different deep learning models, and how to build deep learning models with Keras.
In this course, you will learn how to build a regression model, classification model, and convolutional neural network using the Keras library.
Now, let’s see the syllabus of the course-
Syllabus of the Course-
Module1 – Introduction to Deep Learning
-> Introduction to Deep Learning
-> Biological Neural Networks
-> Artificial Neural Networks – Forward Propagation
Module2 -Artificial Neural Networks
-> Gradient Descent
-> Backpropagation
-> Vanishing Gradient
-> Activation Functions
Module3 – Deep Learning Libraries
-> Introduction to Deep Learning Libraries
-> Regression Models with Keras
-> Classification Models with Keras
Module4 -Deep Learning Models
-> Shallow and Deep Neural Networks
-> Convolutional Neural Networks
-> Recurrent Neural Networks
-> Autoencoders
Extra Benefits-
- You can audit the course for FREE, but for certificate you have to pay additional fee.
Who Should Enroll?
- Who is familiar with Python and Machine learning.
Interested to Enroll?
5. Applied AI with DeepLearning– Coursera
Rating- 4.4/5
Provider- IBM
Time to Complete- 24 hours
This course starts with the fundamentals of Linear Algebra and Neural Networks. Knowledge of linear algebra is useful in grasping topics like time series, and neural networks.
Then you will learn deep learning frameworks like Keras, TensorFlow, PyTorch, DeepLearning4J, and Apache SystemML. In this course, you will also learn about Anomaly Detection, Time Series Forecasting, Image Recognition, and Natural Language Processing by building up models using Keras.
Now, let’s see the syllabus of the course-
Syllabus of the Course-
- Introduction to deep learning
- Deep Learning Frameworks
- Deep Learning Applications
- Scaling and Deployment
Extra Benefits-
- You will get a Course Certificates upon completion.
- Along with this, you will get Course Videos & Readings, Practice Quizzes, Graded Assignments with Peer Feedback, Graded Quizzes with Feedback, Graded Programming Assignments.
Who Should Enroll?
- Who is familiar with Python and Machine Learning.
Interested to Enroll?
6. Complete Tensorflow 2 and Keras Deep Learning Bootcamp- Udemy
Rating- 4.7/5
Provider- Jose Portilla
Time to Complete- 19 hours
This course will teach you how to use TensorFlow 2 framework to create artificial neural networks for deep learning. This course leverage the Keras API to quickly and easily build models.
In this course, you will learn how to build models to forecast future price homes, classify medical images, predict future sales data, generate complete new text artificially, etc.
Extra Benefits-
- You will get a Certificate of Completion.
- Along with that, you will get lifetime access to the course material.
Who Should Enroll?
- Who knows Python and want to learn about TensorFlow 2 for deep learning and artificial intelligence.
Interested to Enroll?
7. TensorFlow 2 for Deep Learning Specialization– Coursera
Rating- 4.9/5
Provider- Imperial College London
Time to Complete- 4 months( If you spend 7 hours per week)
This specialization program is for those who know machine learning and want to develop practical skills in the popular deep learning framework TensorFlow.
In the first course, you will learn the fundamental concepts to build, train, evaluate, and make predictions from deep learning models.
In the second course, you will learn more advanced concepts of TensorFlow and in the last course, you will learn how to develop probabilistic models with TensorFlow.
This specialization is 3-course series. Now, let’s see the course details-
Courses List-
- Getting started with TensorFlow 2
- Customizing your models with TensorFlow 2
- Probabilistic Deep Learning with TensorFlow 2
Now, let’s see what skills will you gain after completing this program-
Skills Gain-
- Tensorflow
- Keras
- TensorFlow Probability
- Probabilistic Neural Networks
- Deep Learning
- Probabilistic Neural Network
- Generative Model
- Probabilistic Programming Language (PRPL)
Extra Benefits-
- You will get a Shareable Certificate and Course Certificates upon completion.
- Along with that, you will get Course Videos & Readings, Practice Quizzes, Graded Assignments with Peer Feedback, Graded Quizzes with Feedback, Graded Programming Assignments.
Who Should Enroll?
- Who knows Python, machine learning concepts, basics of deep learning, and Probability and statistics.
Interested to Enroll?
And that’s all…So, these are the 7 Best Keras Online Courses. Now, it’s time to wrap up.
Conclusion
I hope these listed courses will help you to learn about the Keras library. I aim to provide you with the best resources for Learning. If you have any doubts or questions, feel free to ask me in the comment section.
Tell me in the comment section, which course do you like?
All the Best!
Happy Learning!
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Written By Aqsa Zafar
Founder of MLTUT, Machine Learning Ph.D. scholar at Dayananda Sagar University. Research on social media depression detection. Create tutorials on ML and data science for diverse applications. Passionate about sharing knowledge through website and social media.