What Is Sales Analytics and How Does It Benefit My Business?
March 4, 2024
Article
This course is part of multiple programs.
Instructors: Samaya Madhavan
Instructor ratings
We asked all learners to give feedback on our instructors based on the quality of their teaching style.
36,310 already enrolled
Included with
(904 reviews)
Recommended experience
Intermediate level
Basic/intermediate experience in Python programming, machine learning
Fundamentals of Deep Learning with Keras
(904 reviews)
Recommended experience
Intermediate level
Basic/intermediate experience in Python programming, machine learning
Fundamentals of Deep Learning with Keras
Create custom layers and models in Keras and integrate Keras with TensorFlow 2.x
Develop advanced convolutional neural networks (CNNs) using Keras
Develop Transformer models for sequential data and time series prediction
Explain key concepts of Unsupervised learning in Keras, Deep Q-networks (DQNs), and reinforcement learning
Add to your LinkedIn profile
18 assignments
Add this credential to your LinkedIn profile, resume, or CV
Share it on social media and in your performance review
Deep learning is revolutionizing many fields, including computer vision, natural language processing, and robotics. In addition, Keras, a high-level neural networks API written in Python, has become an essential part of TensorFlow, making deep learning accessible and straightforward. Mastering these techniques will open many opportunities in research and industry.
You will learn to create custom layers and models in Keras and integrate Keras with TensorFlow 2.x for enhanced functionality. You will develop advanced convolutional neural networks (CNNs) using Keras. You will also build transformer models for sequential data and time series using TensorFlow with Keras. The course also covers the principles of unsupervised learning in Keras and TensorFlow for model optimization and custom training loops. Finally, you will develop and train deep Q-networks (DQNs) with Keras for reinforcement learning tasks (an overview of Generative Modeling and Reinforcement Learning is provided). You will be able to practice the concepts learned using hands-on labs in each lesson. A culminating final project in the last module will provide you an opportunity to apply your knowledge to build a Classification Model using transfer learning. This course is suitable for all aspiring AI engineers who want to learn TensorFlow and Keras. It requires a working knowledge of Python programming and basic mathematical concepts such as gradients and matrices, as well as fundamentals of Deep Learning using Keras.
This module provides an overview of Keras advanced features. It will cover Keras functional API for complex model creation. It also includes the creation of custom layers and models in Keras. Then the module describes the integration of Keras with TensorFlow 2.x for enhanced functionality. You will apply your learnings in labs and test your concepts in quizzes.
5 videos2 readings3 assignments2 app items1 discussion prompt2 plugins
In this module, you will learn to develop advanced convolutional neural networks (CNNs) using Keras. You will learn data augmentation techniques with Keras. In addition, you will implement transfer learning with Keras and leverage pre-trained models. Finally, you will learn how to use TensorFlow for enhancing image processing capabilities. You will apply your learnings in labs and test your concepts in quizzes.
6 videos1 reading4 assignments3 app items1 discussion prompt2 plugins
This module covers building and training advanced Transformers using Keras. You will further develop Transformer models for sequential data and time series using TensorFlow with Keras. In addition, you will learn to implement advanced Transformer techniques for text generation. You will apply your learnings in labs and test your concepts in quizzes.
5 videos1 reading3 assignments2 app items1 discussion prompt1 plugin
In this module, you will learn the principles of unsupervised learning in Keras. You will learn to build and train autoencoders and diffusion models. In addition, you will develop generative adversarial networks (GANs) using Keras and integrate TensorFlow for advanced unsupervised learning tasks. You will apply your learnings in labs and test your concepts in quizzes.
5 videos1 reading3 assignments3 app items1 discussion prompt1 plugin
In this module, you will learn advanced techniques in Keras for model development. You will create custom training loops and optimize models using Keras and perform hyperparameter tuning with Keras Tuner. Finally, you will learn to use TensorFlow for model optimization and custom training loops. You will apply your learnings in labs and test your concepts in quizzes.
5 videos1 reading3 assignments2 app items1 discussion prompt1 plugin
In this module, you will learn the fundamentals of reinforcement learning and its applications in Keras. The module also covers the Q-Learning algorithms using Keras. You will develop and train deep Q-networks (DQNs) with Keras for advanced reinforcement learning tasks. You will apply your learnings in labs and test your concepts in quizzes.
3 videos1 reading2 assignments2 app items1 discussion prompt1 plugin
In this module, you will implement the final project and attempt the final assessment.
1 video2 readings1 peer review2 app items2 plugins
We asked all learners to give feedback on our instructors based on the quality of their teaching style.
Instructor ratings
We asked all learners to give feedback on our instructors based on the quality of their teaching style.
At IBM, we know how rapidly tech evolves and recognize the crucial need for businesses and professionals to build job-ready, hands-on skills quickly. As a market-leading tech innovator, we’re committed to helping you thrive in this dynamic landscape. Through IBM Skills Network, our expertly designed training programs in AI, software development, cybersecurity, data science, business management, and more, provide the essential skills you need to secure your first job, advance your career, or drive business success. Whether you’re upskilling yourself or your team, our courses, Specializations, and Professional Certificates build the technical expertise that ensures you, and your organization, excel in a competitive world.
Professional Certificate
DeepLearning.AI
Course
904 reviews
63.57%
22.18%
8.27%
2.86%
3.09%
Showing 3 of 904
Reviewed on Jul 2, 2020
Deep Learning made me feel that there is a way to build models and classify data so easily and in a skillful way. Amazing course!
Reviewed on Jul 25, 2020
Nice course to introduce you to more advanced neural network algorithms, I wish the evaluations were more challenging and based on practical exercises... there is no final assignment either.
Reviewed on Feb 23, 2022
I expected some more explaination for the concepts. However from tensorflow website, more could be learnt.
Unlimited access to 10,000+ world-class courses, hands-on projects, and job-ready certificate programs - all included in your subscription
Earn a degree from world-class universities - 100% online
Upskill your employees to excel in the digital economy
Access to lectures and assignments depends on your type of enrollment. If you take a course in audit mode, you will be able to see most course materials for free. To access graded assignments and to earn a Certificate, you will need to purchase the Certificate experience, during or after your audit. If you don't see the audit option:
The course may not offer an audit option. You can try a Free Trial instead, or apply for Financial Aid.
The course may offer 'Full Course, No Certificate' instead. This option lets you see all course materials, submit required assessments, and get a final grade. This also means that you will not be able to purchase a Certificate experience.
When you enroll in the course, you get access to all of the courses in the Certificate, and you earn a certificate when you complete the work. Your electronic Certificate will be added to your Accomplishments page - from there, you can print your Certificate or add it to your LinkedIn profile. If you only want to read and view the course content, you can audit the course for free.
If you subscribed, you get a 7-day free trial during which you can cancel at no penalty. After that, we don’t give refunds, but you can cancel your subscription at any time. See our full refund policy.