Deep Learning with TensorFlow
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Course
Deep Learning with TensorFlow
Build skills and get hands-on experience using TensorFlow. Explore its main functions and operations, and investigate different types of deep architecture, including convolutional networks, recurrent networks, and autoencoders.
Kick-start your deep learning career with critical skills in this core technology.
Self-Paced
Mentored
Beginner
Duration
3-4 hours/week
TensorFlow is a popular deep learning framework for businesses seeking to maximise the value of their data. Created by Google, it was tailored for machine learning and is now deemed to be one of the best libraries for implementing deep learning. Individuals with strong skills in TensorFlow, therefore, are in high demand.
During this course, you will be introduced to the basic concepts of TensorFlow. You will explore its main functions, operations, and the execution pipeline. Starting with a Hello World example, you will first investigate how TensorFlow can be used in curve fitting, regression, classification, and the minimization of error functions.
You will then learn how to apply TensorFlow for backpropagation to tune weights and biases while neural networks are being trained. Plus, you will be introduced to different types of deep architecture, including convolutional networks, recurrent networks, and autoencoders.
For individuals keen to build a career in the fast-growing field of deep learning, Deep Learning with TensorFlow is the ideal place to start.
This IBM certified course comprises five purposely designed modules that take you on a carefully defined learning journey.
It is a self-paced course, which means it is not run to a fixed schedule with regard to completing modules or submitting assignments. To give you an idea of how long the course takes to complete, it is anticipated that if you work 3-4 hours per week, you will complete the course in 5 weeks. However, as long as the course is completed by the end of your enrollment, you can work at your own pace. And dont worry, youre not alone! You will be encouraged to stay connected with your learning community and mentors through the course discussion space.
The materials for each module are accessible from the start of the course and will remain available for the duration of your enrollment. Methods of learning and assessment will include videos, reading material, and online exam questions.
As part of our mentoring service you will have access to valuable guidance and support throughout the course. We provide a dedicated discussion space where you can ask questions, chat with your peers, and resolve issues. Depending on the payment plan you have chosen, you may also have access to live classes and webinars, which are an excellent opportunity to discuss problems with your mentor and ask questions. Mentoring services will vary across packages.
Once you have successfully completed the course, you will earn your IBM Certificate.
After completing this course, you will be able to:
- Explain foundational TensorFlow concepts such as the main functions, operations, and execution pipelines.
- Describe how TensorFlow can be used in curve fitting, regression, classification, and the minimization of error functions.
- Understand different types of deep architectures such as convolutional networks, recurrent networks, and autoencoders.
- Apply TensorFlow for backpropagation to tune weights and biases while the neural networks are being trained.
This course is suitable for learners with both technical and non-technical backgrounds.
It is particularly useful for people working in, or aspiring to work in, the following roles:
- Machine learning engineers
- Data scientists
- Business intelligence analysts
- Data quality analysts