Overview
The Deep Learning Fundamentals with Keras Certificate from EdX is offered in partnership with IBMx. The programme is part of the Professional Certificate in Deep Learning.
Looking to kickstart a career in deep learning? Look no further. This course will introduce you to the field of deep learning and teach you the fundamentals. You will learn about some of the exciting applications of deep learning, the basics fo neural networks, different deep learning models, and how to build your first deep learning model using the easy yet powerful library Keras.
Key facts
This course will present simplified explanations to some of today's hottest topics in data science, including:
What is deep learning?
How do neural networks learn and what are activation functions?
What are deep learning libraries and how do they compare to one another?
What are supervised and unsupervised deep learning models?
How to use Keras to build, train, and test deep learning models?
The demand for deep learning skills-- and the job salaries of deep learning practitioners -- are continuing to grow, as AI becomes more pervasive in our societies. This course will help you build the knowledge you need to future-proof your career.
What you'll learn
- You will learn about exciting applications of deep learning and why it is really rewarding to learn how to leverage deep learning skills.
- You will learn about neural networks and how they learn and update their weights and biases.
- You will learn about the vanishing gradient problem.
- You will learn about building a regression model using the Keras library.
- You will learn about building a classification model using the Keras library.
- You will learn about supervised deep learning models, such as convolutional neural networks and recurrent neural networks, and how to build a convolutional neural network using the Keras library.
- You will learn about unsupervised learning models such as autoencoders.
Get more details
Visit programme websiteProgramme Structure
Modules included:
Module1 - Deep Learning
- 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
- 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
Check out the full curriculum
Visit programme websiteKey information
Duration
- Part-time
- 2 months
- 2 hrs/week
Start dates & application deadlines
Language
Delivered
- Self-paced
Disciplines
Artificial Intelligence Machine Learning View 144 other Short Courses in Artificial Intelligence in United StatesExplore more key information
Visit programme websiteAcademic requirements
We are not aware of any specific GRE, GMAT or GPA grading score requirements for this programme.
English requirements
We are not aware of any English requirements for this programme.
Other requirements
General requirements
Prerequisites:
- Python Programming. For example, you can complete this course on edX: Python Basics for Data Science.
- Machine Learning with Python. For example, you can complete this course on edX: Machine Learning with Python: A Practical Introduction.
- Partial Derivatives. You can find tutorials for this on Khan Academy.
Make sure you meet all requirements
Visit programme websiteTuition Fee
-
International
99 USD/fullTuition FeeBased on the tuition of 99 USD for the full programme during 2 months. -
National
99 USD/fullTuition FeeBased on the tuition of 99 USD for the full programme during 2 months.
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