- Welcome
- Introduction to Deep Learning
- Artificial Neural Networks
- Neurons and Neural Networks
Intermediate
Online
5 Weeks
Quick facts
particular | details | |
---|---|---|
Medium of instructions
English
|
Mode of learning
Self study
|
Mode of Delivery
Video and Text Based
|
Course overview
In the present times where the advances in technology have shifted to IoT (Internet of Things), the concept of Deep Learning can be foreseen as one of the crucial ones, to be understood and well researched. Deep learning is faster and easier to develop and deploy as well. The Introduction to Deep Learning & Neural Networks with Keras certification course, the participants will get a deep insight into the Deep learning models. Furthermore, they will also be able to create models of Deep learning by making use of the Keras library.
The entrant will be introduced to exhilarating applications of Deep Learning. They will be learning about various deep learning algorithms and neural networks which are inspired by the functioning of neurons and the brain with respect to data processing. They will also get an insight into the working of the neural networks to feed the data throughout the network.
The Introduction to Deep Learning & Neural Networks with Keras training will provide knowledge about optimisation of variables as per the defined function, gradient descent algorithm, backpropagation, and updating the weights and biases of neural networks. Furthermore, the entrant will be taught about the activation functions and vanishing gradient problems.
The highlights
- Offered by IBM
- Approx. 8 hours time required to complete the programme
- Financial aid assistance
- Certificate of completion given by Coursera
Program offerings
- Reading material
- Practice exercises
- Quiz
- Pre-recorded video
Course and certificate fees
The Introduction to Deep Learning & Neural Networks with Keras certification fee is dependent on the choice of a number of months.
Fee details for Introduction to Deep Learning & Neural Networks with Keras
Courses provided by Coursera | Subscription fees per month |
1 Month, Fee | Rs. 4,023 |
3 Months, Fee | Rs. 8,046 |
6 Months, Fee | Rs. 12,069 |
certificate availability
certificate providing authority
Eligibility criteria
Certification Qualifying Details
The candidate has to complete the programme and all the assignments to get the Introduction to Deep Learning & Neural Networks with Keras certification by Coursera.
What you will learn
The participants will gain proficiency in the following skills after learning the Introduction to Deep Learning & Neural Networks with Keras certification syllabus:
- Describe the deep learning model and neural network along with the understanding of the difference between them.
- Understanding the supervised models of Deep learning like recurrent networks and convolutional neural networks.
- Demonstrating the unsupervised model of deep learning models like restricted Boltzmann machines and autoencoders.
- Building networks and deep learning, and artificial intelligence models using Keras library.
- Participants will also be introduced to various deep learning libraries like Pytorch, Tensorflow, and Keras.
- They will be able to create regression and classify the models by making use of the Keras library.
- Also, they will be provided with the knowledge of convolutional networks, autoencoders, and recurrent neural networks.
Who it is for
The Introduction to Deep Learning & Neural Networks with Keras course will be ideal for AI Developers.
Admission details
Follow the Introduction to Deep Learning & Neural Networks with Keras classes admission process as mentioned below:
Step 1: Visit the official site of Coursera.
https://www.coursera.org/learn/introduction-to-deep-learning-with-keras
Step 2: Choose the course Introduction to Deep Learning & Neural Networks with Keras classes.
Step 3: Click on the hyperlink ‘Enroll for free’ to enjoy a 7-days free trial.
Step 4: A pop-up having the details about information and policy will open. Click on ‘Start free trial’.
Step 5: Enter details including card number, name, expiry date, CVV, and more
Step 6: Enter the required details and get started for a free trial of 7 days.
The syllabus
Week 1: Introduction to Neural Networks and Deep Learning
Videos
Readings
- Syllabus
Practice Exercise
- Introduction to Neural Networks and Deep Learning
Week 2: Artificial Neural Networks
Videos
- Gradient Descent
- Backpropagation
- Vanishing Gradient
- Activation Functions
Practice exercise
- Artificial Neural Networks
Week 3: Keras and Deep Learning Libraries
Videos
- Deep Learning Libraries
- Regression Models with Keras
- Classification Models with Keras
Practice exercise
- Keras and Deep Learning Libraries
Week 4: Deep Learning Models
Videos
- Shallow Versus Deep Neural Networks
- Convolutional Neural Networks
- Recurrent Neural Networks
- Autoencoders
Practice exercise
- Deep Learning Models
Week 5: Course Project
Video
- Summary
Scholarship Details
There is a provision of financial aid to get access to the skills the participant wants to learn. Following are the steps to apply for financial aid:
- Visit the official site of Coursera https://www.coursera.org/learn/introduction-to-deep-learning-with-keras#
- Click on the hyperlink that states ‘Financial help available’.
- You will be guided to a pop-up window where you will be given an option to continue the application or Enroll and start learning today.
- Click on continue the application if you intend to take any financial help.
- Terms and conditions will be stated which you need to accept.
- By accepting, you will be guided to the application form wherein you will be asked your background information and a few descriptive questions.
- After answering, click on Submit application.
- The application will be reviewed in 15 days, and then the candidate will be reverted.
How it helps
Deep learning, as compared to machine learning, is much faster to develop and deploy in the application. Currently, Deep learning is extensively used in medical technology, automation and virtual reality. The applications of computer vision like detecting cancer and tumour face and voice recognition and self-driven vehicles make use of Deep Learning. The state-of-the-art results can be achieved by deep learning methods to troubleshoot the challenges like object detection, image classification, and face recognition. There is also another Introduction to Deep Learning & Neural Networks with Keras certification benefits that are mentioned down.
By enrolling on the course, the participant will understand the Deep learning model thoroughly. They will be able to correlate the resemblance of a Deep Learning algorithm and human brain functions to process the neuron data. They will have an understanding of the gradient descent algorithm and backpropagation along with the activation related functions. They will also be acknowledged about different deep learning libraries and building classification and regression models. They will also receive a fair idea about autoencoders and neural networks.
Instructors
Mr Alex Aklson
Data Scientist
IBM
Ph.D
FAQs
When the participants get enrolled in the course by subscribing to Coursera, they get a course completion certificate as well. The e-certificate can be shared online and linked to their LinkedIn profile. If the candidate chooses to audit the course, then they don’t get access to the certificate.
The course doesn’t have any credit at the university. The participant needs to check with their institution. However, courses under Master Track™ and Bachelors and Masters programme do have university credits.
The access to assignments and lectures varies depending on the enrolment chosen by the participant. If the participant chooses to audit the course, then s/he will be able to view the free course material.
There is a provision for financial aid. The participant needs to apply for it by filling the application form. The review of the application takes about 15 days after which the participant will be intimated.
Apart from pre-recorded videos and reading material the participants will be provided with practice exercise and quizzes.
The course instructor is Dr. Alex Aklson who is a data scientist at IBM Skill Development Network.
The course is approximately 8 hours long.
The videos and reading material are provided in English. However, there is a provision of video subtitles in Spanish, Russian, English, Portuguese, etc.
Yes, as the participants are provided with due flexibility, they may choose to take up more than one course.
The subscription in Coursera is charged on a monthly basis. After the completion of the free trial of 7-days, if somehow the participant fails to cancel the subscription on the 7th day, there will be a non-refundable deduction of monthly fees.
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