Neural Networks and Deep Learning by Deep learning via Coursera: Fee, Duration, How to Apply

Quick Facts

particular	details
Medium of instructions English	Mode of learning Self study	Mode of Delivery Video and Text Based

Course overview

Neural Networks and Deep Learning is an online certification programme available on Coursera which is offered by DeepLearning.AI, an online education technology platform with the aim of building a global community of AI talent and professionals. This programme is one of the five specializations of deep learning.

Neural Networks and Deep Learning Certification Course is intended to assist the learners to get acquainted with fundamental concepts of neural networks and deep learning. In Neural Networks and Deep Learning Certification Syllabus, the learners will be provided with the opportunity to explore the technology of Artificial Intelligence by knowing the strategies, challenges, and outcomes of deep learning.

Neural Networks and Deep Learning Certification by Coursera will equip the students with the skills and potential of designing and executing the deep neural networks, bring about the deep learning application in their works, apply the vectorized neural networks and understand the major technological trends in deep learning.

Course and certificate fees

certificate availability

Yes

certificate providing authority

Coursera

Who it is for

Software engineer

Neural Networks and Deep Learning Classes is an intermediate course that is open for enrolment for the professionals like Software engineers, Technical professionals, etc.

Eligibility criteria

Academic Qualifications

The Neural Networks and Deep Learning Online Course can be joined by any candidate who is passionate about exploring data science. However, the prospective candidates are recommended to have an understanding of Python skills, a basic understanding of programming, loops, if/else statements, and data structures to take full advantage of the programme.

Certification Qualifying Details

Neural Networks and Deep Learning Certification will be awarded to the candidates only if they finished the complete proceedings of the programme including the course videos and readings, graded assignments, and various quizzes.

What you will learn

Knowledge of deep learning

After the completion of Neural Networks and Deep Learning Training, the learners will have a thorough understanding of the following concepts:

Deep Learning
Artificial Neural Network
Backpropagation
Python Programming
Neural Network Architecture

The syllabus

Module 1: Introduction to Deep Learning

Videos

What is a Neural Network?
Supervised Learning with Neural Networks
Why is Deep Learning taking off?
About this Course
Geoffrey Hinton Interview

Readings

Frequently Asked Questions
Lecture Notes W1

Quiz

Introduction to Deep Learning

App Items

Intake Survey
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Plugin

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Module 2: Neural Networks Basics

Videos

Binary Classification
Logistic Regression
Logistic Regression Cost Function
Gradient Descent
Derivatives
More Derivative Examples
Computation Graph
Derivatives with a Computation Graph
Logistic Regression Gradient Descent
Gradient Descent on m Examples
Vectorization
More Vectorization Examples
Vectorizing Logistic Regression
Vectorizing Logistic Regression's Gradient Output
Broadcasting in Python
A Note on Python/Numpy Vectors
A quick tour of Jupyter/iPython Notebooks
Explanation of Logistic Regression Cost Function (Optional)
Pieter Abbeel Interview

Readings

Derivation of DL/DZ (Optional)
Deep Learning Honor Code
Programming Assignment FAQ
How to Download your Notebook
How to Refresh your Workspace

Quiz

Neural Network Basics

Programming Assignments

Python Basics with Numpy
Logistic Regression with a Neural Network Mindset

Module 3: Shallow Neural Networks

Videos

Neural Networks Overview
Neural Network Representation
Computing a Neural Network's Output
Vectorizing Across Multiple Examples
The explanation for Vectorized Implementation
Activation Functions
Why do you need Nonlinear Activation Functions?
Derivatives of Activation Functions
Gradient Descent for Neural Networks
Backpropagation Intuition (Optional)
Random Initialization
Ian Goodfellow Interview

Quiz

Shallow Neural Networks

Programming Assignments

Planar Data Classification with One Hidden Layer

Module 4: Deep Neural Networks

Videos

Deep L-layer Neural Network
Forward Propagation in a Deep Network
Getting your Matrix Dimensions Right
Why Deep Representations?
Building Blocks of Deep Neural Networks
Forward and Backward Propagation
Parameters vs Hyperparameters
What does this have to do with the brain?

Readings

Optional Reading: Feedforward Neural Networks in Depth
Clarification For What does this have to do with the brain?
Confusing Output from the AutoGrader
References
Acknowledgments

Quiz

Key Concepts on Deep Neural Networks

Programming Assignments

Building your Deep Neural Network: Step by Step
Deep Neural Network - Application

Admission details

Step 1 - First, the candidates need to register and sign up on https://www.coursera.org/ to get the courses offered on Coursera.

Step 2 - By activating the Coursera account, the candidate can sign in.

Step 3 - Then, the candidate can search ‘DeepLearning.AI’ to be able to find the courses offered by DeepLearning.AI.

Step 4 - Find the course Neural Networks and Deep Learning in the list and click on it.

Step 5- Then, the page of the course will appear, click on the option ‘enrol’ and pay the mentioned amount of fee, or can just audit the course without paying the fee.

Scholarship Details

If the candidates are not able to pay the fee prescribed by Coursera, they can apply for financial aid by clicking on the option “Financial aid available” and filling in the requested information including the annual income, employment status, etc.

How it helps

Neural Networks and Deep Learning Certification benefits consist of the following:

After the completion of the course, the learners will be able to learn technological trends of deep learning and machine learning.
This programme will help the students to explore the applications of efficient (vectorized) neural networks and key parameters in the architecture of neural networks.

Instructors

Dr Andrew Ng
Professor of Computer Science
Stanford

Mr Kian Katanforoosh
Senior Curriculum Developer
Deep learning

Mr Younes Bensouda Mourri
Curriculum developer
Deep learning

FAQs

What is the duration of the Neural Networks and Deep Learning Online Course?

This course will need about 24 hours to complete.

Who are the instructors of Neural Networks and Deep Learning Online Certification?

The course is instructed by Younes Bensouda Mourri, Andrew Ng, and Kian Katanforoosh who are considered to be top instructors of Coursera.

Will all of the candidates be conferred with a certificate?

Only the students who had paid for the course will be awarded the certificate. The learners who audit the course are not able to get the certificate.

Who administers the program?

The programme is administered by DeepLearning.AI which aims at spreading the education of AI around the world through numerous courses and certifications.

Which are the languages in which the subtitles are provided?

The subtitles are provided in the languages of English, Chinese (Traditional), Arabic, French, Ukrainian, Portuguese (European), Chinese (Simplified), Italian, Portuguese (Brazilian), Vietnamese, Korean, German, Russian, Turkish, English, Spanish and Japanese.