HomeSpecialization
Deep Learning specialization
Live Class

Deep Learning

4.7

(558 ratings)

Batch Starts : October 1, 2021

AI is growing exponentially. From self driving cars to movie recommendations to cancer detection, AI is helping us in our daily lives. This Deep Learning specialisation is foundational program that will help you kick start your career in AI. You will learn ANN, CNN, RNN and how to build them.....

Features

Certificate Icon
Shareable Certificate
Earn a Certificate upon completion
Interview Icon
Instant Doubt Resolution
Get your doubt clarified instantly
Lecture Icon
100% online Live Class
Mentor driven live classes.
Notebook Icon
Practice Material
Get Notebook to revise, practice, test your self and interact with mentor

What you'll learn

Tick Icon
Understand Deep Learning and its applications
Tick Icon
What are Neural Networks and how to train and use them
Tick Icon
Different types of neural networks, ANN,CNN & RNN
Tick Icon
How to solve real world problems using deep learning

Class Syllabus

  • Class 1: Introduction to Deep Learning

    Why Machine Learning fails for large dataset, introduction to deep learning, Neurons, neural networks, how they are similar to human brain
  • Class 1

    October 1, 2021 | 03:01 PM

    Introduction to Deep Learning

    Why Machine Learning fails for large dataset, introduction to deep learning, Neurons, neural networks, how they are similar to human brain
October 1, 2021 | 03:01 PM
  • Class 2: Artificial Neural Networks - 1

    Understanding artificial neural networks, neurons, input layers, output layers, wights, bias, activation functions. Case study on ANN
  • Class 2

    October 5, 2021 | 03:01 PM

    Artificial Neural Networks - 1

    Understanding artificial neural networks, neurons, input layers, output layers, wights, bias, activation functions. Case study on ANN
October 5, 2021 | 03:01 PM
  • Class 3: Artificial Neural Networks - 2

    Working of neural networks, forward propagation and backward propagation, deep layered neural networks Case study on ANN
  • Class 3

    October 8, 2021 | 03:01 PM

    Artificial Neural Networks - 2

    Working of neural networks, forward propagation and backward propagation, deep layered neural networks Case study on ANN
October 8, 2021 | 03:01 PM
  • Class 4: Convolutional Neural Networks - 1

    Why Artificial Neural Networks fails for data such as images, Understanding convolution, Padding, pooling, Case study on CNN
  • Class 4

    October 12, 2021 | 03:01 PM

    Convolutional Neural Networks - 1

    Why Artificial Neural Networks fails for data such as images, Understanding convolution, Padding, pooling, Case study on CNN
October 12, 2021 | 03:01 PM
  • Class 5: Convolutional Neural Networks - 2

    How Convolutional neural networks work, Fully Connected Layers, normalization, os library, unzip, image resizing, colab patches for images, transfer learning. Case study on CNN
  • Class 5

    October 15, 2021 | 03:01 PM

    Convolutional Neural Networks - 2

    How Convolutional neural networks work, Fully Connected Layers, normalization, os library, unzip, image resizing, colab patches for images, transfer learning. Case study on CNN
October 15, 2021 | 03:01 PM
  • Class 6: Recurrent Neural Networks - 1

    How to process sequence like text and how to train machine for them, Vanishing Gradient or Exploding Gradient Problem, Limitation of ANN and CNN, Introduction to RNN. Case study on RNN
  • Class 6

    October 19, 2021 | 03:01 PM

    Recurrent Neural Networks - 1

    How to process sequence like text and how to train machine for them, Vanishing Gradient or Exploding Gradient Problem, Limitation of ANN and CNN, Introduction to RNN. Case study on RNN
October 19, 2021 | 03:01 PM
  • Class 7: Recurrent Neural Networks - 2

    Limitations of RNN and advantages of LSTM, LSTM (Long Short Term Memory), Encoder - Decoder network attention model, Keras: tokenizer, Rms prop optimizer, NLTK stopwords, Keras: Pad Sequences. Case study on RNN
  • Class 7

    October 22, 2021 | 03:01 PM

    Recurrent Neural Networks - 2

    Limitations of RNN and advantages of LSTM, LSTM (Long Short Term Memory), Encoder - Decoder network attention model, Keras: tokenizer, Rms prop optimizer, NLTK stopwords, Keras: Pad Sequences. Case study on RNN
October 22, 2021 | 03:01 PM
  • Class 8: Capstone project - Part 1

    Capstone project part 1, data cleaning, model building
  • Class 8

    October 26, 2021 | 03:01 PM

    Capstone project - Part 1

    Capstone project part 1, data cleaning, model building
October 26, 2021 | 03:01 PM
  • Class 9: Capstone Project - Part 2

    Capstone Project part 2, Model testing, app building, deploying to cloud
  • Class 9

    October 29, 2021 | 03:01 PM

    Capstone Project - Part 2

    Capstone Project part 2, Model testing, app building, deploying to cloud
October 29, 2021 | 03:01 PM

Prerequisites

Tick Icon
Python Programming Basics

Practice more with
Notebook

Learn anytime, anywhere

Enroll in unlimited courses, get a personalized schedule and never miss a live class with our timely reminders

Test your knowledge

Enroll in unlimited courses, get a personalized schedule and never miss a live class with our timely reminders

Hands on with code

Enroll in unlimited courses, get a personalized schedule and never miss a live class with our timely reminders

Get your doubts cleared

Enroll in unlimited courses, get a personalized schedule and never miss a live class with our timely reminders

Deep Learning

  • Shareable Certificate
  • Showcase to employers
  • Get recognized

What our learners have to say about us!

Raghav Thakur

babu banrasi das institute of technology and management(engg. and tech.)
5

I enjoyed the deep learning specialisation live classes. Initially it looks tough but with live explanation, i got my concepts cleared.

Frequently Asked Questions

What are the differences between 'Explorer', 'Coder' and 'Hacker' subscription types?

In Explorer subscription type you can attend free courses/live classes/sessions any number of times for 1 month (from the date of signup).


In Coder subscription type you can attend all courses/live classes/sessions (both free and paid) unlimited times for 1 year. Additionally you can choose and attend 1 Project session of your interest.


In Hacker subscription type you can attend all courses, projects/live classes/sessions unlimited times for 1 year. Also you can attend all project sessions.

What are Specialisations?

Specialisations are career paths. They guides you about the particular career path, why its important, what skills you need to learn in that career path, classes and projects available in that career path etc.