Deep Learning in collaboration with IBM

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Industry Experts From

Universally Recognized Certificates

From IBM and DataTrained

Capstone and Real Life Projects

Access to 15 real life projects and a capstone project

Analytics Jobs Placement Assistance

Access to analyticsjobs.in curated jobs

Access to in-demand Tools

IBM Watson labs and $1200 equivalent Cloud Credits

₹49,999 ($750)

for self-paced

₹67,500 ($1,020)

for self-paced and live sessions blended mode

About the Program

  • Deep Learning Fundamentals

  • Deep Learning with TensorFlow

  • Natural Language Processing

  • Computer Vision

  • Accelerating Deep Learning with GPU

Download Syllabus

Prerequisite

A. Applied Data Science with Python in collaboration with IBM
https://cognitiveclass.ai/learn/data-science-with-python

B. Machine Learning with Python in collaboration with IBM
https://cognitiveclass.ai/courses/machine-learning-with-python

IBM is an American multinational information technology company headquartered in Armonk, New York, with operations in over 170 countries.  IBM is one of the world's largest employers, with over 350,000 employees, known as "IBMers". At least 70% of IBMers are based outside the United States, and the country with the largest number of IBMers is India. [7]  IBM employees have been awarded five Nobel Prizes, six Turing Awards, ten National Medals of Technology (USA) and five National Medals of Science (USA). This collaboration between IBM and DataTrained provide our student's hands-on experience in predictive analytics and advanced computing.

Expectations for this program co-developed with IBM:
1.    Industry-recognized certificate from IBM and DataTrained.
2.    IBM Cloud Credits for 6 months equivalent to $1200
3.    IBM Cloud Platforms access like IBM Watson for hands-on practice
In this particular learning path, you are going to be in a position to master the fundamental ideas of Deep Leaning as well as TensorFlow. After that, you are going to get hands-on experience in solving issues using Deep Learning. Beginning with a basic "Hello Word" instance, throughout the program you are going to be in a position to see just how TensorFlow could be utilized in curve fitting, regression, minimization, and classification of error functions. This idea is then explored within the Deep Learning community. You are going to learn the right way to put on TensorFlow for back propagation to tune the weights as well as biases even though the Neural Networks are now being trained. Lastly, the course covers various kinds of Deep Architectures, for instance, Convolutional Networks, Recurrent Networks as well as Autoencoders.
A. Applied Data Science with Python in collaboration with IBM
https://cognitiveclass.ai/learn/data-science-with-python

B. Machine Learning with Python in collaboration with IBM
https://cognitiveclass.ai/courses/machine-learning-with-python

Programming Languages and Tolls Covered

Instructors

Learn from India’s leading Software Engineering faculty and Industry leaders

Learning Path

1
Course 1: Deep Learning Fundamentals

Deep Learning provides a simplified idea of the hottest topics in data science today:
This course answers some of the basic questions on Deep Learning

A. What's Deep Learning?
B. What are actually convolutional neural networks?
C. Why is deep learning very powerful and its usage?

* Be a part of a quickly growing area in data science; there is no better time than right now to get going with neural networks.


Module 1 - Introduction to Deep Learning
. Why Deep Learning?
. What is a neural network?
. Three reasons to go Deep
. Your choice of Deep Net
. An old problem: The Vanishing Gradient

* Module 2 - Deep Learning Models
. Restricted Boltzmann Machines
. Deep Belief Nets
. Convolutional Networks
. Recurrent Nets

* Module 3 - Additional Deep Learning Models
. Autoencoders
. Recursive Neural Tensor Nets
. Deep Learning Use Cases

* Module 4 - Deep Learning Platforms and Software Libraries
. What is a Deep Learning Platform?
. H2O.ai
. Dato GraphLab
. What is a Deep Learning Library?
. Theano
. Caffe
. TensorFlow

Course 2: Deep Learning with TensorFlow


The vast majority of data and information on the earth are actually unlabeled and unstructured. Shallow neural networks can't quickly capture related structures in, for example, pictures, audio, and textual details. Deep networks are actually able to discover concealed structures within this data type. In thisTensorFlow course, you will make use of Google's library to use deep learning to different types of data to be able to solve real-world issues.


Module 1 – Introduction to TensorFlow
. HelloWorld with TensorFlow
. Linear Regression
. Nonlinear Regression
. Logistic Regression
. Activation Functions

Module 2 – Convolutional Neural Networks (CNN)
. CNN History
. Understanding CNNs
. CNN Application

Module 3 – Recurrent Neural Networks (RNN)
. Intro to RNN Model
. Long Short-Term memory (LSTM)
. Recursive Neural Tensor Network Theory
. Recurrent Neural Network Model

Module 4 - Unsupervised Learning
. Applications of Unsupervised Learning
. Restricted Boltzmann Machine
. Collaborative Filtering with RBM

Module 5 - Autoencoders
. Introduction to Autoencoders and Applications
. Autoencoders
. Deep Belief Network
2

3
Natural Language Processing
Module 1. Introduction to NLP

. Overview
. Introduction to libraries
. Environmental setup
. Installing dependencies
 
Module 2: - Sentiment Analysis:
. Loading dataset
. Pre-processing dataset
. Creating word Embeddings
. Designing layers
. Training the model
. Predicting from the model

Module-3 Text Summarization:
. Loading dataset
. Pre-processing dataset
. Creating word Embeddings
. Designing layers
. Training the model
. Predicting from the model

Course 4: Computer Vision
Module 1. Introduction to Computer Vision
. Overview
. Introduction to libraries
. Environmental setup
. Installing dependencies

Module 2: - Face Detection:
. Single Face Detection in Images
. Multiple Face detection in Images
. Single Face Detection in Pre-recorded Videos
. Multiple Face detection in Pre-recorded Videos
. Single Face Detection in Iive feed videos
. Multiple Face detection in live feed videos

Module-2 Face Recognition
. Single Face Recognition in Images
. Multiple Face Recognition in Images
. Single Face Recognition in Pre-recorded Videos
. Multiple Face Recognition in Pre-recorded Videos
. Single Face Recognition in Live feed videos
. Multiple Face Recognition in live feed videos

Module 3: - Image Classification
. Loading Training Image data
. Training custom images using CNN

Module 4- Object Detection
. Loading Training Image
. Training Custom object using YOLO
4

5
Course 5: Accelerating Deep Learning with GPU

6 Months Program in Deep Learning in collaboration with IBM

Get eligible for 3 world-class certifications thus adding that extra edge to your resume.
  • Alumni Status
  • Learning paths and certification from IBM
  • Course completion certificate from DataTrained Education
  • Project completion certificate from DataTrained Education

Admission Process

There are 3 simple steps in the Admission Process which is detailed below
Step 1: Fill in a Query Form
Fill up the Query Form and one of our counselor will call you & understand your eligibility.
Step 2: Get Shortlisted & Receive a Call
Our Admissions Committee will review your profile. Upon qualifying, an Email will be sent to you confirming your admission to the Program.
Step 3: Block your Seat & Begin the Prep Course
Block your seat with a payment of INR 10,000 to enroll into the program. Begin with your Prep course and start your Data Science journey!

Program Fee

No Cost EMI options are also available. *

What's Included in the Price

Features/Benefits
  • Industry recognized certificate from IBM
  • Access to real-life 30 industry projects
  • 3 Months online Internship part of the core curriculum

I’m interested in this program

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Career Impact

Over 500 Careers Transformed
Average Salary Hike
Highest Salary
Jobs Sourced
Hiring Partners

Frequently Ask Questions

Yes, you will get a certificate from DataTrained and IBM for the course completion as well as a project completion certificate from DataTrained.
There are two types of projects:

A. Practice projects: Your mentor will first do 2-3 projects for you and then you will do the next 3-4 projects wherein you will get help from your mentor and on tickets.

B. Evaluation projects: Once you’re done with the practice projects, you get access to the evaluation projects.
Data Science doesn’t need any previous technical or programming experience. We will teach you Math, Stats and programming at a very beginner level.
No, the program is designed in such a way that, you can continue with your job along with this program. It will be a mix of pre-recorded videos, live classes as well as printed study material. Every topic would be project-based and will be taught as per the live market scenario. The course module will be covered under the guidance of Industry Experts.
There are two training modes:

A. Self-paced: You will get access to DataTrained and IBM joint LMS wherein you will be assigned courses and projects. You will need to go through these courses and complete the projects as your own pace. Mentor support will be provided.

B. Blended: You will get access to DataTrained and IBM joint LMS wherein you will be assigned courses and projects. You will need to go through these courses and complete the projects as your own pace. In addition to these courses, live online classes are conducted on Saturdays and Sundays for you. Mentor support will be provided.
In case you miss a class, you need not to worry. All the live classes’ recordings will be available on your LMS. You can watch and practice the concepts at your own time.
We have partnered with analyticsjobs.in for the placement assistance for our learners who successfully completes our programs. Analytics Jobs is a leading media and job portal company specifically aimed for the jobs in Data Science, Analytics, Automation, RPA, Cloud, Block Chain and computer science.
The program fee is Rs. 9999 for self-paced and Rs. 14999 for self-paced and live sessions blended mode. For International students, the program fee is $170 plus taxes for self-paced.
For Queries and Suggestions

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