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Artificial Intelligence And Deep Learning Part 1

Learn Artificial Intelligence, Deep Learning, Tensorflow, Keras, Deep Neural Network, Computer Vision, Optimization algorithms
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Upto 50%  Discount on Early Admissions | EMI options Available | Decodr Edge (Learn Now, Pay Later)

What Will You Learn

You’ll learn Artificial Intelligence & Machine Learning technologies and applications including Machine Learning, Deep Learning, Computer Vision, Neural Network, TensorFlow Keras etc.
50 hours Instructor Led training with additional doubt clarification sessions every week.
You will create your GitHub repository and make all of your submissions on Github.
Online Test will be conducted to gauge progress

Learn First and Pay Later

First Time in India. Just invest time and pay after you get a job
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About This Program

The Artificial Intelligence and Deep Learning Part 1 is an online instructor program that will introduce you the core concepts and teach you the workings of applied Artificial Intelligence and deep learning. This program is laser-focused on teaching you practical, modern skills and tools that will take your career to the next level. The Program will prepare you for the role of a AI Scholar.

How This Program Works

Learn the latest skills in market

Our corporate partners are deeply involved in curriculum design ensuring that it meets the current industry requirements for data science professionals. Learn through real-life industry projects sponsored by top companies across industries

Network with your future employers

Learn LinkedIn Personal Branding & Image building to showcase your skills and talent. Build Network with industry leaders to build relationships and get opportunities. A portfolio is the #1 way to prove your skills and win the trust of employers… And as you complete those projects, you’ll be building your portfolio too.

Crack the interview

With Decodr’s Corporate Network and Career Services you Land your First job in Data Science.

Syllabus

Syllabus

Module
1
:
Introduction of Artificial Intelligence

●      What is Artificial Intelligence (AI)?

●      A broad overview of terms and technology

●      AI v/s Machine Learning v/s Deep Learning v/s Data Science

●      What has lead us to this point?

●      What are the predictions for the future?

●      Who should be involved in an AI project?

●      Examining team culture, capabilities and readiness

●      AI v/s Non AI

●      How to decide when to use capabilities of AI for business?

●      What are the 5 misconceptions regarding implementing emerging technologies?

●      How could AI impact on my business unit - both negatively and positively?

●      What happens to executives and businesses that misunderstand disruption?

●      AI - accelerating disruption: opportunities or crisis?

Module
2
:
AI application and Different

●      Banking/Finance

●      Robotics & Automation

●      Online Retails

●      Digital Marketing

●      Healthcare Sector

●      Human resources and recruiting

●      Online and telephone customer service

●      News, publishing and writing

●      Games or Entertainment

●      Personal Assistance

Module
3
:
Introduction to Machine Learning Approach

●      Artificial Intelligence & Machine Learning Introduction

●      What is Data Science?

●      Supervised & Unsupervised Learning

●      Reinforcement learning

●      Regression & Classification Problems

●      What makes a Machine Learning Expert?

Module
4
:
Introduction of Deep Learning

●      Deep Learning: A revolution in Artificial Intelligence

●      Limitations of Machine Learning

●      What is Deep Learning?

●      Advantage of Deep Learning over Machine learning

●      Real-Life use cases of Deep Learning

Module
5
:
Introduction to TensorFlow & keras

 ●      The Programming Model - Tensorflow

 ●      Data types, constant, Variable

 ●      Matrics operation and basic function

 ●      Optimization function in tensorboard

 ●      Understand basic concept of tensorflow

 ●      Machine learning function of tensorflow

 ●      Design different tensor

 ●      Introduction to tensorboard

 ●      Keras function using tensorflow

 ●      Working with Tensor board

Module
6
:
Project

●      Machine Learning algorithm using Tensorflow

●      Linear Regression – Insurance dataseS

●      Logistic Regression – Bank churn modelling dataset

Module
7
:
Artificial Neural Networks

●     Neurons, ANN & Working

●     Single Layer Perceptron Model

●      Multilayer Neural Network

●      Feed Forward Neural Network

●      Cost Function Formation

●      Applying Gradient Descent Algorithm

●      Backpropagation Algorithm & Mathematical Modelling

●      Programming Flow for backpropagation algorithm

Module
8
:
MNIST dataset- Image dataset Drug dataset

●      MNIST dataset- Image dataset

●      Drug dataset

Module
9
:
Deep Neural Network

●      Why Deep Networks

●      Why Deep Networks give better accuracy?

●      Use-Case Implementation on SONAR dataset

●      Understand How Deep Network Works?

●      How Back propagation Works?

●      Illustrate Forward pass, Backward pass

●      Different variants of Gradient Descent

●      Types of Deep Networks

●      Gradient Descent and Back propagation

Module
10
:
Computer Vision Image

●      Image formation and perception

●      Image representation

●      Image filtering: space- and frequency- domain filtering, linear and nonlinear filters Morphological image processing

●      Image geometric transformations, image registration.

●      Edge detection, image segmentation, active contours, level set methods

Module
11
:
Open-CV - Image Preprocessing

●      OpenCv - image read and write

●     OpenCv - video read and write

●     Draw different geometric shapes

●     Get the points where mouse is clicked

●     Write on each frame of Video

●     Playing with color

●     Various transformations

Module
12
:
Convolutional Neural Networks

●      CNN Architecture

●      Convolutional layer

●      Feature Extraction

●      Selection of filter

●      MaxPooling, dropout

●      Variants of the Basic Convolution Function

●      Efficient Convolution Algorithms

Module
13
:
Projects & Case Studies

●      X - Ray Dataset – Image classification

Module
14
:
Optimization algorithm

●      Optimizers

●      Gradient descent with momentum

●      RMSprop

●      Adam optimization algorithm

●      Other optimization algorithms

●      Hyper parameter tuning, Batch Normalization and

●      Programming Frameworks

●      Tuning process

●      Using an appropriate scale to pick

●      Hyperparameters

●      Normalizing activations in a network

●      Fitting Batch Norm into a neural network

●      Why does Batch Norm work?

●      Batch Norm at test time

●      Softmax Regression

●      Training a softmax classifier

Download Full Curriculum

Program Schedule

The Program Schedule will be updated soon

What Our Students Say About Us

"This course covers the machine learning ,python and statistical part which is back bone of data science which will definitely helping me in career growth."
BE, Computer Science
Saurabh Baliram Powar
"This course covers all the basics of Data Science and Machine Learning. The main feature I liked about this course is that we would be doing the industry level projects during the coursework. And that's the plus point. The course work helped me to clarify my basics about the subject and it helped me during my interview process. "
Master of Engineering, Automatic Control & Robotics
Jaymit Surve
"Decodr's course is helping to gather all the required skills to excel in this field by proper practice and giving an insight on how it is used in day-to-day world in an actual project."
Technical Associate, Genpact
Akshya Kumar Patel
"Decodr course is helping me to Get a wide knowledge of data science which is beneficial in my career growth and development."
MCA, Computer Science
Shrija Shweeta
" This course at Decodr is very good because it started from the scratch and include everything thing that a data scientist need to know. Now, I have hands on experience in python and I can use machine learning libraries to visualize. "
BE, Electronics Engineering
Sanjay Prasad
"I was thinking to switch my domain , Decodr's data science course has been really helpful throughout. It helped me to be confident to land a job in Data Science domain."
Network Technician, Vidini Technology
Subhajit Mondal

Mentors

Mentors

Aashish Pandey
Consultant & Trainer || Artificial Intelligence || Data Science || Deep Learning || Internet of Things

Training and Development,Technology Enthusiast with 8+ years of remarkable experience in multi-sector ranged domains of Data Science, Artificial Intelligence - Machine Learning - Deep Learning and Industry 4.0 who's greatly interested in challenging roles towards real-time solutions, Research and becoming a part of change-oriented end products or services while being a continuous learner, upgrading and applying to the best of Innovation resulting in qualitative productivity to Individuals and Industry.

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Amit Goyal
Team Lead - Data Analytics, Paytm

A wide variety of experience in Business Applications including Telecom, Finance, Supply Chain, Retail and Staffing industry.

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Arka Dey
Consultant, Advanced Analytics | Machine Learning on Cloud | CPG | Researcher in Applied Statistical Methods & NLP

Besides being a passionate researcher in his areas of interest, Arka takes up Data Science as a profession too. Academically, a Masters in Economics, he has been mostly working on and around several niche areas of Machine Learning, Econometric Modeling and Computational Linguistics (viz. NLP).

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Arpit Yadav
AIML Researcher, tensorbrew | Pursuing phd in Machine Learning | PGP AIML | Trainer in DS/AIML | Speaker | Blogger

I am working as Artificial intelligence and Machine Learning Researcher at tensorBrew, Hyderabad. I am also working as Freelancer Corporate Trainer in Python, Data Science, Machine Learning, Deep Learning, and Artificial Intelligence. I am currently pursuing Ph. D in Machine Learning from SVVV Indore.

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Govinda Bobade
Data Scientist | Trainer | Speaker | Blogger

10 years’ experience in IT and data analytics with multiple domains such as Finance, HR, IT Managed Services, Machine Data. An avid rational curiosity, and the ability to mine unseen gems located within large sets of data. Able to leverage a mathematics and applied statistics with visualization for exploration of data.

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Puneet Goyal
Consultant – Deal Advisory & Analytics, KPMG

Experienced Consultant with a demonstrated history of working in the management consulting industry. Skilled in Analytical Skills, Microsoft Word, Management, Management Information Systems (MIS), and Tableau.

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Saptarshi Ray
Data scientist

With more than 7 years​ of experience in data science with strong knowledge in statistical analysis, predictive modeling, machine learning and AI tools my passion and career lying side by side. It gives me immense pleasure to work with various data sets and building predicting models

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Shreyas Raghavan
Data Scientist, Dun & Bradstreet

Data Scientist | Machine Learning Engineer Part of team developing D&B Flagship projects on Risk Management. Whilst Working on projects involving D&B internal projects and their clients (Microsoft , T-Mobile , AT&T ).

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Smit Shah
AI Developer at Ample.ai

A Certified Data Scientist, with a demonstrated history of working in the information technology and services industry. Skilled in Data Science, Machine Learning, Deep Learning and Computer vision. Strong engineering professional with a Bachelor of Technology - BTech focused in Computer Science from SVKM's Narsee Monjee Institute of Management Studies (NMIMS).

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Anjali Batra
Principal Data Scientist, OpsMx

Management and Information Technology professional with 17 years of experience spanning across MNC’s, mid-level companies and startups

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Certification

Certificate of Completion

You can share your Course Certificates in the Certifications section of your LinkedIn profile, on printed resumes, CVs, or other documents.

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