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Artificial Intelligence And Deep Learning Part 2

Learn Generative Adversarial Networks, Transfer Learning , Tensorflow, Keras, Natural Language Processing, Vectorization, Production and Deployment strategies – AI Model
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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 Generative Adversarial Networks, Transfer Learning , Tensorflow, Keras, Natural Language Processing, Vectorization, Production and Deployment strategies – AI Model , 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 2 is an online instructor program that will teach you the advanced concepts and teach you the implementation 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 Specialist.

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
:
Generative Adversarial Networks(GANs)

●      Introduction to GANs

●      Application of GANs

●      Understand working and architecture

●      Challenges with GANs

●      Use case and Project

Module
2
:
Project

●      Face Synthesis

Module
3
:
Restricted Boltzmann Machine (RBM) and Autoencoders

●      Restricted Boltzmann Machine

●      Applications of RBM

●      Collaborative Filtering with RBM

●      Introduction to Autoencoders

●      Autoencoders applications

●      Understanding Autoencoders

●      Building a Autoencoder model for classification of handwritten images extracted from the MNIST Dataset

Module
4
:
Project

●      Dimension Reduction

Module
5
:
Transfer Learning

·      Introduction and Hyperparameter tuning

·      VGG16/19

·      MobileNet

·      YOLO

·      SSD

Module
6
:
Project

●      Pattern Recognition

●      Image Classification

●      Object Classification and Detection

●      Image Segmentation

Module
7
:
Natural Language Processing Introduction

●      Natural Language Understanding

●      Text Understanding

●      Semantic, Syntactic and Discourse Planning

●      Natural Language Generation

Module
8
:
NLP – Text Preprocessing

●      Working with regular expressions

●      Removing unwanted tokens

●      Spelling correction

●      Dictionary Filtering

●      Word and Sentence Tokenization

●      Stemming and Lemmatization

●      POS Tagging

●      Text Vectorization

●      Frequency based Vectorization -Count Vectorizer, TF-IDF and Co-occurrence

Module
9
:
Vectorization

●      Prediction based Embedding Techniques

●      Word2Vec, Fast Text and Glove

●      Topic Modelling

●      Unigram and Bigram Text Analysis

Module
10
:
Recurrent and Recursive Nets

●      Basic concepts of RNN

●      Unfolding Recurrent Neural Networks

●     The Vanishing Gradient Problem

●      LSTM Networks

●     Different Gate

●      Recursive Neural Networks

●     Deep Belief Networks

●     Concept and methods

●     Time Series Analysis

Module
11
:
Projects & Case Studies

●      Text Classification

●      Sentiment Analysis

●      Sorting customer feedback

●      Automating processes in customer support

●      Chatbots for customer success

●      Machine translation

●      Natural language generation

Module
12
:
Production and Deployment strategies – AI Model

●      An Executive’s Guide to Code

●      AI platforms explored

●      APIs examined

●      Machine learning models as services

●      Deployment with Flask

         o  Creating a sample web app with flask

         o  Creating Request response interface

         o  Integrating with a ML model

         o  Connecting to web server using postman

         o  Building the frontend interface via JS and integrating with Flask webserver

●      Best Practices for API design for ML services

●      Deploying model with nginx and uWSGI – demo

●      Deployment with AWS Cloud

         o  Working with AWS Sagemaker Cloud

         o  Prepare Data and Train the model

         o  Deploy the model and terminate resources

●      Machine Learning and DevOps

●      Containerizing models

         o  Building Docker images with docker files

         o  Example Docker Build Process

         o  Using Docker registries to manage images

●      Defining scalability

●      Tools and techniques for scalable machine learning

●      Architecture design patterns for scalable systems

●      Kubernetes Overview

●      Best Practices of scaling machine learning models

●      Finish off experiments

●      Review of what has been taught

●      Get individuals to create their own action list

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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₹ 6000 (Registration fees)

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