What you'll learn

  • Python
  • Numpy
  • Pandas
  • Statistics
  • Data analysis
  • Deep learning
  • CNN, RNN,LSTM, GAN
  • Deployment in Google coral & Nvidia JetsNano

Why Learn Deep Learning Masters At iNeuron?

iNeuron is a product-driven organization carrying ample experience in deep learning projects that it has successfully delivered to its clients domestically as well as internationally, thus we have the capabilities and experience to deliver high-quality education along with live-project facilities that can help you build a lucrative career in Deep Learning.

  • Students:1400+
  • Duration:4 months
  • Major Projects:20
  • Minor Projects:10
  • Mode:Online
  • Job Assistence:100%
  • Certificate:Yes
  • Mock Interviews:Yes

Course Curriculum

  • Introduction of Deep Learning and its application in Day to Day life
  • Course overview and Dashboard description

  • Introduction to python and comparison with other programming language
  • Installation of Anaconda Distribution and other python IDE
  • Python Objects,Numbers & Booleans, Strings,Container objects, Mutability of objects
  • Operators – Arithmetic,Bitwise,comparison and Assignment operators,Operators Precedence and associativity
  • Conditions(If else,if-elif)
  • Loops(While ,For)
  • Break and Continue statements
  • Range functions

  • String object basics
  • String methods
  • Splitting and Joining
  • Strings String format functions
  • List object basics
  • List methods
  • List as stack and Queues
  • List comprehensions

  • Tuples, Sets, Dictionary Object basics,Dictionary Object methods,
  • Dictionary View Objects.
  • Functions basics,Parameter passing & Iterators
  • Generator functions
  • Lambda functions
  • Map, Reduce, Filter functions

  • Creating classes and Objects
  • Inheritance,Multiple Inheritance
  • Working with files
  • Reading and writing files
  • Buffered read and write
  • Other File methods

  • Creating new modules
  • Exceptions Handling with Try-except
  • Creating ,inserting and retrieving Table
  • Updating and deleting the data.

  • Flask introduction
  • Flask Application
  • Open link Flask
  • App Route Flask
  • URL Building Flask
  • HTTP Methods Flask
  • Templates Flask
  • Django end to end

  • Matplotlib
  • Seaborn
  • Plotly
  • Cuflinks

  • Mongo DB
  • SQL lite
  • python SQL

  • Web crawlers for image data sentiment analysis and product review sentiment analysis
  • Integration with web portal
  • Integration with rest api ,web portal and mongodb on Azure
  • Deployment on web portal on Azure
  • Text mining
  • Social media data churn

  • Python Pandas – Series
  • Python Pandas – DataFrame
  • Python Pandas – Panel
  • Python Pandas – Basic Functionality
  • Descriptive Statistics
  • Function Application
  • Python Pandas – Reindexing
  • Python Pandas – Iteration
  • Python Pandas – Sorting
  • Working with Text Data
  • Options & Customization
  • Indexing & Selecting Data
  • Statistical Functions
  • Python Pandas – Window Functions
  • Python Pandas – Date Functionality
  • Python Pandas – Timedelta
  • Python Pandas – Categorical Data
  • Python Pandas – Visualization
  • Python Pandas – IO Tools

  • NumPy – Ndarray Object
  • NumPy – Data Types
  • NumPy – Array Attributes
  • NumPy – Array Creation Routines
  • NumPy – Array from Existing Data
  • Array From Numerical Ranges
  • NumPy – Indexing & Slicing
  • NumPy – Advanced Indexing
  • NumPy – Broadcasting
  • NumPy – Iterating Over Array
  • NumPy – Array Manipulation
  • NumPy – Binary Operators
  • NumPy – String Functions
  • NumPy – Mathematical Functions
  • NumPy – Arithmetic Operations
  • NumPy – Statistical Functions
  • Sort, Search & Counting Functions
  • NumPy – Byte Swapping
  • NumPy – Copies & Views
  • NumPy – Matrix Library
  • NumPy – Linear Algebra

  • Feature_Engineering and Selection
  • Building Tuning and Deploying Models
  • Analyzing Bike Sharing Trends
  • Analyzing Movie Reviews Sentiment
  • Customer Segmentation and Effective Cross Selling
  • Analyzing Wine Types and Quality
  • Analyzing Music Trends and Recommendations
  • Forecasting Stock and Commodity Prices

  • Descriptive Statistics
  • Sample vs Population statistics
  • Random Variables
  • Probability distribution function
  • Expected value
  • Binomial Distribution
  • Normal Distributions
  • Z-score
  • Central limit Theorem
  • Hypothesis testing
  • Z-Stats vs T-stats
  • Type 1 type 2 error
  • Confidence interval
  • Chi-Square test
  • ANOVA test
  • F-stats

  • Basic of Neural Network
  • Type of NN
  • Cost Function
  • Gradient descent
  • Linear Algebra basics
  • Vanilla implementation of Neural Network in python
  • Tensorflow In depth
  • Hands on Simple NN with Tensorflow
  • Word Embedding
  • CBOW, Skip-gram
  • Word Relations
  • Hands on word2vec

  • Convolutional Neural Network
  • Maxpool, Window padding
  • Hands On
  • Image classification using Convolutional Neural Network
  • Recurrent Neural Network
  • Long Short Term Memory (LSTM) architecture
  • Building Story writer using character level RNN
  • Sentiment Analysis Hands on
  • Hands on embedding + RNN
  • Seq-to-Seq model
  • Hands on translation
  • Encoder Decoder
  • Hands on cleaning images

  • GAN
  • Generative Model Using GAN
  • BERT
  • Semi-supervised learning using GAN
  • Restricted Boltzmann Machine(RBM) and Autoencoders
  • CNN Architectures
  • LeNet-5
  • AlexNet
  • GoogLeNet
  • VGGNet
  • ResNet
  • SSD
  • SSD lite
  • Faster R CNN

  • SCNN
  • Masked R-CNN
  • Xception
  • SENet
  • Facenet
  • Implementing a ResNet-34 CNN Using Keras
  • Using Pretrained Models From Keras
  • Pretrained Models for Transfer Learning
  • Classification and Localization
  • Tensorflow Object Detection
  • You Only Look Once (YOLO)
  • Semantic Segmentation

  • Masked R-CNN
  • Xception
  • SENet
  • Facenet
  • Implementing a ResNet-34 CNN using Keras
  • Using Pretrained Models From Keras
  • Pretrained Models for Transfer Learning
  • Classification and Localization
  • Tensorflow object Detection
  • You Only Look Once(YOLO)
  • Semantic Segmentaion
  • Semi-supervised learning GAN

End to end Scenario based Interview preparation for every individual resume discussion.

  • One to one resume Discussion with project, technology and Experience.
  • Mock interview for every students multiple rounds

Projects

  • Case Study: Spam Detection
  • Case Study : Anomaly Detection
  • Case Study: Image Classification
  • Case Study : Prediction of lungs Disease
  • Case Study : Google and Microsoft speech and vision API integration
  • Case Study: Translation model for languages
  • Image Classification
  • Image Segmentation/Object Detection

  • Face Recognition
  • Clinical Diagnostics: Image Identification, classification & segmentation.
  • Music/Audio Recommendation Systems
  • Style Transfer

  • Statistical Project
  • Traffic Surveillance System
  • Object Identification
  • Object Tracking
  • Object Classification
  • Tensorflow Object Detection
  • Image to Text processing
  • Speech to Speech analysis
  • Vision Based Attendance System
  • Vision Based Sentiment Analysis
  • Raspberry pi Integration
  • Azure cloud Integration Deployment in ML devOps pipeline
  • Autonomous Vehicle
  • Custom Object training using TFOD
  • Truck licence plate detection and its integration with IP camera
  • End to end cloud Deployment of computer vision
  • Machine learning and NLP project

  • Hardware Architecture
  • Coral Requirements
  • End to End Coral Setup
  • Deploying Models in Edge TPU
  • Pose Estimation using Coral
  • Hand Detection Using Coral
  • Face Detection Using Coral
  • Music Generation Using Pose and Action

  • Hardware Architecture
  • JetsNano Requirements
  • End to End JetsNano Setup
  • Deploying Models in Edge TPU
  • Pose Estimation using JetsNano
  • Hand Detection Using JetsNano
  • Face Detection Using JetsNano
  • Music Generation Using Pose and Action

Batch Timings & Fee

Fee Structure

₹3,540

incl. GST
Online

Start Date : 28th Mar 2020

Sat & Sun: 10.00 AM - 12.00 PM

Thu(Doubt Clearing): 10.00 PM - 12.00 AM

Deep Learning Masters from iNeuron

Complete your Deep learning at iNeuron and get your certificate.

  • 3 Months live session training
  • Placement Assistance
  • 1 Months in-house internship
Certificate

Our Features

3 Months Classroom Training

Once on-board our candidates will go through an intense classroom training session of 3 months conducted by our best team of experienced senior data scientists, who will provide all conceptual knowledge in an innovative as well as an interactive manner.

Career Counselling

After successful completion of our course, we train our candidates via mock interviews, personal interviews, and group discussions as well as provide them with professional mentoring and help them build an attractive resume which will enable them to fetch a lucrative job.

1 Months Of In-House Projects

What makes us different from other training institutes is that we are also into product development and that enables us to provide hands-on experience to our candidates to contribute in live projects, which will result in a deeper understanding of the course with industry-level knowledge.

Admission Process

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