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IT Expert Training Program

.NET Full Stack

Duration:40HRS
  1. Basic Data Structure – Variable, Array, List, Dictionary
  2. OOPS concepts – Basic, Advanced
  3. Web Framework – Routes, Rendering, Filtering, Bundling
  4. .NET MVC – Model, View, Controller
  5. Rendering – HTML5, Razor View, CSS3, Scripts
  6. SQL Server 2014 – Query, Stored Proc, Function, Trigger
  7. Data Set, Data Table, ADO.NET 8.Entity Framework, LINQ
  8. JavaScript, JSON , Async Calls, Callbacks
  9. jQuery, AJAX Calls
  10. Responsive UI - Bootstrap
  11. WebAPI, Postman tool

MERN Full Stack

Duration:32HRS
  1. JavaScript, JSON
  2. jQuery, AJAX Calls
  3. NodeJS – Console application
  4. NodeJS – Event, Socket Programming
  5. NodeJS – Web Framework
  6. PUG template
  7. WebAPI, Postman tool
  8. Angular 6 / ReactJS
  9. Redux
  10. Connection to MongoDB/Firebase Cloud Database
  11. Deployment in to Azure

Artificial Intelligence

Duration:40HRS
  1. Intro - Artificial Intelligence, Data Science
  2. Azure Cognitive APIs - .NET Implementation
  3. Python Programming - Basics, Advanced
  4. Python Programming – Libraries, Numpy, MatplotLib, Pandas
  5. Machine Learning Algorithms – Overview
  6. Supervised, Unsupervised Learning
  7. Python Project – Linear Regression
  8. Python Project - Face Identification
  9. Chatbots : Dialogflow – NLP, Channels Integration

Machine Learning

Duration:32HRS
  1. Intro - Artificial Intelligence, Data Science
  2. Python Programming – Basics, Adv., Libraries, Environment (Project)
  3. Python Web Framework – Flask, Jinja (Project)
  4. Data Analytics: Python – Cleaning, Visualization
  5. Machine Learning Algorithms Fundamental
  6. Data Preparation, Visualization, Analytics
  7. Algorithm Essentials – Statistics, Validation, Tuning
  1. Supervised Learning – Linear, Logistic, Decision Tree/Forest, NB, PCA
  2. Unsupervised Learning – K-Means, KNN, SVM,
  3. Python Project - Face Recognition
  4. Project 1 : Python – Face Identification (Project)
  5. Project 2 : Python – Retail Domain : Targeted Marketing (Project)
  6. Project 3 : Python – Entertainment: Recommendations (Project)

Code on Cloud

Duration:40HRS
  1. Intro to Cloud – Azure, Environment
  2. Public, Private, Hybrid, IaaS, PaaS, SaaS, FaaS
  3. Web App - Deployment, App Insights, Diagnostics, logs, Kudu
  4. Serverless Computing – Function App
  5. Storage – Blob, Queues, Table, Files, Disk, Data Lake Storage
  6. Service Bus – Queue, Topic, Relay
  7. Azure SQL – Configure, Connect, Execute through .NET
  8. Configure and deploy Web Jobs, Functions App, Logic Apps
  9. Cosmos DB – concepts, SQL API, Mongo API, Table API
  10. Developer tools - Virtual Machine, DSVM, CLI, SDK
  11. Pricing, Scaling, Reliability Comparison

Deep Learning

Duration:32HRS
  1. Azure Cognitive APIs – Face, Vision, Speech
  2. Azure ML Studio – Model Creation, Deployment, Leveraging
  3. Neural Networks, Deep Learning
  4. TensorFlow : CNN, RNN (Project)
  5. Dynamic Memory Networks, LSTMs
  6. Project 1 : TensorFlow – Prediction Case (Project)
  7. Project 2 : TensorFlow – Image Classification (Project)
  8. Python – Flask API : Model Creation, Model Deployment

Chat Bot Specialization

Duration:32HRS
Dialogflow Chatbots:
  1. NLP – Intent, Entity, Parameter
  2. Fulfillment – Code in NodeJS, API calls
  3. Integration – Web, Google Assistant, Google Home, Facebook
  4. Rich response, Helper Modules, Storage, Authorization
  5. Pricing Tiers, Scalability
Alexa Skill Kit Chatbots:
  1. NLP – Intent, Entity, Slot
  2. Fulfillment – Code in NodeJS, API calls
  3. Integration – Alexa Echo
Azure Bot Service:
  1. LUIS – Intent, Entity, Parameter
  2. Handlers – Code in C#, API calls, Speech Enabled
  3. Simple Bot, Form Bot, LUIS Bot, QnA Bot, Proactive Bot
  4. Integration – Web, Skype, Facebook Rich response, Storage,
  5. Authorization, Message Wrappers
  6. Multi Dialogs, Call, Forward
  7. Global Handlers, Intercept, Backchannel Mechanism
  8. Pricing Tiers, Scalability

Certification Course In Hadoop

Module 1 - Introduction to Big Data and Hadoop
  1. What is Hadoop?
  2. What is Big data?
  3. What comes under big data?
  4. What are the challenges for processing big data?
  5. Traditional Approach and its Limitation
  6. What are the benefits of big data?
  7. What technologies support big data?
  8. Solution of big data
  9. Hadoop Architecture
  10. Advantages of Hadoop
Module 2 – HDFS
  1. What is HDFS
  2. Where to use HDFS
  3. Where not to use HDFS
  4. Features of HDFS
  5. HDFS Architecture
  6. HDFS Concepts
  7. HDFS Architecture 1.x and its daemons
  8. HDFS Architecture 2.x and its daemons
  9. HDFS Federation
  10. HDFS High availability
  11. Scheduler
  12. Rack Awareness
  13. HDFS commands
Module 3- Understanding - Map-Reduce Basics
  1. What is MapReduce
  2. Why MapReduce
  3. How MapReduce work
  4. Partitioners
  5. Combiners
  6. Hadoop Streaming
  7. Failures in MapReduce
Module 4- YARN : Yet Another Resource Negotiator
  1. Introduction to YARN
  2. Limitation of Current Architecture
  3. Apache Hadoop Yarn Concepts & Applications
  4. JobSubmission and Job Initialization
  5. Failure Handling in YARN
  6. Task Failure
  7. Application Master Failure
  8. Node Manager Failure
  9. Resource Manager Failure
Module 5 – HIVE
  1. What is hive
  2. Features of Hive
  3. Architecture of Hive
  4. Working of Hive
  5. What is Schema on Write?
  6. What is Schema on Read?
  7. Advantages of Schema on Write
  8. Advantages of Schema on Read
  9. Disadvantages of Schema on Write
  10. Disadvantages of Schema on Read
  11. Hive datatypes
  12. Hive Statements
Module 6 – PIG
  1. What is pig?
  2. Why Do We Need Apache Pig?
  3. Features of Pig
  4. Pig Architecture
  5. Apache Pig Vs MapReduce
  6. Apache Pig Vs SQL
  7. Apache Pig Vs Hive
  8. pig run modes
  9. Pig latin concepts
  10. Pig Data Types
  11. Pig operators
Module 7 – SQOOP
  1. Introduction
  2. Working of sqoop
  3. Sqoop Commands
Module 8 – FLUME
  1. Apache Flume - Introduction
  2. Applications of Flume
  3. Advantages of Flume
  4. Features of Flume
  5. Apache Flume - Data Transfer In Hadoop
  6. Apache Flume - Architecture
  7. Apache Flume - Data Flow
  8. Apache Flume - Sequence Generator Source
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