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IT Expert Training Program
.NET Full Stack
Duration:40HRS- Basic Data Structure – Variable, Array, List, Dictionary
- OOPS concepts – Basic, Advanced
- Web Framework – Routes, Rendering, Filtering, Bundling
- .NET MVC – Model, View, Controller
- Rendering – HTML5, Razor View, CSS3, Scripts
- SQL Server 2014 – Query, Stored Proc, Function, Trigger
- Data Set, Data Table, ADO.NET 8.Entity Framework, LINQ
- JavaScript, JSON , Async Calls, Callbacks
- jQuery, AJAX Calls
- Responsive UI - Bootstrap
- WebAPI, Postman tool
MERN Full Stack
Duration:32HRS- JavaScript, JSON
- jQuery, AJAX Calls
- NodeJS – Console application
- NodeJS – Event, Socket Programming
- NodeJS – Web Framework
- PUG template
- WebAPI, Postman tool
- Angular 6 / ReactJS
- Redux
- Connection to MongoDB/Firebase Cloud Database
- Deployment in to Azure
Artificial Intelligence
Duration:40HRS- Intro - Artificial Intelligence, Data Science
- Azure Cognitive APIs - .NET Implementation
- Python Programming - Basics, Advanced
- Python Programming – Libraries, Numpy, MatplotLib, Pandas
- Machine Learning Algorithms – Overview
- Supervised, Unsupervised Learning
- Python Project – Linear Regression
- Python Project - Face Identification
- Chatbots : Dialogflow – NLP, Channels Integration
Machine Learning
Duration:32HRS- Intro - Artificial Intelligence, Data Science
- Python Programming – Basics, Adv., Libraries, Environment (Project)
- Python Web Framework – Flask, Jinja (Project)
- Data Analytics: Python – Cleaning, Visualization
- Machine Learning Algorithms Fundamental
- Data Preparation, Visualization, Analytics
- Algorithm Essentials – Statistics, Validation, Tuning
- Supervised Learning – Linear, Logistic, Decision Tree/Forest, NB, PCA
- Unsupervised Learning – K-Means, KNN, SVM,
- Python Project - Face Recognition
- Project 1 : Python – Face Identification (Project)
- Project 2 : Python – Retail Domain : Targeted Marketing (Project)
- Project 3 : Python – Entertainment: Recommendations (Project)
Code on Cloud
Duration:40HRS- Intro to Cloud – Azure, Environment
- Public, Private, Hybrid, IaaS, PaaS, SaaS, FaaS
- Web App - Deployment, App Insights, Diagnostics, logs, Kudu
- Serverless Computing – Function App
- Storage – Blob, Queues, Table, Files, Disk, Data Lake Storage
- Service Bus – Queue, Topic, Relay
- Azure SQL – Configure, Connect, Execute through .NET
- Configure and deploy Web Jobs, Functions App, Logic Apps
- Cosmos DB – concepts, SQL API, Mongo API, Table API
- Developer tools - Virtual Machine, DSVM, CLI, SDK
- Pricing, Scaling, Reliability Comparison
Deep Learning
Duration:32HRS- Azure Cognitive APIs – Face, Vision, Speech
- Azure ML Studio – Model Creation, Deployment, Leveraging
- Neural Networks, Deep Learning
- TensorFlow : CNN, RNN (Project)
- Dynamic Memory Networks, LSTMs
- Project 1 : TensorFlow – Prediction Case (Project)
- Project 2 : TensorFlow – Image Classification (Project)
- Python – Flask API : Model Creation, Model Deployment
Chat Bot Specialization
Duration:32HRSDialogflow Chatbots:
- NLP – Intent, Entity, Parameter
- Fulfillment – Code in NodeJS, API calls
- Integration – Web, Google Assistant, Google Home, Facebook
- Rich response, Helper Modules, Storage, Authorization
- Pricing Tiers, Scalability
- NLP – Intent, Entity, Slot
- Fulfillment – Code in NodeJS, API calls
- Integration – Alexa Echo
Azure Bot Service:
- LUIS – Intent, Entity, Parameter
- Handlers – Code in C#, API calls, Speech Enabled
- Simple Bot, Form Bot, LUIS Bot, QnA Bot, Proactive Bot
- Integration – Web, Skype, Facebook Rich response, Storage,
- Authorization, Message Wrappers
- Multi Dialogs, Call, Forward
- Global Handlers, Intercept, Backchannel Mechanism
- Pricing Tiers, Scalability
Certification Course In Hadoop
Module 1 - Introduction to Big Data and Hadoop
- What is Hadoop?
- What is Big data?
- What comes under big data?
- What are the challenges for processing big data?
- Traditional Approach and its Limitation
- What are the benefits of big data?
- What technologies support big data?
- Solution of big data
- Hadoop Architecture
- Advantages of Hadoop
Module 2 – HDFS
- What is HDFS
- Where to use HDFS
- Where not to use HDFS
- Features of HDFS
- HDFS Architecture
- HDFS Concepts
- HDFS Architecture 1.x and its daemons
- HDFS Architecture 2.x and its daemons
- HDFS Federation
- HDFS High availability
- Scheduler
- Rack Awareness
- HDFS commands
Module 3- Understanding - Map-Reduce Basics
- What is MapReduce
- Why MapReduce
- How MapReduce work
- Partitioners
- Combiners
- Hadoop Streaming
- Failures in MapReduce
- Introduction to YARN
- Limitation of Current Architecture
- Apache Hadoop Yarn Concepts & Applications
- JobSubmission and Job Initialization
- Failure Handling in YARN
- Task Failure
- Application Master Failure
- Node Manager Failure
- Resource Manager Failure
Module 5 – HIVE
- What is hive
- Features of Hive
- Architecture of Hive
- Working of Hive
- What is Schema on Write?
- What is Schema on Read?
- Advantages of Schema on Write
- Advantages of Schema on Read
- Disadvantages of Schema on Write
- Disadvantages of Schema on Read
- Hive datatypes
- Hive Statements
- What is pig?
- Why Do We Need Apache Pig?
- Features of Pig
- Pig Architecture
- Apache Pig Vs MapReduce
- Apache Pig Vs SQL
- Apache Pig Vs Hive
- pig run modes
- Pig latin concepts
- Pig Data Types
- Pig operators
Module 7 – SQOOP
- Introduction
- Working of sqoop
- Sqoop Commands
- Apache Flume - Introduction
- Applications of Flume
- Advantages of Flume
- Features of Flume
- Apache Flume - Data Transfer In Hadoop
- Apache Flume - Architecture
- Apache Flume - Data Flow
- Apache Flume - Sequence Generator Source