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Summer School

Globsyn, Summer School began in 2004, in response to the demand for professionally driven technology program tracks. Held during the summer vacations, each program track is designed keeping in view the latest industry trends and needs – making it a one-of-its-kind ‘industry readiness’ program.

Globsyn Summer School encourages engineering students to utilize their summer vacations by learning and developing their IT skills, gearing them for their future IT careers. Projects done during summer school are recognized by WBUT as part of the vocational training mandate.

Program Highlights

  • Training faculty accredited by global IT giants like IBM, CapGemini, CTS, Siemens, TCS, Tech-Mahindra, Wipro, R S Software etc.
  • In-depth theoretical grooming to build up developmental competency.
  • The Project Report is recognized by WBUT as part of the Vocational Training mandate.
  • Special Soft Skills classes with emphasis on facing Personal Interviews for placement.
  • Participation and project certificate for all successful candidates.
  • Projects similar to real-life applications.
  • Formal Project Evaluation by Technical panel.

Technology Tracks

Data is key to every decision making. Efficient processing of data gives trends , hidden pattern along with many other aspects and all of them have immense importance for a business organization to strategize , positioning etc . Larger the amount of data better the result . Not so long back access to large amount of data was very difficult. But today due our access to the Internet and cheap sensors it is possible to access very high volume of data so large that requires thousands of computer to store and process them . These data are not only very large but also unstructured . These are commonly referred to as BigData. Traditional data processing technologies are incapable of handling such large volume of data. Hadoop is solution to this problem. Hadoop is an open-source software framework for storing data and running applications on clusters of commodity hardware. It provides massive storage for any kind of data, enormous processing power and the ability to handle virtually limitless
concurrent tasks or jobs.

Pre-requisite of the course

  • Knowledge of programming using JAVA, SQL

Curriculum

  • Necessary Java Knowledge for Hadoop
  • Introduction to BigData and Hadoop
  • HDFS
  • Introduction to MapReduce
  • Pig
  • Hive
  • NOSQL Database Management using HBASE
  • Project

At the end of this course, participants will be able to develop advanced ASP.NET MVC applications using .NET Framework tools and technologies. The focus will be on coding activities that enhance the performance and scalability of a web application. ASP.NET MVC will be introduced and compared with Web Forms so that participants know when each should/could be used. This course will also prepare the participants for Microsoft certification exam 70-486.

Pre-requisite of the Course

  • Knowledge of programming using C

Curriculum

  • Collections, Generic collections
  • Introduction to ASP.NET
  • ADO.NET and database connection
  • Lambda expression, LINQ concepts
  • LINQ To Objects. Linq To SQL, LINQ to XML
  • CRUD operations using MS SQLServer DB
  • HTML 5
  • CSS3
  • Jquery
  • MVC Architecture
  • Routing in MVC
  • Controller, Action Method/Selectors, ActionVerbs
  • Model Binding and validation
  • Layout view and other views.
  • Filters and action filters
  • Authorization and Authentication in MVC
  • Windows Communication Foundation (WCF) overview
  • JSON v/s XML
  • Web API, Integration with Web Services
  • Entity Framework
  • Project

The key advantage of machine learning is that it enables computers to access hidden
insights, finding patterns that can either be used by researchers to find unknown patterns (as
might be used for movie recommendation) or by businesses to find insights into customer
behaviour or to target potential new consumers. Machine learning not only helps find things
that people may not, it also does what people do far more quickly. Machine learning
algorithms tend to operate at expedited levels. Machine learning is a method of data
analysis that automates analytical model building. It is a branch of artificial intelligence based
on the idea that systems can learn from data, identify patterns and make decisions with
minimal human intervention.

Pre-requisite of the course

  • Good knowledge at algorithms development
  • Basic knowledge of statistics and conditional probability
  • Understanding of linear algebra: vector operations, matrix operation

Curriculum

  • Getting started with Python
  • Working with NumPy
  • Non Parametric classification with K nearest neighbor
  • Baysian Classification with Naive Bayes
  • Predicting numeric data using Regression
  • Making model simple using Dimensionality Reduction
  • K-Means Clustering
  • Project

Cloud computing facilitates success of an enterprise where AWS is the frequently used cloud tool. Most enterprises leverages AWS that can be best customized to fit their IT environment. The reputed players like Netflix, Reddit, Expedia and even NASA run their applications on AWS. The program will enable a computer science graduates to understand various aspects of AWS in terms of its Architecture, Services and Applications. After attending this course, a fresher becomes more relevant not only to the IT industry but other sectors also.

Pre-requisite of the Course

  • Knowledge of programming knowledge using C

Curriculum

  • Fundamentals of Cloud Computing
  • Cloud Infrastructure and Cloud Advantage
  • Azure Fundamentals
  • Overview of all Azure Services
  • Azure Storage
  • Storage Account Rep
  • Fundamentals of Cloud Computing
  • Cloud Infrastructure and Cloud Advantage
  • Azure Fundamentals
  • Overview of all Azure Services
  • Azure Storage
  • Storage Account Replication Techniques: LRS, ZRS, GRS & RA-GRS
  • Azure Virtual Network
  • Architectural difference between Azure VPNs like VNET to VNET, point-to-site and site-to-site.
  • Azure Virtual Machines
  • Understanding concepts of: Load Balancing, Availability Set and Auto Scaling
  • Azure Web Apps
  • Resource Group and App Service Plans
  • Azure SQL Database
  • Advance Capabilities
  • lication Techniques: LRS, ZRS, GRS & RA-GRS
  • Azure Virtual Network
  • Architectural difference between Azure VPNs like VNET to VNET, point-to-site and site-to-site.
  • Azure Virtual Machines
  • Understanding concepts of: Load Balancing, Availability Set and Auto Scaling
  • Azure Web Apps
  • Resource Group and App Service Plans
  • Azure SQL Database
  • Advance Capabilities
  • Project

According to StatCounter, market share of Android is 76.61 %. At the same time number of people using smartphone to theirs day to day work is increasing. It is expected to reach 2.7 billion by 2019. These fact underlines the importance of Android App Development as any business organization will try reach customer through Android powered app. This course will take the students through the various intricacies of Android App Development using Studio 3.

Pre-requisite of the Course

  • Knowledge in JAVA & SQL is essential for the course

Curriculum

  • Revising Java
  • Android Architecture
  • Developing a simple Activity
  • Android Intents
  • Android Menu
  • Activity lifecycle
  • Fragments
  • List View
  • Material Design Controls
  • Thread
  • Service
  • Broadcast Receiver
  • Notification
  • Location  and Google Map
  • Firebase
  • Project
  • Collection Framework
  • JDBC
  • HTML
  • Intro to JEE Framework
  • Different types of modules in JEE
  • Introduction to HTTP
  • Introduction to Servlet
  • Request forwarding
  • Java Server Pages
  • Session Handling
  • MVC
  • Introduction to Apache Struts2
  • Building a simple struts App
  • Core Struts Controller concepts
  • Building Struts views
  • Working with Struts Models
  • Pulling it all together
  • Project
  • IOT system architecture
  • IOT Phy connectivity
  • Shot, Medium, Long range wireless
  • IOT Networking
  • IOT Security
  • Project
  • Significance of BigData
  • Hadoop Architecture
  • HDFS
  • MapReduce
  • Implementing Mapper, Reducer, Combiner, Partitioner
  • Pig and PigLatin
  • Hive
  • Project
  • Introduction to Web Development
  • xHTML Basics
  • Introduction to CSS
  • Introduction to JavaScript
  • Introduction to PHP
  • PHP Control Structure
  • Functions in PHP
  • Sessions and Cookies in PHP
  • File Handling using PHP
  • Object Oriented Programming Using PHP
  • MySQL Database handling using PHP
  • Implementing Security

It is almost impossible to escape the impact frontier technologies are having on everyday life.
At the core of this impact are the advancements of artificial intelligence and deep learning.
These technologies are ushering in a revolution that will fundamentally alter the way we live,
work, and communicate akin to the industrial revolution – more specifically, AI & Deep
Learning is the new industrial revolution. Companies across industries seek to use advanced
computational techniques to find useful information hidden across huge swaths of data.
While the field of artificial intelligence is decades old, breakthroughs in the field of artificial
neural networks(ANN) are driving the explosion of deep learning.

Pre-requisite of the Course

  • Knowledge of python programming
  • Knowledge of Machine Learning
  1. Concept of Overfit, Underfit, Training and Test Set
  2. Regression, Classification

Curriculum

  • Understanding Deep Learning
  • Understanding Neural Network and TensorFlow
  • Deep dive into Neural Networks and TensorFlow
  • Convutionsl Neural Network
  • Recurrent Neural Network
  • Restricted Boltzmann Machine RBM and Autoencoders
  • Keras
  • Tflearn
  • Project
  • Getting started with Java
  • DataTypes and Operators
  • Classes in Java
  • Access Modifiers
  • Method Overloading and Constructor
  • Arrays in java
  • Inheritance in Java
  • Packages in Java
  • Exceptions and Error Handling
  • Multi Threaded Programming in Java
  • Java Swing
  • Input and Output Streams
  • Collections
  • Event Handling
  • Generics and Collections
  • Simulation of Compouter Networks
  • Introduction to NS2
  • Linkage between OTcl and C++ in NS2
  • Implementation of discrete event simulation in NS2
  • Network objects: Creation, Configuration and Packet forwarding
  • Nodes as Routers and Computer hosts
  • Link and Buffer Management
  • Packets, packet headers, and header format
  • Developing new modules for NS2
  • Project
  • Overview of Database Management and Architecture
  • Introduction to Relational Databases
  • Entity-Relationship Model
  • Introduction to Oracle and SQL*PLUS Fundamentals
  • Retrieving Data Using SQL ?Overview (Select Command)
  • Joining of Tables and Sub query
  • Data Manipulation Language  and Set operators
  • DDL Commands and other Oracle objects
  • Introduction to PL/SQL
  • Cursors
  • SubPrograms
  • Packages
  • Database Triggers
  • Introduction to oracle forms
  • Features of Oracle forms
  • Forms parameters and PL-SQL objects association
  • Entity-Relationship Modeling Technique
  • Project