Fashion Designing Entrance Exams 2017 - Notification and Dates

Name of Exam	Date of Exam
All India Entrance Examination For Design (AIEED)	Online Exam – 15 Apr to 30 Apr 2017 CBT – 07 May 2017
Army Institute of Fashion Design (AIFD)	13 May 2017 – UG Only
Common Entrance Examination for Design (CEED)	22 Jan 2017
Footwear Design & Development Institute (FDDI AIST)	01, 02 & 03 Aug 2016
GD Goenka Design Aptitude Test (DAT)	05 Feb 2017
GLS Institute of Design Entrance Exam	29 Jan 2017
Indian Institute of Art & Design (IIAD) Entrance Exam	Outstation – 05 & 06 May 2017 Delhi – 18 to 21 May 2017
Indian Institute of Crafts & Design (IICD) Entrance Exam	28 May 2017
IIT Undergraduate Common Entrance Examination for Design (UCEED)	22 Jan 2017
MAEER’s MIT Institute of Design GDP and PGDP Admission	02 Apr 2017 Cycle 2 – June 2017
NIFT Entrance Exam	12 Feb 2017
NIIFT Mohali Entrance Exam	04 Jun 2016
NID Kurukshetra Entrance Exam	Prelims – 08 Jan 2017 Mains – 09 to 10 Jan 2017
NID Graduate Diploma Programme in Design (GDPD)	Prelims – 08 Jan 2017 Mains – 15 to 20 May 2017
NID Post Graduate Diploma Programme in Design (PGDPD)	Prelims – 08 Jan 2017 Mains – 15 to 20 May 2017
Pearl Academy of Fashion (PAF) Combined General Proficiency Test (GPT) and Design Aptitude Test (DAT)	Cycle 1 – 28 Jan 2017 Cycle 2 – 29 Apr 2017
School of Fashion Technology (SOFT) Pune	18 May – 20 May 2017
Srishti Entrance & Aptitude Test (SEAT)	UG Courses – 15 Apr – 17 Apr 2017 PG Courses – 28 Jan – 29 Jan 2017
UID Ahmedabad Entrance Exam	05 Feb 2017
WLCI All Indian Common Entrance Test (AICET)	Jan 2017

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Easylearning Free Webinar on Image Processing in Apache Spark

Easylearning.guru Introduce a new webinar on Image processing in spark. This webinar New Webinar Session around how images can be upload and processed in Apache spark.

Image processing is loading an image and performing some operation on it or extracting some useful information from it. This is what we will show in our webinar. 
We will read images in spark and perform operations like resizing the image on it or counting the number of faces in an image or extract some useful information like width and size of an image. 

Image processing is a type of signal processing in which input is an image and output may be image or characteristics/features associated with that image. Nowadays, image processing is among rapidly growing technologies. It forms core research area within engineering and computer science disciplines too. 

The output of image processing may be either an image or a set of characteristics or parameters related to the image. Users will get to know how to handle big data in unstructured format using spark. The webinar is about analyzing images using spark. There are various analytics tools for processing images but making analysis using spark makes this webinar interesting. Theory as well as hand-on session are included in this webinar.

Get Complete Webinar Details and Enroll Now- http://goo.gl/J9faOV
Date: 28 June 2016 at 06:30 PM ( IST )

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Face Detection using Hadoop MapReduce Framework

Face detection  is a PC innovation that is utilized to spot and distinguish human appearances in computerized pictures. Programming and particular calculations are utilized to build up the presence, area, size and different points of interest of a human face in a photo or video or some other picture. The product has the capacity to separate between the facial elements of the individual and other foundation objects.

Go along with this online course to figure out how to distinguish and separate appearances from pictures utilizing the Hadoop MapReduce structure. Hadoop MapReduce is a standout amongst the most sought after programming models that attempts to actualize preparing and producing tremendous information sets with parallel and appropriated calculations on a bunch. A MapReduce program basically comprises of a Map, the methodology that channels and sorts information, and a Reduce, which plays out the synopsis operation, along these lines actualizing the MapReduce System foundation or structure that coordinates the information handling by marshaling appropriated servers, running parallel assignments, dealing with all information exchanges between framework parts and minimizing redundancies and issues.

The center of this online course is the anaylsis of unstructured information utilizing the Hadoop Framework. Specifically it will focus on face location by means of Hadoop Framework. The online class will incorporate hypothesis furthermore have a hands-on down to earth session. In this online class will take you through the fundamental parts of Hadoop MapReduce and afterward talk about a portion of the picture handling calculations. It will likewise display a basic model that can be utilized for the recognition, area and extraction of countenances from pictures in the Hadoop Framework with the assistance of particular calculations.

Webinar Details-

Webinar Topic- Face Detection Using Hadoop Mapreduce Framework
 Date:                21 June 2016 at 6:30 Pm (IST)
Register For Webinar- http://goo.gl/2bW2Wk

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MongoDB Tutorials for Beginners at EasyLearning Guru

MongoDB is a flexible, powerful and scalable general-purposed database. MongoDB is the most popular choice to fit in document database model. MongoDB provides high availability with automatic failover and automated sharding capabilities.

MongoDB is document-oriented database. The primary reason for moving away from the relational model is to make scaling out easier, but there are some advantages as well like there are no predefined schemas in MongoDB. MongoDB is intended to be general-purpose database, so aside creating, reading, updating data, it provides an ever-growing list of unique features like aggregation, indexing, range queries, file storage, replication, auto sharding and many more.

MongoDB is the leading NoSQL database, with significant adoption among the fortune 500 and global 500.Due to MongoDB’s popularity the need for MongoDB training is growing, people usually search for MongoDB Tutorial for beginners and EasyLearning.Guru is one of the websites, which provides online instructor led training for MongoDB.

The MongoDB tutorials for beginners by EasyLearning.Guru provides an in-depth Knowledge of all the contents of the course. The trainers here, have expertise in their field and the training provided by EasyLearning.Guru has practical sessions to understand the concepts clearly.

If you would like to attend “FREE Live Demo” you can click on the link below:

Website Url- http://easylearning.guru/

Phone: +91-124-4763660

Email: contact@easylearning.guru

Address:  First Floor, Plot No-97, Sector-44, Gurgaon Haryana - 122002

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Apache Hadoop Training at Easylearning Guru

Apache Hadoop has become one of the most growing technologies these days. As the amount of “Big Data” rises, the need for Hadoop is growing as well as the need for Hadoop Training is growing. People usually search Hadoop Tutorial, Hadoop for beginners, Hadoop Tutorial Cloudera and more but there are few vendors who provide actual training in this regard. Those who do, they provide it at such a price, which will make your pockets empty.

Easylearning Guru is one of the websites, which provide Online Instructor led Training on Hadoop at a reasonable price. People like to watch Hadoop tutorial step by step, with each step explained. Easylearning Guru offers such explanations and then they provide access to the Hadoop Tutorial for lifetime. 

We have made learning Hadoop online very easy. The best part is that not only we provide Hadoop Training, but we also give Hadoop Certification after the training gets completed. The course curriculum is created in such a way that it will equip you to clear the Cloudera Certification with ease.

All in all, Easylearning Guru provide Big Data and Hadoop Training and Certification at a very reasonable price.

If you would like to attend “FREE Live Demo” you can click on the link below:

Website Url- http://easylearning.guru/

Phone: +91-124-4763660

Email: contact@easylearning.guru

Address:  First Floor, Plot No-97, Sector-44, Gurgaon Haryana - 122002

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