Archive for September 2017

Data Analytics Training in Vellore

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What Will I Learn?

Successfully perform all steps in a complex Data Science project

Create Basic Tableau Visualisations

Perform Data Mining in Tableau

Understand how to apply the Chi-Squared statistical test

Apply Ordinary Least Squares method to Create Linear Regressions

Assess R-Squared for all types of models

Assess the Adjusted R-Squared for all types of models

Create a Simple Linear Regression (SLR)

Create a Multiple Linear Regression (MLR)

Create Dummy Variables

Interpret coefficients of an MLR

Read statistical software output for created models

Use Backward Elimination, Forward Selection, and Bidirectional Elimination methods to create statistical models

Create a Logistic Regression

Intuitively understand a Logistic Regression

Operate with False Positives and False Negatives and know the difference

Read a Confusion Matrix

Create a Robust Geodemographic Segmentation Model

Transform independent variables for modelling purposes

Derive new independent variables for modelling purposes

Check for multicollinearity using VIF and the correlation matrix

Understand the intuition of multicollinearity

Apply the Cumulative Accuracy Profile (CAP) to assess models

Build the CAP curve in Excel

Use Training and Test data to build robust models

Derive insights from the CAP curve

Understand the Odds Ratio

Derive business insights from the coefficients of a logistic regression

Understand what model deterioration actually looks like

Apply three levels of model maintenance to prevent model deterioration

Install and navigate SQL Server

Install and navigate Microsoft Visual Studio Shell

Clean data and look for anomalies

Use SQL Server Integration Services (SSIS) to upload data into a database

Create Conditional Splits in SSIS

Deal with Text Qualifier errors in RAW data

Create Scripts in SQL

Apply SQL to Data Science projects

Create stored procedures in SQL

Present Data Science projects to stakeholders

Requirements

Only a passion for success

All software used in this course is either available for Free or as a Demo version

Description

Extremely Hands-On... Incredibly Practical... Unbelievably Real!

This is not one of those fluffy classes where everything works out just the way it should and your training is smooth sailing. This course throws you into the deep end.

In this course you WILL experience firsthand all of the PAIN a Data Scientist goes through on a daily basis. Corrupt data, anomalies, irregularities - you name it!

This course will give you a full overview of the Data Science journey.

Upon completing this course you will know:

How to clean and prepare your data for analysis

How to perform basic visualisation of your data

How to model your data

How to curve-fit your data

And finally, how to present your findings and wow the audience

This course will give you so much practical exercises that real world will seem like a piece of cake when you graduate this class. This course has homework exercises that are so thought provoking and challenging that you will want to cry... But you won't give up! You will crush it. In this course you will develop a good understanding of the following tools:

SQL

SSIS

Tableau

Gretl

This course has pre-planned pathways. Using these pathways you can navigate the course and combine sections into YOUR OWN journey that will get you the skills that YOU need.

Who is the target audience?

Anybody with an interest in Data Science

Anybody who wants to improve their data mining skills

Anybody who wants to improve their statistical modelling skills

Anybody who wants to improve their data preparation skills

Anybody who wants to improve their Data Science presentation skills

The choice is yours. Join the class and start learning today!

Or you can do the whole course and set yourself up for an incredible career in Data Science.

For More Details :

Redback IT Solutions Pvt Ltd.,

No : 5/X2 Hari Ohm 2nd Street,

Phase III, Sathuvachari, Vellore.

+91 8189985551.

Wednesday, 27 September 2017

Posted by Sivapriya

2 Comments

Tag : Amazon AWS, Big Data, Data Analytics, Hadoop, Hive, Mongo DB, Pig, R, SAS

Cloud Computing Training at Vellore

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Course Introduction :

This graduate-level course investigates cloud computing models, techniques, and architectures. Cloud computing has evolved as a very important computing model, which enables information, software, and other shared resources to be provisioned over the network as services in an on-demand manner. Students will be exposed to the current practices in cloud computing.

Topics may include distributed computing models and technologies, Infrastructure-as-a-Service (IaaS), Platform-as-a-Service (PaaS), Software-as-a-Service (SaaS), virtualization, security and privacy issues, performance and systems issues, capacity planning, disaster recovery, Cloud OS, federated clouds, challenges in implementing clouds, data centers, hypervisor CPU and memory management, cloud hosted applications, and other advanced and research topics in cloud computing.

WHAT KIND OF BACKGROUND DO I NEED ?

A working knowledge of Internet, browsers, MS Windows and Web applications is helpful but not required. Programming experience is also helpful but not required. If you do not possess knowledge of Linux we teach you that too.

WHAT BENEFIT I DO GET FROM THE CLOUD COMPUTING COURSE?

Yes! The course presents the business advantages of the cloud and also the technical benefits it can provide. The technical discussions are at a level that attendees with a business background can understand and apply. Where technical knowledge is required, sufficient guidance for all backgrounds is provided to enable activities to be completed and the learning objectives achieved.

World's Most Popular Cloud Computing Technologies are,

Salesforce.com-The Worlds No.1 CRM.

VMware, Inc-Virtualizes Computing.

Amazon Web Services(AWS)-Broad & Deep Core Cloud Infrastructure Services.

Linux OpenStack-Open source software for creating private and public clouds.

Microsoft Azure.

Syllabus :

#MODULE - 1

Introduction to Computing

Recent Stages in the cloud Computing

About Grid Computing in Cloud

Utility Computing in Cloud

Basics of Cloud Cluster Computing

Distributed system Computing and Evolutions in Cloud Computing

#MODULE - 2

Overview of Cloud Computing

(NIST) Model Overview

Basics, Cloud Service History . Cloud Computing history.

Properties,Characteristics.

Advantages and Disadvantages of Cloud Computing,Cloud computing

#MODULE - 3

Architecture of Cloud Computing

stacks in Cloud computing

Traditional computing architecture Comparison, Services providers.

How Cloud Computing Works, Networking and web services roles in Cloud computing, (XaaS)Service Models, protocols used.

(PaaS) -Platform as a Service.

(IaaS) -Infrastructure as a Service.

(SaaS) -Software as a Service.

#MODULE - 4

Infrastructure as a Service

Resource Virtualization of Cloud Computing

Server and Network in Infrastructure as a service

Storage Virtualization in Cloud Computing

#MODULE - 5

Platform as a Service (PAAS)

IBasics of PaaS

(SOA) Service Oriented Architecture and What is PaaS?

Cloud Management and Platform

Computation,storage,Google app engine's,Salesforce explanations

Microsoft Azure in Platform as a service

Working of Salesforce platform

#MODULE - 6

Software as a Service (SAAS)

Basics to SaaS

Web services in Cloud Computing

Web OS and Web 2.0 working Principles

Case Studies

#MODULE - 7

Service Management

Agreements and Service Level

Accounting and Billing in Service Management

Cloud vs Traditional Discussions

Working of Scaling factor

#MODULE - 8

Data Management

Cloud Services and Scalability

Data in cloud Computing

Large Scale Data Processing

Cloud and infrastructure Management

Host level security

Network level security

Application level security

For Details contact :

Redback IT Academy

No : 5/X2 Hari Om 2nd Street,

Phase III, Sathuvachari, Vellore.

+91 8189985551.

Sunday, 24 September 2017

Posted by Sivapriya

1 Comment

Tag : Amazon AWS, Cloud Computing, Google Cloud, Microsoft Azure

GOOGLE SIGNS $1.1 BILLION DEAL WITH HTC

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GOOGLE SIGNED 1.1 BILLION DOLLARS WITH HTC : TOP 8 THINGS TO KNOW

1. Google is making another big bet on the smartphone market. The company has announced acquisition of a part of Taiwan-based HTC's smartphone division. Here's all you need to know about the Google's latest hardware acquisition.

2. Google will pay $1.1 billion in cash to acquire a part of HTC's Pixel smartphone division. Google's head of hardware, Rick Osterloh said in a blog post that with this agreement, a team of HTC talent will join Google as part of the hardware organization.

3. The deal no where means that HTC is bidding goodbye to the smartphone market. HTC will still continue to make its own branded smartphones. It will also be able to put its research in future smartphones, like it did with HTC U11 and its 'Edge Sense' feature.

4. The deal marks Google's second bid at smartphone manufacturing. The first being in five years back in 2012, when Google acquired Motorola in a $12.5 billion deal. Two years later, the search giant sold Motorola to Lenovo for $3 billion. Some other big acquisition of the search giant include YouTube in 2006 for $1.6 billion, Waze for $1.3 billion and Nest for $3.2 billion.

5. As a part of the deal, HTC will receive a non-exclusive license for HTC's. intellectual property. It is, however, so far not clear if HTC will also be able to share its IP with a third party post this deal.

6. HTC will be retaining its Vive division. The company also said that it will continue its focus technologfies like Internet of Things, augmented reality and artificial intelligence.

7. HTC is also the manufacturer of Google's Pixel smartphones for this year as well as were for the last year's models. "These future fellow Googlers are amazing folks we’ve already been working with closely on the Pixel smartphone line, and we're excited to see what we can do together as one team," Osterloh wrote in the blog post.

8. Google's association with HTC goes a long way back. The company made the first-ever Android phone - HTC Dream. HTC also made Google's first Nexus smartphone - Nexus One in 2010 followed by Nexus 9 tablets in 2014.

9. HTC’s worldwide smartphone market share declined to 0.9% last year from a peak of 8.8% in the year 2011, according to data research firm IDC. As for Google Pixel, it held less than 1% market share since it was launched a year ago.

For more details :

http://bit.ly/2hhenlY

Thursday, 21 September 2017

Posted by Anonymous

0 Comments

Top 10 Programming Languages in 2017

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Programming is something vast and rather individual as each developer chooses tools that are most convenient for them. However, certain languages, platforms and frameworks have claimed themselves as one of the easiest and most efficient to use. Thus we have collected for you top-10 programming languages loved by developers nowadays. Which one is your favorite?

1. Python

Python is a dynamic and general-purpose language that emphasizes code readability and enables developers to use fewer lines of code (in comparison with Java or C++). It supports multiple programming paradigms and has a large standard library.

Developers love this language for clear syntax, good OOP support and great shortcuts.

2. C

C is a general-purpose imperative language that supports structured programming, recursion and lexical variable scope. It is designed to encourage cross-platform programming and is available on many platforms.

This language is valued for being clear, providing access to hardware and making it possible to create tiny binaries.

3. Java

Java is one the leading choices among developers all over the world. This language is object-oriented and class-based and follows the “WORA” principle: write once, run anywhere.

People love Java for its concurrency (comparing it to be better than Python, for example), great variety of libraries and steadily good performance. Community is huge as well, meaning Java fans can always get a lot of support.

4. С++

This language is compiled, imperative and program-oriented and allows low-level memory manipulation. C++ influenced a number of other languages, such as C# or Java and is used for a variety of purposes.

Its key features that make it stand out are strong, static type system (making it possible to catch more errors within a compile time), ability to use it in a few programming styles, good performance and expressiveness.

5. C#

C Sharp has seen an increase in popularity over the last year. It is an object-oriented and multi-paradigm language that encompasses many disciplines. C# was developed by Microsoft and is designated for the Common Language Infrastructure.

Though it is not so widespread as Java or Python, C# has its fans who appreciate the lack of headers, macros and templates, presence of LINQ and anonymous types.

6. R

This is an open source language for statistical computing and it is very popular among data miners and statisticians. This language is a GNU package.

The R pros include its package ecosystem and its vastness and all the charting benefits.

7. JavaScript

JS is an object-based and dynamic language and is one of the core technologies of WWW content production. Even though some people tend to think Java and JS are the same (or at least, very similar) languages, JavaScript was influenced mostly by Self and Scheme.

JavaScript is seeing a rise in popularity and is included in hottest web development trends for the year 2017.

8. PHP

It’s a server-side and general-purpose language designed for web development. PHP is considered rather easy to learn and is often chosen by junior developers.

As well developers love that it’s portable, has a lot of high-quality solutions for an array of web problems and has a lot of frameworks.

9. Go

Go was created at Google and is an open-source language. It’s compiled and has such features as garbage collection, memory safety and limited structural typing.

It is really a good choice if you work with network applications and web servers. Go also consistently behaves across platforms, which is also a good feature.

10. Swift

Swift is a multi-paradigm language developed by Apple and is one of the top choices among iOS developers. It supports such concepts as late binding, extensible programming and dynamic dispatch.

Even though Swift is a relatively new language, it also saw rise in popularity in 2017 and overall looks quite promising.

At DashBouquet we personally prefer JavaScript due to the projects that we work on. However, we are always open to learning something new and we don’t limit our skills to one certain language or framework. Just tell us what you want and we will think of the best way to carry it out.

Tuesday, 12 September 2017

Posted by Redback Academy