Up-Coming Training Events:

            13-17 October, 2019            

This is a full Day Training from 09:00am - 17:00pm

- Module 1 : BigData Management

- Module 2 : Data Analytics & Visualization

- Module 3 : Machine Learning & Modeling

- Module 4 : Deep Learning & Computer Vision

                                                          

This is a full Day Training from 09:00am - 17:00pm

- Module 1 : BigData Management

- Module 2 : Data Analytics & Visualization

- Module 3 : Machine Learning & Modeling

- Module 4 : Deep Learning & Computer Vision

        29 September - 03 October, 2019        

This is a full Day Training from 09:00am - 17:00pm

- Module 1 : BigData Management

- Module 2 : Data Analytics & Visualization

- Module 3 : Machine Learning & Modeling

- Module 4 : Deep Learning & Computer Vision

Up-Coming Training Events:

            13-17 October, 2019            

This is a full Day Training from 09:00am - 17:00pm

- Module 1 : BigData Management

- Module 2 : Data Analytics & Visualization

- Module 3 : Machine Learning & Modeling

- Module 4 : Deep Learning & Computer Vision

                                                          

This is a full Day Training from 09:00am - 17:00pm

- Module 1 : BigData Management

- Module 2 : Data Analytics & Visualization

- Module 3 : Machine Learning & Modeling

- Module 4 : Deep Learning & Computer Vision

        29 September - 03 October, 2019        

This is a full Day Training from 09:00am - 17:00pm

- Module 1 : BigData Management

- Module 2 : Data Analytics & Visualization

- Module 3 : Machine Learning & Modeling

- Module 4 : Deep Learning & Computer Vision

Up-Coming Training Events:

                                                           

This is a full Day Training from 09:00am - 17:00pm

  - Track 1 : BigData Management

  - Track 2 : Data Analytics & Visualization

  - Track 3 : Machine Learning & Modeling

  - Track 4 : Deep Learning & Computer Vision

                                                           

This is a full Day Training from 09:00am - 17:00pm

  - Track 1 : BigData Management

  - Track 2 : Data Analytics & Visualization

  - Track 3 : Machine Learning & Modeling

  - Track 4 : Deep Learning & Computer Vision

                                                           

This is a full Day Training from 09:00am - 17:00pm

  - Track 1 : BigData Management

  - Track 2 : Data Analytics & Visualization

  - Track 3 : Machine Learning & Modeling

  - Track 4 : Deep Learning & Computer Vision

The Data Science training is a practical fast-paced training to get you into data science field immediately. Our program consists of three paths: BigData Engineering, Data Analytics & Visualization and Machine Learning.

Download Training Booklet !

    Download Training Booklet now !

      The Data Science training is a practical fast-paced training to get you into data science field immediately. Our program consists of three paths: BigData Engineering, Data Analytics & Visualization and Machine Learning.

      Program Contents :-

      Module 0 : Introduction

            Intro to  AI & Data Science   

      Artificial Intelligence (AI) is a field that has a long history but is still constantly and actively growing and changing.

      The term artificial intelligence (AI) refers to a set of computer science techniques that enable systems to perform tasks normally requiring human intelligence, such as visual perception, speech recognition, decision-making and language translation. Machine learning and deep learning are branches of AI which, based on algorithms and powerful data analysis, enable computers to learn and adapt independently.

      In this Program, you’ll learn the basics of modern AI from data collection all the way to solution design and make your final product online. This program provides you with:

      • In-depth overview of Hadoop and MapReduce, the cornerstones of big data processing and data management systems.
      • Principles of data Analytics techniques, building predictive models, design visualizing dashboards, creating reports and presenting results to audiences of all levels.
      • Develop an understanding of the principles of machine learning and derive practical solutions using predictive analytics.
      • Overview about Deep Learning, Computer vision and its applications in developing advanced Artificial Intelligence solution.

       

      Register Now !
      Module 1 : BigData Analytics

           BigData Management     

      Today, organizations in every industry are being showered with imposing quantities of new information. Along with traditional sources, many more data channels and categories now exist. Collectively, these vastly larger information volumes and new assets are known as big data. 

      Enterprises are using technologies such as MapReduce and Hadoop to extract value from big data. This course provides an in-depth overview of Hadoop and MapReduce, the cornerstones of big data processing. To crystalize the concepts behind Hadoop and MapReduce, write basic MapReduce programs, gain familiarity with advanced MapReduce programming practices, and utilize interfaces such as Pig and Hive to interact with Hadoop. You will also learn about real-world situations were MapReduce techniques can be used.

      Module 1 Outline:

      • Hadoop Introduction
      • Hadoop Hands-on
      • Introduction to ETL Tool (Pig)
      • Introduction to Hive (DWH)
      • Introduction to Map Reduce
      • NoSQL Databases: MongoDB
      •  Apache Spark Basics
      Register Now !
      Module 2 : Data Visualization

       Data Analytics & Visualization  

      This course introduces the basic goals and techniques in data science and analytics process with some theoretical foundations which include useful statistical concepts and data visualization to get insight about from the dataset. The course provides basic principles on important steps of the process which include data collecting, curating, analyzing, building predictive models and reporting and presenting results to audiences of all levels.

      Python or R languages and statistical analysis techniques are introduced based on examples such as from marketing, business intelligence and decision support. Finally, you get introduced to state of the art Business Intelligence Data Visualization tools like PowerBI and Tableau and how to use it in storytelling.

      Track 2 modules are:

      • Introduction to Data Science 
      • Stages of Data Science Project
      • (R / Python) for Data Science
      • Data Cleansing &Manipulation
      • Exploring and Visualizing Data
      • Data Visualization - Tableau
      • Data Visualization - Power BI
      Register Now !
      Module 3 : Machine Learning

        Machine Learning & Modeling  

      In this course, you will develop an understanding of the principles of machine learning and derive practical solutions using predictive analytics. you'll learn about some of the most widely used and successful machine learning techniques. You'll have the opportunity to implement these algorithms yourself, and gain practice with them. You will also learn some of practical hands-on tricks and techniques (rarely discussed in textbooks) that help get learning algorithms to work well.

      This is an "applied" machine learning Course, and we emphasize the intuitions and know-how needed to get learning algorithms to work in practice, rather than the mathematical derivations. At the end of course, you are going to work on large scale real-world project to emphasize all skills learned in all three courses.

      Track 3 modules are:

      • Classification
      • Regression
      • Tree and Ensemble Methods
      • Clustering & Recommenders
      • Artificial Neural Networks
      • Predictive Modeling
      • Applied Machine Learning
      • Capstone Project
      Register Now !
      Module 4 : Deep Learning

      Deep Learning & Computer Vision

      Machine learning were around us for some time and it help us to solve so many problems, but when it comes to use huge amount of data the tradition machine learning can’t help a lot. Due to the development in computation capabilities, statistical and mathematical algorithms to improve our prediction and modelling. Here, where Artificial Neural Networks (ANN) and it’s Deep Neural Networks (DNN) comes to picture.

      Track 4 modules are:

      • Introduction to Deep Learning
      • TensorFlow & Keras for ANN
      • Convolutional NN (CNN)
      • Recurrent NN (RNN)
      • Boltzmann & Autoencoders
      • Intro. to Computer Vision
      • Intro. to OpenCV, SSD & GANs
      • Intro. to Object Detection
      • Intro. to Facial Recognition
      • Capstone Project
      Register Now !
      Module 0 : Intro to Artificial Intelligence & Data Science

      Intro to Artificial Intelligence & Data Science

      Artificial Intelligence (AI) is a field that has a long history but is still constantly and actively growing and changing. The term artificial intelligence (AI) refers to a set of computer science techniques that enable systems to perform tasks normally requiring human intelligence, such as visual perception, speech recognition, decision-making and language translation. Machine learning and deep learning are branches of AI which, based on algorithms and powerful data analysis, enable computers to learn and adapt independently.
       
       
      In this Program, you’ll learn the basics of modern AI from data collection all the way to solution design and make your final product online. This program provides you with:
       
       
      • In-depth overview of Hadoop and MapReduce, the cornerstones of big data processing and data management systems.
      • Principles of data Analytics techniques, building predictive models, design visualizing dashboards, creating reports and presenting results to audiences of all levels.
      • Develop an understanding of the principles of machine learning and derive practical solutions using predictive analytics.
      • Overview about Deep Learning, Computer vision and its applications in developing advanced Artificial Intelligence solution.

       

      Register Now !
      Module 1 : BigData Management & Analytics

      BigData Management & Analytics

      Today, organizations in every industry are being showered with imposing quantities of new information. Along with traditional sources, many more data channels and categories now exist. Collectively, these vastly larger information volumes and new assets are known as big data. Enterprises are using technologies such as MapReduce and Hadoop to extract value from big data. This course provides an in-depth overview of Hadoop and MapReduce, the cornerstones of big data processing. To crystalize the concepts behind Hadoop and MapReduce, write basic MapReduce programs, gain familiarity with advanced MapReduce programming practices, and utilize interfaces such as Pig and Hive to interact with Hadoop. You will also learn about real-world situations were MapReduce techniques can be used.

      Big Data Track main modules are:

      • Hadoop Introduction
      • Hadoop Installation and Hands-on
      • Introduction to ETL Tool (Pig)
      • Introduction to Hive (Warehouse)
      • Introduction to Map Reduce
      • NoSQL Databases: Casandra and MongoDB
      • Apache Spark Basics

      Register Now !
      Module 2 : Data Analytics & Visualization

      Data Analytics & Visualization

      This course introduces the basic goals and techniques in data science and analytics process with some theoretical foundations which include useful statistical concepts and data visualization to get insight about from the dataset. The course provides basic principles on important steps of the process which include data collecting, curating, analyzing, building predictive models and reporting and presenting results to audiences of all levels. R programming or Python Programming language and statistical analysis techniques are introduced based on examples such as from marketing, business intelligence and decision support. Finally, you get introduced to state of the art Business Intelligence Data Visualization tools like PowerBI and Tableau and how to use it in storytelling.

      Analytics and Visualization main modules are:

      • Introduction to Data Science
      • The Stages of a Data Science Project
      • (R / Python) for Data Science
      • Data Cleansing and Manipulation
      • Exploring and Visualizing Data
      • Data Visualization using Tableau
      • Data Visualization with PowerBI
      Register Now !
      Module 3 : Machine Learning & Modeling

      Machine Learning and Modeling

      In this course, you will develop an understanding of the principles of machine learning and derive practical solutions using predictive analytics. you'll learn about some of the most widely used and successful machine learning techniques. You'll have the opportunity to implement these algorithms yourself, and gain practice with them. You will also learn some of practical hands-on tricks and techniques (rarely discussed in textbooks) that help get learning algorithms to work well. This is an "applied" machine learning Course, and we emphasize the intuitions and know-how needed to get learning algorithms to work in practice, rather than the mathematical derivations. At the end of course, you are going to work on large scale real-world project to emphasize all skills learned in all three courses.

      Machine Learning track main modules are:

      • Classification
      • Regression
      • Tree and Ensemble Methods
      • Clustering and Recommenders
      • Neural Networks
      • Predictive Modeling
      • Applied Machine Learning
      • Capstone Project
      Register Now !
      Module 4 : Deep Learning & Computer Vision

      Deep Learning & Computer Vision

      Machine learning were around us for some time and it help us to solve so many problems, but when it comes to use huge amount of data the tradition machine learning can’t help a lot. Due to the development in computation capabilities, statistical and mathematical algorithms to improve our prediction and modelling. Here, where Artificial Neural Networks (ANN) and it’s Deep Neural Networks (DNN) comes to picture.

      Deep Learning track modules are:

      • Introduction to Deep Learning
      • Neural Networks with TensorFlow
      • Convolutional Neural Networks (CNN)
      • Recurrent Neural Networks (RNN)
      • Boltzmann (RBM) and Autoencoders
      • Introduction to Computer Vision
      • Introduction to OpenCV, SSD and GANs
      • Object Detection and Facial Recognition
      • Capstone Project
      Register Now !

      Training Setup :-

      Training Calendar :

      Partners & Tools :-

      PARTNERS & TOOLS

      List of Technology Partners and Tools we use

      TECHNOLOGY PARTNERS

      List of Technology & Success Partners

      Register Now :-

      Course Registration

       

       

       

       

       

      Training Location :-

      Emirates Towers

      Diamond Room - Level 5
      Sheikh Zayed Road, Dubai, United Arab Emirates

      Central Plaza Tower

      28/F Central Plaza
      34 Jalan Sultan Ismail, 50250 KL, Malaysia

      ADGM Building

      Authorities Building, ADGM Square,
      Al Maryah Island - Abu Dhabi - U.A Emirates

      Emirates Towers

      Diamond Room - Level 5
      Sheikh Zayed Road, Dubai, United Arab Emirates

      Central Plaza Tower

      28/F Central Plaza
      34 Jalan Sultan Ismail, 50250 KL, Malaysia

      ADGM Building

      Authorities Building, ADGM Square,
      Al Maryah Island - Abu Dhabi - U.A Emirates

      Remaining Time :-