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      Program Contents :

      Module 0 : Introduction to DS
      Data Science (DS) is a field that has a long history but is still constantly and actively growing and changing.
      DS Training Summer Mobile
      In this Program, you’ll learn the basics of Data Science framework 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.

       

      Register Now !

           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. 

      DWH 1

      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 !

       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.

      BI 1 1

      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 !

        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.

      AI 300 200

      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 0 : Introduction to Data Science

      Introduction to Data Science

      Data Science (DS) is a field that has a long history but is still constantly and actively growing and changing.

      DS Training Summer Mobile
      In this Program, you’ll learn the basics of Data Science framework 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.

       

      Register Now !

      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.

      DWH 1

      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

      big data hadoop retail 1

      Register Now !

      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.

      BI 1

      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
      Sales Featuere 2
      Register Now !

      Machine Learning and Modeling

      AI 300 200

      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.

      AI 300 200

      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 !

      Training Setup:

      Training Enviroment 1
      Class Setup 3

      Training Calendar :

      Training Calender General new 1

      Partners & Tools:

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      PARTNERS & TOOLS

      List of Technology Partners and Tools we use

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      TECHNOLOGY PARTNERS

      List of Technology & Success Partners

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            Training Venues

            Biz City Business Center

            City Tower 2 - 14th Floor - Sheikh Zayed Rd - Dubai - United Arab Emirates

            Central Plaza Tower

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

            Point Lab Space

            Jl. Banda No.30, Citarum, 40115 Bandung, Indonesia

            Biz City Business Center

            City Tower 2 - SZR - Dubai - UAE

            Central Plaza Tower

            8/F Central Plaza 34, KL, Malaysia

            Point Lab Space

            Jl. Banda No.30, Bandung, Indonesia

            Remaining Time :

             
             

            |  Dubai, UAE  |  Kuala, Malaysia  | Istanbul, Turkey |

            |  Riyadh, KSA  |  Amman, Jordan  | Hangzhou, China |

            |  Muscat, Oman  |  Cairo, Egypt  | Bangkok, Thailand |