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Software Engineer Jobs In Sharjah | Canonical
About the job
This engineering role is an opportunity for a technologist with a passion for Linux to build a career with Canonical and drive the success of those leveraging Ubuntu and open source products. If you have an affinity for open source development, you will enjoy working with some of the best people in the industry at Canonical.Requirement
The third major area is related to internal business operations. We develop and operate a data warehouse, including data ingestion pipelines, that are relied on by operations and data analytics teams. In addition to that, we help internal business units to automate processes across many software solutions and integrate SaaS solutions to ensure a smooth flow of data. #J-18808-LjbffrApply safely
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'global_location_id' => '225', 'rel_gloc_ids' => '251,250,249,248,247,246,245,244,225', 'currency' => 'AED', 'currency_name' => 'UAE Dirham', 'languages' => 'en,ar', 'default_language' => 'en', 'country_time_zone' => 'Asia/Dubai', 'job_location' => '1', 'published' => '1', 'show' => '1' ), 'saudi' => array( 'name' => 'Saudi Arabia', 'country_id' => '183', 'country_code' => 'sa', 'slug' => 'saudi', 'global_location_id' => '187', 'rel_gloc_ids' => '274,273,272,271,269,268,267,266,265,264,263,262,261,260,259,258,257,256,255,254,253,187', 'currency' => 'SAR', 'currency_name' => 'Saudi Riyal', 'languages' => 'en,ar', 'default_language' => 'en', 'country_time_zone' => 'Asia/Riyadh', 'job_location' => '1', 'published' => '1', 'show' => '1' ), 'india' => array( 'name' => 'India', 'country_id' => '99', 'country_code' => 'in', 'slug' => 'india', 'global_location_id' => '100', 'rel_gloc_ids' => '100,465,466,467,468,469,470,471,472,473,474,475,476,477,478,479,480,481,976,994,1263,1264', 'currency' => 'INR', 'currency_name' => 'Indian Rupee', 'languages' => 'en', 'default_language' => 'en', 'country_time_zone' => 'Asia/Kolkata', 'job_location' => '1', 'published' => '1', 'show' => '1' ), 'south-africa' => array( 'name' => 'South Africa', 'country_id' => '236', 'country_code' => 'za', 'slug' => 'south-africa', 'global_location_id' => '197', 'rel_gloc_ids' => '197,498,499,500,501,502,503,504', 'currency' => 'ZAR', 'currency_name' => 'South African Rand', 'languages' => 'en', 'default_language' => 'en', 'country_time_zone' => 'Africa/Johannesburg', 'job_location' => '0', 'published' => '1', 'show' => '1' ), 'egypt' => array( 'name' => 'Egypt', 'country_id' => '61', 'country_code' => 'eg', 'slug' => 'egypt', 'global_location_id' => '64', 'rel_gloc_ids' => '64,955,957,1102,1103,1104,1105,1106,1107,1108,1109,1110,1111,1112,1113,1114,1115', 'currency' => 'EGP', 'currency_name' => 'Egyptian pound', 'languages' => 'en,ar', 'default_language' => 'en', 'country_time_zone' => 'Africa/Cairo', 'job_location' => '1', 'published' => '1', 'show' => '1' ), 'singapore' => array( 'name' => 'Singapore', 'country_id' => '188', 'country_code' => 'sg', 'slug' => 'singapore', 'global_location_id' => '192', 'rel_gloc_ids' => '192,382,432,438,445,453', 'currency' => 'SGD', 'currency_name' => 'Singapore Dollar', 'languages' => 'en', 'default_language' => 'en', 'country_time_zone' => 'Asia/Singapore', 'job_location' => '1', 'published' => '1', 'show' => '1' ), 'qatar' => array( 'name' => 'Qatar', 'country_id' => '178', 'country_code' => 'qa', 'slug' => 'qatar', 'global_location_id' => '176', 'rel_gloc_ids' => '176,252', 'currency' => 'QAR', 'currency_name' => 'Qatar Rial', 'languages' => 'en,ar', 'default_language' => 'en', 'country_time_zone' => 'Asia/Qatar', 'job_location' => '1', 'published' => '1', 'show' => '1' ), 'pakistan' => array( 'name' => 'Pakistan', 'country_id' => '169', 'country_code' => 'pk', 'slug' => 'pakistan', 'global_location_id' => '164', 'rel_gloc_ids' => '164,979,1052,1053,1054,1055,1056,1057,1058,1059,1060,1061,1062,1063,1064,1065,1066,1067,1068,1069,1070,1071', 'currency' => 'PKR', 'currency_name' => 'Pakistani rupee', 'languages' => 'en', 'default_language' => 'en', 'country_time_zone' => 'Asia/Karachi', 'job_location' => '1', 'published' => '1', 'show' => '1' ), 'kuwait' => array( 'name' => 'Kuwait', 'country_id' => '116', 'country_code' => 'kw', 'slug' => 'kuwait', 'global_location_id' => '116', 'rel_gloc_ids' => '116,276,277,278,279,280,281', 'currency' => 'KWD', 'currency_name' => 'Kuwait Dinar', 'languages' => 'en,ar', 'default_language' => 'en', 'country_time_zone' => 'Asia/Kuwait', 'job_location' => '1', 'published' => '1', 'show' => '1' ), 'oman' => array( 'name' => 'Oman', 'country_id' => '163', 'country_code' => 'om', 'slug' => 'oman', 'global_location_id' => '163', 'rel_gloc_ids' => '163,282,283,284,285,286,287,288,289,290,291', 'currency' => 'OMR', 'currency_name' => 'Oman Rial', 'languages' => 'en,ar', 'default_language' => 'en', 'country_time_zone' => 'Asia/Muscat', 'job_location' => '1', 'published' => '1', 'show' => '1' ), 'jordan' => array( 'name' => 'Jordan', 'country_id' => '106', 'country_code' => 'jo', 'slug' => 'jordan', 'global_location_id' => '110', 'rel_gloc_ids' => '110,958,959,1101,1247,1246,1245,1244,1243,1242,1241,1240,1239', 'currency' => 'JOD', 'currency_name' => 'Jordanian Dinar', 'languages' => 'en,ar', 'default_language' => 'en', 'country_time_zone' => 'Asia/Amman', 'job_location' => '1', 'published' => '1', 'show' => '1' ), 'philippines' => array( 'name' => 'Philippines', 'country_id' => '168', 'country_code' => 'ph', 'slug' => 'philippines', 'global_location_id' => '171', 'rel_gloc_ids' => '171,482,483,484,485,486,487,488,489,490,491,492,493,494,495,496,497,1262', 'currency' => 'PHP', 'currency_name' => 'Philippine Peso', 'languages' => 'en', 'default_language' => 'en', 'country_time_zone' => 'Asia/Manila', 'job_location' => '1', 'published' => '1', 'show' => 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'country_time_zone' => 'Asia/Kathmandu', 'job_location' => '1', 'published' => '1', 'show' => '1' ), 'nigeria' => array( 'name' => 'Nigeria', 'country_id' => '155', 'country_code' => 'ng', 'slug' => 'nigeria', 'global_location_id' => '158', 'rel_gloc_ids' => '158,995,996,997,1095', 'currency' => 'NGN', 'currency_name' => 'Nigerian Naira', 'languages' => 'en', 'default_language' => 'en', 'country_time_zone' => 'Africa/Lagos ', 'job_location' => '1', 'published' => '1', 'show' => '1' ), 'newzealand' => array( 'name' => 'New Zealand', 'country_id' => '162', 'country_code' => 'nz', 'slug' => 'newzealand', 'global_location_id' => '155', 'rel_gloc_ids' => '155,998,999,1080,1081,1082,1083', 'currency' => 'NZD', 'currency_name' => 'New Zealand Dollar', 'languages' => 'en', 'default_language' => 'en', 'country_time_zone' => 'Pacific/Auckland', 'job_location' => '0', 'published' => '1', 'show' => '1' ), 'brasil' => array( 'name' => 'Brasil', 'country_id' => '29', 'country_code' => 'br', 'slug' 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The certification tests the candidates on various areas in data mining and warehousing which include knowledge of planning, managing, designing, implementing, supporting, maintaining and analyzing the organization’s data warehouse and covering data mining and On-Line Analytical Processing (OLAP).<br /> <br /> <strong>Why should one take this certification?</strong><br /> This certification is intended for professionals and graduates wanting to excel in their chosen areas. It is also well suited for those who are already working and would like to take certification for further career progression.<br /> Earning Vskills Data Mining and Warehousing Professional Certification can help candidate differentiate in today's competitive job market, broaden their employment opportunities by displaying their advanced skills, and result in higher earning potential.<br /> <br /> <strong>Who will benefit from taking this certification?</strong><br /> Job seekers looking to find employment in IT department of various companies, students generally wanting to improve their skill set and make their CV stronger and existing employees looking for a better role can prove their employers the value of their skills through this certification.<br /> <br /> <strong>Companies that hire Vskills Certified Data Mining and Warehousing Professional</strong><br /> Data Mining and Warehousing professional are in great demand. Companies specializing in Integration Services are constantly hiring knowledgeable professionals. Various banks, telecom and IT companies also need data mining and warehousing professionals for data management and analysis.<br /> <br /> <strong>Table of Contents</strong><br /> <br /> <strong>DATA WAREHOUSING INTRODUCTION</strong> <ul> <li>Introduction</li> <li>Meaning of Data Warehousing</li> <li>History of Data Warehousing</li> </ul> <strong>DATA WAREHOUSING CHARACTERISTICS</strong> <ul> <li>Introduction</li> <li>Data Warehousing</li> <li>Operational vs. Informational Systems</li> <li>Characteristics of Data Warehousing</li> </ul> <strong>ONLINE TRANSACTION PROCESSING</strong> <ul> <li>Introduction</li> <li>Data Warehousing and OLTP Systems</li> <li>Processes in Data Warehousing OLTP</li> <li>What is OLAP?</li> <li>Who uses OLAP and WHY?</li> <li>Multi-Dimensional View s</li> <li>Benefits of OLAP</li> </ul> <strong>DATA WAREHOUSING MODELS</strong> <ul> <li>Introduction</li> <li>The Data Warehouse Model</li> <li>Data Modeling for Data Warehouses</li> </ul> <strong>DATA WAREHOUSING ARCHITECTURE</strong> <ul> <li>Introduction</li> <li>Structure of a Data Warehouse</li> <li>Data Warehouse Physical Architectures</li> <li>Principles of a Data Warehousing</li> </ul> <strong>DATA WAREHOUSING AND OPERATIONAL SYSTEMS</strong> <ul> <li>Introduction</li> <li>Operational Systems</li> <li>“ Warehousing” Data outside the Operational Systems</li> <li>Integrating Data from more than one Operational System</li> <li>Differences between Transaction and Analysis Processes</li> <li>Data is mostly Non-volatile</li> <li>Data saved for longer periods than in transaction systems</li> <li>Logical Transformation of Operational Data</li> <li>Structured Extensible Data Model</li> <li>Data Warehouse model aligns with the business structure</li> <li>Transformation of the Operational State Information</li> <li>De-normalization of Data</li> <li>Static Relationships in Historical Data</li> <li>Physical Transformation of Operational Data</li> <li>Operational terms transformed into uniform business terms</li> </ul> <strong>DATA WAREHOUSING CONSIDERATIONS</strong> <ul> <li>Introduction</li> <li>Building a Data Warehouse</li> <li>Nine Decisions in the design of a Data Warehouse</li> </ul> <strong>DATA WAREHOUSING - APPLICATIONS</strong> <ul> <li>Introduction</li> <li>Data Warehouse Application</li> </ul> <strong>ROI AND DESIGN CONSIDERATIONS</strong> <ul> <li>Introduction</li> <li>Need of a Data Warehouse</li> <li>Business Considerations: Return on Investment</li> <li>Organizational Issues</li> <li>Design Considerations</li> <li>Data content</li> <li>Metadata</li> <li>Data Distribution</li> <li>Tools</li> <li>Performance Considerations</li> </ul> <strong>TECHNICAL AND IMPLEMENTATION CONSIDERATIONS</strong> <ul> <li>Introduction</li> <li>Technical Considerations</li> <li>Hardware Platforms</li> <li>Balanced Approach</li> <li>Optimal hardware architecture for parallel queryscalability</li> <li>Data warehouse and DBMS Specialization</li> <li>Communications Infrastructure</li> <li>Implementation Considerations</li> <li>Access Tools</li> </ul> <strong>DATA WAREHOUSING BENEFITS</strong> <ul> <li>Introduction</li> <li>Benefits of Data Warehousing</li> <li>Problems with Data Warehousing</li> <li>Criteria for a Data Warehouse</li> </ul> PROJECT MANAGEMENT PROCESS <ul> <li>Introduction</li> <li>Project Management Process</li> <li>The Scope Statement</li> <li>Project Planning</li> <li>Project Scheduling</li> <li>Software Project Planning</li> <li>Critical Path Method</li> <li>Decision Making</li> </ul> <strong>WORK BREAKDOWN STRUCTURE</strong> <ul> <li>Introduction</li> <li>Work Breakdow n Structure (WBS)</li> <li>How to build a WBS (a serving suggestion)</li> <li>To Create Work Breakdown Structure</li> <li>From WBS to Activity Plan</li> <li>Estimating Time</li> </ul> <strong>PROJECT ESTIMATION AND RISK</strong> <ul> <li>Introduction</li> <li>Project Estimation</li> <li>Analyzing Probability & Risk</li> </ul> <strong>MANAGING RISK</strong> <ul> <li>Introduction</li> <li>Risk Analysis</li> <li>Risk Management</li> <li>Risk Analysis</li> <li>Managing Risks: Internal & External</li> <li>Internal and External Risks</li> <li>Critical Path Analysis</li> </ul> <strong>DATA MINING CONCEPTS</strong> <ul> <li>Introduction</li> <li>Data Mining</li> <li>Data Mining Background</li> <li>Inductive Learning</li> <li>Statistics</li> <li>Machine Learning</li> </ul> <strong>DATA MINING AND KDD</strong> <ul> <li>Introduction</li> <li>What is Data Mining?</li> <li>Data Mining: Definitions</li> <li>KDD vs. Data Mining</li> <li>Stages OF KDD</li> <li>Machine Learning vs. Data Mining</li> <li>Data Mining vs. DBMS</li> <li>Data Warehouse</li> <li>Statistical Analysis</li> </ul> <strong>ELEMENTS OF DATA MINING</strong> <ul> <li>Introduction</li> <li>Elements and uses of Data Mining</li> <li>Relationships & Patterns</li> <li>Data Mining Problems/Issues</li> <li>Goals of Data Mining and Know ledge Discovery</li> </ul> <strong>DATA INFORMATION AND 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<strong>DECISION TREES</strong> <ul> <li>What is a Decision Tree?</li> <li>Decision Trees</li> <li>Where to use Decision Trees?</li> <li>Tree Construction Principle</li> <li>The Generic Algorithm</li> <li>Guillotine Cut</li> <li>Over Fit</li> </ul> <strong>DECISION TREES - ADVANCED</strong> <ul> <li>Best Split</li> <li>Decision Tree Construction Algorithms</li> <li>Cart</li> <li>ID3</li> <li></li> <li>Chaid</li> <li>How the Decision Tree Works</li> <li>State of the Industry</li> </ul> <strong>NEURAL NETWORKS</strong> <ul> <li>Basics of Neural Networks</li> <li>Are neural networks easy to use?</li> <li>Business Scorecard</li> <li>Where to use Neural Networks</li> <li>Neural Networks for Clustering</li> <li>Neural Networks for Feature Extraction</li> <li>Applications Score Card</li> <li>The General Idea</li> </ul> <strong>NEURAL NETWORKS - ADVANCED</strong> <ul> <li>What is a Neural Network Pparadigm?</li> <li>Design decisions in architecting a neural network</li> <li>Different types of 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The certification tests the candidates on various areas in data mining and warehousing which include knowledge of planning, managing, designing, implementing, supporting, maintaining and analyzing the organization’s data warehouse and covering data mining and On-Line Analytical Processing (OLAP).<br /> <br /> <strong>Why should one take this certification?</strong><br /> This certification is intended for professionals and graduates wanting to excel in their chosen areas. It is also well suited for those who are already working and would like to take certification for further career progression.<br /> Earning Vskills Data Mining and Warehousing Professional Certification can help candidate differentiate in today's competitive job market, broaden their employment opportunities by displaying their advanced skills, and result in higher earning potential.<br /> <br /> <strong>Who will benefit from taking this certification?</strong><br /> Job seekers looking to find employment in IT department of various companies, students generally wanting to improve their skill set and make their CV stronger and existing employees looking for a better role can prove their employers the value of their skills through this certification.<br /> <br /> <strong>Companies that hire Vskills Certified Data Mining and Warehousing Professional</strong><br /> Data Mining and Warehousing professional are in great demand. Companies specializing in Integration Services are constantly hiring knowledgeable professionals. Various banks, telecom and IT companies also need data mining and warehousing professionals for data management and analysis.<br /> <br /> <strong>Table of Contents</strong><br /> <br /> <strong>DATA WAREHOUSING INTRODUCTION</strong> <ul> <li>Introduction</li> <li>Meaning of Data Warehousing</li> <li>History of Data Warehousing</li> </ul> <strong>DATA WAREHOUSING CHARACTERISTICS</strong> <ul> <li>Introduction</li> <li>Data Warehousing</li> <li>Operational vs. Informational Systems</li> <li>Characteristics of Data Warehousing</li> </ul> <strong>ONLINE TRANSACTION PROCESSING</strong> <ul> <li>Introduction</li> <li>Data Warehousing and OLTP Systems</li> <li>Processes in Data Warehousing OLTP</li> <li>What is OLAP?</li> <li>Who uses OLAP and WHY?</li> <li>Multi-Dimensional View s</li> <li>Benefits of OLAP</li> </ul> <strong>DATA WAREHOUSING MODELS</strong> <ul> <li>Introduction</li> <li>The Data Warehouse Model</li> <li>Data Modeling for Data Warehouses</li> </ul> <strong>DATA WAREHOUSING ARCHITECTURE</strong> <ul> <li>Introduction</li> <li>Structure of a Data Warehouse</li> <li>Data Warehouse Physical Architectures</li> <li>Principles of a Data Warehousing</li> </ul> <strong>DATA WAREHOUSING AND OPERATIONAL SYSTEMS</strong> <ul> <li>Introduction</li> <li>Operational Systems</li> <li>“ Warehousing” Data outside the Operational Systems</li> <li>Integrating Data from more than one Operational System</li> <li>Differences between Transaction and Analysis Processes</li> <li>Data is mostly Non-volatile</li> <li>Data saved for longer periods than in transaction systems</li> <li>Logical Transformation of Operational Data</li> <li>Structured Extensible Data Model</li> <li>Data Warehouse model aligns with the business structure</li> <li>Transformation of the Operational State Information</li> <li>De-normalization of Data</li> <li>Static Relationships in Historical Data</li> <li>Physical Transformation of Operational Data</li> <li>Operational terms transformed into uniform business terms</li> </ul> <strong>DATA WAREHOUSING CONSIDERATIONS</strong> <ul> <li>Introduction</li> <li>Building a Data Warehouse</li> <li>Nine Decisions in the design of a Data Warehouse</li> </ul> <strong>DATA WAREHOUSING - APPLICATIONS</strong> <ul> <li>Introduction</li> <li>Data Warehouse Application</li> </ul> <strong>ROI AND DESIGN CONSIDERATIONS</strong> <ul> <li>Introduction</li> <li>Need of a Data Warehouse</li> <li>Business Considerations: Return on Investment</li> <li>Organizational Issues</li> <li>Design Considerations</li> <li>Data content</li> <li>Metadata</li> <li>Data Distribution</li> <li>Tools</li> <li>Performance Considerations</li> </ul> <strong>TECHNICAL AND IMPLEMENTATION CONSIDERATIONS</strong> <ul> <li>Introduction</li> <li>Technical Considerations</li> <li>Hardware Platforms</li> <li>Balanced Approach</li> <li>Optimal hardware architecture for parallel queryscalability</li> <li>Data warehouse and DBMS Specialization</li> <li>Communications Infrastructure</li> <li>Implementation Considerations</li> <li>Access Tools</li> </ul> <strong>DATA WAREHOUSING BENEFITS</strong> <ul> <li>Introduction</li> <li>Benefits of Data Warehousing</li> <li>Problems with Data Warehousing</li> <li>Criteria for a Data Warehouse</li> </ul> PROJECT MANAGEMENT PROCESS <ul> <li>Introduction</li> <li>Project Management Process</li> <li>The Scope Statement</li> <li>Project Planning</li> <li>Project Scheduling</li> <li>Software Project Planning</li> <li>Critical Path Method</li> <li>Decision Making</li> </ul> <strong>WORK BREAKDOWN STRUCTURE</strong> <ul> <li>Introduction</li> <li>Work Breakdow n Structure (WBS)</li> <li>How to build a WBS (a serving suggestion)</li> <li>To Create Work Breakdown Structure</li> <li>From WBS to Activity Plan</li> <li>Estimating Time</li> </ul> <strong>PROJECT ESTIMATION AND RISK</strong> <ul> <li>Introduction</li> <li>Project Estimation</li> <li>Analyzing Probability & Risk</li> </ul> <strong>MANAGING RISK</strong> <ul> <li>Introduction</li> <li>Risk Analysis</li> <li>Risk Management</li> <li>Risk Analysis</li> <li>Managing Risks: Internal & External</li> <li>Internal and External Risks</li> <li>Critical Path Analysis</li> </ul> <strong>DATA MINING CONCEPTS</strong> <ul> <li>Introduction</li> <li>Data Mining</li> <li>Data Mining Background</li> <li>Inductive Learning</li> <li>Statistics</li> <li>Machine Learning</li> </ul> <strong>DATA MINING AND KDD</strong> <ul> <li>Introduction</li> <li>What is Data Mining?</li> <li>Data Mining: Definitions</li> <li>KDD vs. Data Mining</li> <li>Stages OF KDD</li> <li>Machine Learning vs. Data Mining</li> <li>Data Mining vs. DBMS</li> <li>Data Warehouse</li> <li>Statistical Analysis</li> </ul> <strong>ELEMENTS OF DATA MINING</strong> <ul> <li>Introduction</li> <li>Elements and uses of Data Mining</li> <li>Relationships & Patterns</li> <li>Data Mining Problems/Issues</li> <li>Goals of Data Mining and Know ledge Discovery</li> </ul> <strong>DATA INFORMATION AND KNOWLEDGE</strong> <ul> <li>Data, Information and Knowledge</li> <li>What can Data Mining do?</li> <li>How does Data Mining Work?</li> <li>Data Mining in a Nutshell</li> </ul> <strong>DATA MINING MODELS</strong> <ul> <li>Data Mining</li> <li>Data Mining Models</li> <li>Discovery of Association Rules</li> <li>Discovery of Classification Rules</li> </ul> <strong>DATA MINING ISSUES AND CHALLENGES</strong> <ul> <li>Data Mining Problems/Issues</li> <li>Other Mining Problems</li> <li>Data mining Application Areas</li> <li>Data Mining Applications-Case Studies</li> <li>Housing Loan Prepayment Prediction</li> <li>Mortgage Loan Delinquency Prediction</li> <li>Crime Detection</li> <li>Store-Level Fruits Purchasing Prediction</li> <li>Other Application Area</li> </ul> <strong>DM NEAREST NEIGHBOR AND CLUSTERING TECHNIQUES</strong> <ul> <li>Types of Knowledge Discovered during Data Mining</li> <li>Comparing the Technologies</li> <li>Clustering And Nearest-Neighbor Prediction Technique</li> </ul> <strong>DECISION TREES</strong> <ul> <li>What is a Decision Tree?</li> <li>Decision Trees</li> <li>Where to use Decision Trees?</li> <li>Tree Construction Principle</li> <li>The Generic Algorithm</li> <li>Guillotine Cut</li> <li>Over Fit</li> </ul> <strong>DECISION TREES - ADVANCED</strong> <ul> <li>Best Split</li> <li>Decision Tree Construction Algorithms</li> <li>Cart</li> <li>ID3</li> <li></li> <li>Chaid</li> <li>How the Decision Tree Works</li> <li>State of the Industry</li> </ul> <strong>NEURAL NETWORKS</strong> <ul> <li>Basics of Neural Networks</li> <li>Are neural networks easy to use?</li> <li>Business Scorecard</li> <li>Where to use Neural Networks</li> <li>Neural Networks for Clustering</li> <li>Neural Networks for Feature Extraction</li> <li>Applications Score Card</li> <li>The General Idea</li> </ul> <strong>NEURAL NETWORKS - ADVANCED</strong> <ul> <li>What is a Neural Network Pparadigm?</li> <li>Design decisions in architecting a neural network</li> <li>Different types of Neural Networks</li> <li>Kohonen feature Maps</li> <li>Applications of Neural Networks</li> <li>Knowledge Extraction Through Data Mining</li> </ul> <strong>ASSOCIATION RULES AND GENETIC ALGORITHM</strong> <ul> <li>Association Rules</li> <li>Basic Algorithms for Finding Association Rules</li> <li>Association Rules among Hierarchies</li> <li>Negative Associations</li> <li>Additional Considerations for Association Rules</li> <li>Genetic Algorithm</li> <li>Crossover</li> <li>Genetic Algorithms In detail</li> <li>Mutation</li> <li>Problem-Dependent Parameters</li> <li>Encoding</li> <li>The Evaluation Step</li> <li>Data Mining using GA</li> </ul> <strong>OLAP MULTIDIMENSIONAL DATA MODEL</strong> <ul> <li>On Line Analytical Processing</li> <li>OLAP Example</li> <li>What is OLAP?</li> <li>Who uses OLAP and WHY?</li> <li>Multi-Dimensional Views</li> <li>Complex Calculations</li> <li>Time Intelligence</li> </ul> <strong>OLAP CHARACTERISTICS</strong> <ul> <li>Definitions of OLAP</li> <li>Comparison of OLAP and OLTP</li> <li>Characteristics of OLAP: FASMI</li> <li>Basic Features of OLAP</li> <li>Special features</li> </ul> <strong>MULTIDIMENSIONAL AND MULTIRELATIONAL OLAP</strong> <ul> <li>Introduction</li> <li>Multidimensional Data Model</li> <li>Multidimensional versus Multi-relational OLAP</li> <li>OLAP Guidelines</li> </ul> <strong>OLAP OPERATIONS</strong> <ul> <li>Introduction</li> <li>OLAP Operations</li> <li>Lattice of Cubes, Slice and Dice Operations</li> <li>Relational Representation of the Data Cube</li> <li>DBMS</li> <li>Data Mining</li> <li>Mining Association Rules</li> <li>Classification by Decision Trees and Rules</li> <li>Prediction Methods</li> </ul> <strong>MOLAP/ ROLAP TOOLS</strong> <ul> <li>Categorization of OLAP Tools</li> <li>MOLAP</li> <li>ROLAP</li> <li>Managed Query Environment (MQE)</li> <li>Cognos PowerPlay</li> </ul> ', 'outline' => null, 'who_should_take_this_course' => null, 'career_path' => 'Data Mining and Warehousing Professional,Data Mining Professional,Warehousing Professional', 'eligibility' => null, 'school' => 'Vskills', 'keywords' => 'Data Mining,Warehousing,Data Mining and Warehousing certification', 'location' => 'Online', 'duration' => '1 To 2 Months', 'timing' => 'Flexible', 'cost' => null, 'discount' => '50% off through Laimoon!', 'eligibility_criteria' => null, 'job_matching_keywords' => null, 'boosted' => '0', 'lang_code' => 'pt', 'status' => 'active', 'auto_translated' => '1', 'objectives' => null, 'photo' => null, 'photo_cta' => null, 'video' => null ), 'Profile' => array() ), (int) 1 => array( 'Course' => array( 'id' => '91645', 'seeder_id' => '0', 'edited_seeder_id' => '0', 'edited_client_id' => '8102', 'title' => 'Flex 3: Rich Internet & AIR', 'external_link' => 'https://www.1training.org/course/flex-3-rich-internet-air-applications/', 'objectives' => null, 'photo_cta' => null, 'photo' => null, 'length' => '', 'next_session' => '', 'schedules' => null, 'duration' => 'Upto 11 Hours', 'base_duration' => '0', 'timing' => '', 'location' => 'Online', 'global_location_id' => '275', 'school' => '1TRAINING', 'logo' => '', 'certificate_diploma' => 'yes', 'image' => '', 'brochure_url' => null, 'video' => '', 'cost' => '', 'price' => '17', 'price_enquiry' => '0', 'course_status' => 'Paid', 'base_price' => '23', 'nondiscounted_base_price' => '153.333333333', 'currency' => 'GBP', 'discount' => '85% off through Laimoon!', 'free_trial_text' => null, 'laimoon_offer' => '1', 'summary' => '<strong>Overview</strong><br /> <br /> <strong>Flex 3</strong> is a much loved cross platform, open source framework for creating rich Internet applications and Adobe AIR™ applications. 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With this excellent discount course you can expect professional qualification, which will enable you to enhance your CV in no time, and for less!<br /> <br /> <strong>What skills am I going to get from this course?</strong> <ul> <li>Learn how to effectively architect applications that follow best practices to produce maintainable, re-useable software.</li> <li>Discover how to easily connect your Flex and AIR applications to server side data sources as well as how to manage data effectively on the client following best practices.</li> <li>Understand how to make the most of and extend the Flex component framework using your knowledge of the Flex class hierarchy.</li> <li>Find out how to draw using ActionScript 3 and how to apply this program to customize your components using CSS.</li> <li>Learn how to create native application windows, plus uncover how to access the file system in AIR applications and how to upload a file from a rich internet application.</li> </ul> <strong>Course Duration:</strong><br /> <br /> Learners will have <strong>365 days access</strong> to their chosen course. 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Hiring company
Canonical
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AED 208
AED 485Duração: 1 To 2 Months -
Flex 3: Rich Internet & AIR 1TRAININGAED 78
AED 563Duração: Upto 11 Hours
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