Fundamentals of Data Science and Machine Learning Self-Study CBT

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Seller: elearning4u (12) 100%, Location: DOCKLANDS, LONDON, Ships to: Worldwide, Item: 273632798191 MORE SKILLS. MORE POWER. MORE MONEY. BOOST YOUR CAREER WITH DATA SCIENCE AND MACHINE LEARNING.HONE YOUR SKILLS AND UPGRADE YOUR STATUS AND INCOME. EARN MINIMUM £70K WITH YOUR DATA SCIENCE AND MACHINE LEARNING SKILLS.VERY GOOD INTERACTIVE TRAINING MATERIAL (CBT) WITH SOFTWARE SIMULATIONS AND REAL-LIFE BASED SCENARIOS. PACKED WITH TASKS, ACTIVITIES AND EXERCISES.PERFECT INTERACTIVE SELF-TEACH TRAINING COURSE FOR DATA MINERS, ANALYTICS DEVELOPERS, DATA WAREHOUSING DEVELOPERS, BI CONSULTANTS AND DEVELOPERS WHO WORK WITH EITHER ORACLE, SAP, MICROSOFT OR IBM BI TOOLS LOOKING TO UPSKILL TO A DATA SCIENCE ENVIRONMENT. FUNDAMENTALS OF DATA SCIENCE AND MACHINE LEARNING SELF-STUDY CBTHow This Course Is OrganisedThis course is designed to help you understand the core principles of data science, and to learn techniques and technologies that you can use to explore and visualize data. The Fundamentals of Data Science and Machine Learning course teaches you about the most effective Data Science techniques, and gain practice implementing them and getting them to work for yourself. More importantly, you'll learn about not only the theoretical underpinnings of Foundations of Data Science and Machine Learning, but also appreciate the practical know-how needed to quickly and powerfully apply these techniques to new problems. Demand for Data Science and machine learning talent is exploding. According to Glassdoor, being a data scientist is the best job in America; with a median base salary of $110,000 and thousands of job openings at a time. Learn Data Science with experts from WebLearning Publishing partnering with Oracle, IBM and Microsoft to help develop your career as a data scientist. With the Data Science course, you will learn how to build and derive insights from Data Science models. You will learn key concepts in data acquisition, preparation, exploration and visualization along with examples on how to build a data science solution using Microsoft Azure Machine Learning and Opensource Tools: R or Python. The WebLearning hands-on series reduces the time spent investigating what steps are required to perform a task. Because the step-by-step solutions are built for practical real world situations, not only is knowledge gained through valuable hands-on experience, but also the solutions presented may then be used as the foundation for production implementation, dramatically reducing time to deployment. AudienceProject Managers of teams of business intelligence, analytics, and big data professionalsBusiness and Data Analysts Data and database professionalsBusiness Intelligence and Data Warehousing ProfessionalsData Engineers and ETL DevelopersData Science and big data developers PrerequisitesTo complete this course successfully, you need a basic knowledge of mathematics, including linear algebra. Additionally, some programming experience, ideally in either R or Python, is assumed. Objectives:Describe key concepts of Data Science and Machine LearningUnderstand Open Source Data Science tools including R and PythonUnderstand Open Source Machine learning Tools and PlatformsUnderstand Commercial Data Science tools including Microsoft Azure Machine LearningDevelop Data Science solutions using RDevelop R solutions using Microsoft AzureMLDevelop Data Science solutions using Microsoft Azure ML StudioDevelop Machine solutions using Microsoft Azure ML StudioPrepare data for predictive modellingVisualize and explore dataCreate supervised and unsupervised machine learning models Course Outline Introduction to Data Science Overview of Data ScienceWhat Is Data Science?The Data Science ProcessOverview of the Data Science ProcessExample of the Data Science Process Data Science TechnologiesIntroduction to Data Science TechnologiesIntroduction to Jupyter NotebooksAccessing Jupyter NotebooksAccessing Azure NotebooksAzure Machine Learning StudioSetting Up Azure MLExploring Azure ML StudioUsing Code in Azure MLOverview of SQL Server R ServicesOverview of Oracle R (ORE) Probability and Statistics for Data Science Probability and Random VariablesOverview of Probability and Random Variables Introduction to Probability Discrete Random Variables Discrete Probability Distributions Binomial Distribution Examples Poisson Distributions Continuous Probability Distributions Cumulative Distribution Functions Central Limit Theorem Introduction to StatisticsOverview of StatisticsDescriptive StatisticsSummary StatisticsViewing Summary Statistics Z-ScoresCorrelationViewing CorrelationSimpson's Paradox Simulation and Hypothesis Testing Simulation Introduction to SimulationSimulationPerforming a Simulation Hypothesis TestingOverview of Hypothesis TestingIntroduction to Hypothesis TestingZ-Tests, T-Tests, and Other TestsHypothesis Test ExamplesType 1 and Type 2 ErrorsConfidence IntervalsHypothesis TestingMisconceptions About Hypothesis Testing Exploring and Visualizing Data Exploring DataIntroduction to Data Exploration Data and Data Frames Getting Started with Data Frames Basic Data Frame Manipulation Computing Columns in Data Frames Chaining Data Frame Operations Data Frames in Azure ML Visualizing DataOverview of Data Visualization Introduction to Data Visualization Getting Started with Univariate Plots Two-Dimensional Plots Aesthetics for Multidimensional Plots Faceting Plots Plotting in Azure ML Experiments Data Cleansing and Manipulation Data Ingestion and FlowOverview of Data Ingestion and FlowData Flow in Azure MLJoining Data SetsDemo: Ingesting and Joining DataDemo: Joins in R or PythonMetadataWorking with Metadata Data CleansingIntroduction to Data CleansingOverview of Data CleansingMissing and Repeated ValuesDemo: Handling Missing and Repeated ValuesFeature EngineeringOutliers and ErrorsFinding OutliersHandling Outliers in Azure MLCleaning Data with R or PythonIntroduction to Data ScalingScaling Data in Azure MLScaling Data in R or Python Introduction to Machine Learning Getting Started with Machine LearningMachine Learning OverviewIntroduction to Machine Learning ClassificationEvaluating ClassifiersCreating a Classification Model in Azure ML Regression Evaluating Regression Models Creating a Regression Model ClusteringK-Means Clustering Publishing a Machine Learning Web ServiceIntroduction to Azure ML Web ServicesOverview of Publishing a Web ServicePublishing a Web ServiceConsuming a Web ServiceCustom Code Considerations NOTE: THIS COURSE IS ALSO AVAILABLE IN SELF-STUDY TRAINING GUIDE, E-LEARNING OR DISTANCE LEARNING FORMATS. FEEL FREE TO ASK IF YOU PREFER DISTANCE, E-LEARNING OR TRAINING GUIDE FORMATS. PRICES DIFFER What is Computer Based Training - CBT?Computer Based Training - CBT's are usually interactive with Software Simulations (behaves like you're using the real thing on the PC, therefore you don't even need the real software installed on your machine) and sometimes BUT NOT ALWAYS with voice. This Publisher's CBT Titles do NOT have voice. Generally, CBT's tend to be more expensive. This Publisher's CBT Titles are NOT based on Flash. They are based on the latest technology which uses the: See It, Do It, and Try It learning paradigm. A very powerful new way of learning. All CBT and Courseware Learning formats are delivered with FULL LICENCE KEY. Today's competitive business environment and frequent software updates by software vendors demands rapid skill acquisition. WebLearning Publishing helps you keep up-to-date by delivering quality Interactive Self-Study in CBT format. These factors give CBT's a clear advantage over conventional, inconvenient and expensive Classroom and Hard-copy print training methods. CBT's not only offers the advantage in terms of convenience and lower cost, but it also facilitates improved subject-matter comprehension. NOTE: WebLearning Publishing CBT products are now delivered with FULL LICENCE KEY. The WebLearning unique Methodology All WebLearning® CBT and Courseware courses are based on the latest materials available at the time of publishing and are regularly updated every 3 months with FREE UPGRADES to the LATEST EDITION: ANEW, very effective and proven way of learning. FACT: Material retention with CBT’S are 45% better than with conventional training methodsYour learning curve with CBT is 25%-55% less than conventional methodsThe cost of CBT training is over 65% less than Classroom trainingCBT’S are self pacing, interactive and simulate the actual software being studied TRY WEBLEARNING E-LEARNING DEMOS TODAY:: CLICK HERELOOKING FOR A Training Guide DEMO? THEN CLICK HERELOOKING FOR A CBT DEMO? THEN CLICK HERE Condition: New, Compatible Product: Self-Study Computer Based Training - CBT, Format: Computer Based Training - CBT On CD-ROM Media Only, Language: English, Publisher: WebLearning Publishing, Licence: 1 User Licence, Training Category: SELF-STUDY TRAINING, Licence Key Required?: YES, Compatible Brand: Self-Study CD-ROM, Compatible Model: Self-Study CBT

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