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Free Download Microsoft Excel - Data Analytics Power Query and PivotTables Last updated: 4/2020 Created by: Kyle Pew,Office Newb MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch Level: All | Genre: eLearning | Language: English + subtitle | Duration: 77 Lectures ( 5h 55m ) | Size: 6.11 GB Clean, Transform and Summarize Microsoft Excel Data Quickly with Excel's Power Query and PivotTable Tools What you'll learn Create Connections and Discover External Data Sources Clean, Transform and Prepare Data Sets for Reporting within Excel Transform Raw Data with Power Query Calculations Create Consistentcy in Data with Power Querys Powerful Toolset Streamline Data Work by Automating with Power Query Steps Create Clean Data Interfaces with Power Query Parameters and Excel Variables Requirements Microsoft Excel 2016 or newer to follow along Power Query is not Available in the MAC release of Excel Power Query is available through a free download for Excel 2010 and 2013. Best if you have Excel 2016 or newer. Description Microsoft Excel's Power Query tool is the biggest feature Microsoft has added to Excel since PivotTables. Seriously, no joke. Read on to learn more about Excel Power Query and how you'll save loads of time as you take advantage of this powerful feature.In Excel 2016, 2019 and Office 365, Power Query is built directly in the Excel interface through the GET AND TRANSFORM command on the Data tab. (Power Query is NOT available on the MAC release of Excel)Power Query is available on Excel 2010 and 2013 through a free download from Microsoft as described in the course.Lets face it, retrieving, cleaning and transforming data to report on can take hours of precious time. With Excel Power Query you can eliminate repetitive tasks freeing your time for other important tasks, like lunch and going home on time. Excel Power Query removes the hassle and complex formulas of manual tasks such as:Finding the Data each time you need a reportCleaning Columns of DataSplitting or Joining Column ValuesRemoving unnecessary characters and extra spacesFormatting data correctlyFiltering data needed for the reportCombining multiple Datasets into a master listManipulating the data layout to work with other tools, i.e. Excel PivotTables and ChartsIn just 3 easy steps, you'll have a final report ready for presentation and your next raise.Get DataTransform/Clean DataReport on DataOnce you've got it all setup with Excel Power Query all you need to do is hit the Refresh button to update the report with next weeks data. Microsoft Power Query remembers all the steps you performed to get, transform and clean the data all you do is refresh and your report is updated.Sounds all too easy, right? Enroll now and let me guide you through Excel Power Query and you'll quickly be on your way to harnessing the power of managing and reporting on data with Excel Power Query.This Excel Power Query Course Includes:6+ hours of video contentDownloadable exercise files to follow alongAccess to the instructor through the QA section Who this course is for Microsoft Excel users looking to speed up their time managing and reporting on data Microsoft Excel users looking to learn the hottest tool in Excel since PivotTables were introduced Homepage: https://www.udemy.com/course/microsoft-excel-data-analytics-power-query-and-pivottables/ Rapidgator https://rg.to/file/bd0d6cd72cd8f2c8f9a347913bef5ccf/escku.Microsoft.Excel..Data.Analytics.Power.Query.and.PivotTables.part1.rar.html https://rg.to/file/9d259f0d4bf2a4672eb4e8320b7659c9/escku.Microsoft.Excel..Data.Analytics.Power.Query.and.PivotTables.part2.rar.html https://rg.to/file/38b66f7ce55a23b1fd3aacdb25bf85c8/escku.Microsoft.Excel..Data.Analytics.Power.Query.and.PivotTables.part3.rar.html https://rg.to/file/4378f71dd9ba4894fbc47d38a6412947/escku.Microsoft.Excel..Data.Analytics.Power.Query.and.PivotTables.part4.rar.html https://rg.to/file/77d979eeabb2480a4831c3596e64ddab/escku.Microsoft.Excel..Data.Analytics.Power.Query.and.PivotTables.part5.rar.html https://rg.to/file/c83dd47752b4f6eca8572b24fae859e8/escku.Microsoft.Excel..Data.Analytics.Power.Query.and.PivotTables.part6.rar.html https://rg.to/file/9477ffa8fcac0e667425514dfb819c5f/escku.Microsoft.Excel..Data.Analytics.Power.Query.and.PivotTables.part7.rar.html Fikper Free Download https://fikper.com/5E6KVcp4jr/escku.Microsoft.Excel..Data.Analytics.Power.Query.and.PivotTables.part1.rar.html https://fikper.com/kCwVnB3RAY/escku.Microsoft.Excel..Data.Analytics.Power.Query.and.PivotTables.part2.rar.html https://fikper.com/HdR2VrD7b7/escku.Microsoft.Excel..Data.Analytics.Power.Query.and.PivotTables.part3.rar.html https://fikper.com/qsjmRhmBaB/escku.Microsoft.Excel..Data.Analytics.Power.Query.and.PivotTables.part4.rar.html https://fikper.com/xwLLCnFx6Y/escku.Microsoft.Excel..Data.Analytics.Power.Query.and.PivotTables.part5.rar.html https://fikper.com/CUdzYAQQ3X/escku.Microsoft.Excel..Data.Analytics.Power.Query.and.PivotTables.part6.rar.html https://fikper.com/nvOeamyjSS/escku.Microsoft.Excel..Data.Analytics.Power.Query.and.PivotTables.part7.rar.html No Password - Links are Interchangeable

Free Download Google Analytics Simplified - 5 Steps To Track What Matters Published: 3/2025 MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz Language: English | Size: 305.33 MB | Duration: 0h 30m Lost in GA4? Discover the 5 step system to track what matters - without getting overwhelmed. What you'll learn Navigate GA4 with confidence - Understand key reports and metrics Find your best marketing channels - See where your visitors are coming from Optimise top pages - Improve engagement and conversions Fix problem areas - Identify where visitors drop off and why Understand your audience - Learn who they are and what they care about Turn data into action - Use insights to guide smarter marketing decisions Requirements This course is designed for beginners-no prior experience with Google Analytics or data tracking is required Description Are you getting lost in GA4 reports? You open GA4, and it feels like a maze of graphs and confusing metrics. You just want to know:Where are my best customers coming from?What's working in my marketing-and what's a waste of money?Why are people visiting my site but not converting?Instead, you're stuck in data overwhelm, clicking through reports that feel like they were designed by robots. What if you could cut through the noise and track exactly what matters-without the confusion? That's where this course comes in.What you'll learnIn just 5 simple steps, you'll learn exactly how to use GA4 to make better marketing decisions.Find your best traffic sources → see which channels drive real resultsOptimise your top pages → discover which pages perform well and how to improve themFix drop-off points → identify where you're losing potential customersUnderstand who your users are → get insights into demographics and behaviorTurn data into a strategy → build an action plan to grow your business with confidenceNo unnecessary reports. Just the key insights you need to make smarter marketing moves.Who this course is for Marketers and business owners (new to GA4) who need a simple way to track performanceFreelancers and consultants (new to GA4) who want to offer data-driven strategies to clientsBeginners in GA4 who feel stuck, overwhelmed, or frustrated with analyticsWhy learn GA4 with me?Hi, I'm Liz, a marketing professional with over 10 years of experience. I struggled with GA4 when I first started-it felt overwhelming and overly technical. But after years of practice, it finally clicked. I designed this course to teach GA4 the way I wish someone had taught me-without jargon, without complexity, and with a clear, step-by-step approach.By the end of this course, you'll have:Confidence in GA4-no more second-guessing dataA clear understanding of which GA4 reports to use to track what drives resultsAn action plan to optimise your website and marketing strategyReady to master GA4 without the overwhelm?Enroll now and learn how to track, analyse, and optimise your marketing in just 5 simple steps.No unnecessary reports. Just the insights you actually need! Overview Section 1: Introduction Lecture 1 Why this course will change the way you see data Section 2: Find your best marketing channels Lecture 2 Find your best marketing channels Lecture 3 Extra insights: What are UTM tags? Section 3: Optimise your best-performing pages Lecture 4 Optimise your best-performing pages Section 4: Capture key insights to fix underperforming areas Lecture 5 Capture key insights to fix underperforming areas Section 5: Understand your audience Lecture 6 Understand your audience Section 6: Strategise and take action Lecture 7 Strategise and take action Lecture 8 Extra insights: Fine tune your ad spend with a custom exploration report This course is perfect for beginners, business owners, and marketers who want a simple, step-by-step approach to GA4-no technical expertise required. Homepage: https://www.udemy.com/course/google-analytics-simplified-5-steps-to-track-what-matters/ DOWNLOAD NOW: Google Analytics Simplified - 5 Steps To Track What Matters Rapidgator https://rg.to/file/136b48fd756c6bc575df9b95eb40ed2d/hbyyf.Google.Analytics.Simplified.5.Steps.To.Track.What.Matters.rar.html Fikper Free Download https://fikper.com/dHmhZx6ClT/hbyyf.Google.Analytics.Simplified.5.Steps.To.Track.What.Matters.rar.html No Password - Links are Interchangeable

Free Download Advanced AI Analytics on AWS - Amazon Bedrock, Q, SageMaker Data Wrangler, and QuickSight Released 03/2025 With Noah Gift, Pragmatic AI Labs MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch Skill Level: Advanced | Genre: eLearning | Language: English + subtitle | Duration: 1h 10m 35s | Size: 131 MB Learn to leverage AI-enhanced analytics tools like Amazon Bedrock, QuickSight, and SageMaker to enhance traditional analytics methods and optimize performance. Course details Discover how to elevate your data analytics skills using AI-enhanced tools on AWS. In this course, MLOps expert Noah Gift shows you how to integrate Amazon Bedrock for advanced code analysis and Amazon SageMaker Data Wrangler for efficient data processing. Find out how to use Amazon Q and QuickSight. Explore practical examples and real-world scenarios where AI can optimize your existing workflows and reduce costs significantly. Learn how to automatically detect anomalies, generate visual stories, and create a comprehensive data narrative. Step through the methodology for leveraging AI to enhance traditional processes and improve overall performance. This course provides valuable insights into making your analytics pipeline more efficient and cost-effective. When you complete the course, you'll be equipped to apply AI tools to drive decision-making and achieve better business outcomes. This course was Created by: Noah Gift and Pragmatic AI Labs. We are pleased to host this training in our library. Homepage: https://www.linkedin.com/learning/advanced-ai-analytics-on-aws-amazon-bedrock-q-sagemaker-data-wrangler-and-quicksight Fileaxa https://fileaxa.com/kznen73ejsvi/xdjnj.Advanced.AI.Analytics.on.AWS.Amazon.Bedrock.Q.SageMaker.Data.Wrangler.and.QuickSight.rar TakeFile https://takefile.link/d8jop561lixw/xdjnj.Advanced.AI.Analytics.on.AWS.Amazon.Bedrock.Q.SageMaker.Data.Wrangler.and.QuickSight.rar.html Rapidgator https://rg.to/file/d5a5103c0c8e0fe8cba6f7d79c47925b/xdjnj.Advanced.AI.Analytics.on.AWS.Amazon.Bedrock.Q.SageMaker.Data.Wrangler.and.QuickSight.rar.html Fikper Free Download https://fikper.com/eTsAbGWqfC/xdjnj.Advanced.AI.Analytics.on.AWS.Amazon.Bedrock.Q.SageMaker.Data.Wrangler.and.QuickSight.rar.html No Password - Links are Interchangeable

Free Download Statistics For Data Science & Business Analytics by Mandar Zarekar Published: 3/2025 MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz Language: English | Size: 1.66 GB | Duration: 4h 58m Learn key statistical concepts and techniques to analyze data with IIM Ahmedabad Alumnus What you'll learn Better understanding of key concepts and properties in statistics Understand the connection of key concepts with real life scenarios Learn basic probability concepts used widely in Data science, Analytics, medicinal researches and other imprtant fields Learn Descriptive and Inferential Statistics and it's real life application Learn everything from Probabiity to Hypothesis testing and different analysis Requirements Anyone who is eager to learn Statistics with real life applications Anyone who is looking forward to expand the horizons of understanding of statistics No prior knowledge of Statistics required Description Master the Fundamentals of Statistics and Elevate Your Data Analysis Skills!Are you looking to build a strong foundation in statistics for data science, analytics, and decision-making? This beginner-to-intermediate level course is designed to simplify complex statistical concepts with real-world applications, helping you gain confidence in data analysis, hypothesis testing, and regression modeling.What You'll Learn: Module 1: Introduction to Statistics - Understand the role of statistics in data science types of datakey distinctions between descriptive & inferential statistics.Module 2: Descriptive Statistics - Learn about measures of central tendency (mean, median, mode)Measure of dispersion (range, variance, standard deviation)visualize data using histograms, box plots, and scatter plots.Module 3: Probability Basics - Master probability conceptsconditional probabilityBayes' theorem Module 4: Probability Distributions - Understanding Discrete and Continuous Probability distributions Binomial DistributionPoisson DistributionNormal DistributionExponential DistributionCentral Limit Theorem(CLT)Module 5: Inferential Statistics - Dive into sampling techniquesWhat is confidence intervalshypothesis testing Types of errorst-tests & z-testsUnderstanding chi-square testModule 6: Regression & Correlation - ( Coming Soon)Explore correlation analysis, simple & multiple linear regression, R-squared value, and the line of best fit to make data-driven predictions. Who Is This Course For? Aspiring Data Scientists, Business Analysts, and ResearchersMBA & Analytics Students looking to strengthen their statistical foundationStudents & professionals in Finance, Marketing, and Business Strategy Anyone looking to interpret and analyze data effectively Why Take This Course?Beginner-friendly explanations with real-world examplesNo prior advanced math required-concepts explained intuitivelyHands-on learning with statistical tools and visualization techniquesEssential for careers in data-driven decision-makingBy the end of this course, you'll be able to confidently apply statistical techniques to analyze data, test hypotheses, and build predictive models-a must-have skill set for any data professional!Ready to turn data into actionable insights? Enroll now and master statistics for real-world decision-making! Overview Section 1: Introduction to Statistics Lecture 1 What is Statistics? Lecture 2 Types of Data Lecture 3 What is Descriptive Statistics and Inferential Statistics? Section 2: Descriptive Statistics Lecture 4 Measures of Central Tendancy - Mean, Median and Mode Lecture 5 Measures of Dispersion Lecture 6 Understanding Standard Deviation Lecture 7 What is Co-efficient of Variation? Lecture 8 What are Quartiles and Percentiles? Lecture 9 Data Visualization with Graphs Section 3: Probability Basics Lecture 10 Introduction to Probability Lecture 11 Conditional Probability Lecture 12 Bayes' Theorem Section 4: Probability Distributions Lecture 13 Introduction to Probability Distributions Lecture 14 Binomial Distribution Lecture 15 Poisson Distribution Lecture 16 Normal Distribution Lecture 17 Exponential Distribution Lecture 18 What is Central Limit Theorem? Section 5: Inferential Statistics Lecture 19 Sampling and Sampling techniques Lecture 20 What is Confidence Interval? Lecture 21 What is Hypothesis Testing? Lecture 22 Types of errors in Hypothesis testing. Lecture 23 Understanding T tests and Z tests Lecture 24 Understanding Chi-Square Test Lecture 25 Chi-Square Example solving on Excel Students planning to get into Data Science and Analytics,Students of Psychology who are interested in building strong foundation in statistics,Analytics or Data Science professionals who are interested in improving statistical understanding,Beginners of stastitics planning to get into further studies Homepage: https://www.udemy.com/course/statistics-for-data-science-business-analytics/ DOWNLOAD NOW: Statistics For Data Science & Business Analytics by Mandar Zarekar Rapidgator https://rg.to/file/801bdbf280f1b64f614a602098dec445/dnopd.Statistics.For.Data.Science..Business.Analytics.by.Mandar.Zarekar.part1.rar.html https://rg.to/file/ee7e8db341cb4c33bf5100b60068cb63/dnopd.Statistics.For.Data.Science..Business.Analytics.by.Mandar.Zarekar.part2.rar.html Fikper Free Download https://fikper.com/JKrTD4QH5W/dnopd.Statistics.For.Data.Science..Business.Analytics.by.Mandar.Zarekar.part1.rar.html https://fikper.com/ie34noJ8fp/dnopd.Statistics.For.Data.Science..Business.Analytics.by.Mandar.Zarekar.part2.rar.html No Password - Links are Interchangeable

Free Download Starting Data Analytics with Generative AI and Python, Video Edition Released 11/2024 By Artur Guja, Dr. Marlena Siwiak, and Dr. Marian Siwiak MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch Genre: eLearning | Language: English | Duration: 12h | Size: 2.22 GB Accelerate your mastery of data analytics with the power of ChatGPT. Whether you're a data novice or an experienced pro looking to do more work, faster, Starting Data Analytics with Generative AI and Python is here to help simplify and speed up your data analysis! Written by a pair of world-class data scientists and an experienced risk manager, the book concentrates on the practical analytics tasks you'll do every day. Inside Starting Data Analytics with Generative AI and Python you'll learn how to Write great prompts for ChatGPT Perform end-to-end descriptive analytics Set up an AI-friendly data analytics environment Evaluate the quality of your data Develop a strategic analysis plan Generate code to analyze non-text data Explore text data directly with ChatGPT Prepare reliable reports In Starting Data Analytics with Generative AI and Python you'll learn how to improve your coding efficiency, generate new analytical approaches, and fine-tune data pipelines-all assisted by AI tools like ChatGPT. For each step in the data process, you'll discover how ChatGPT can implement data techniques from simple plain-English prompts. Plus, you'll develop a vital intuition about the risks and errors that still come with these tools. About the Technology If you have basic knowledge of data analysis, this book will show you how to use ChatGPT to accelerate your essential data analytics work. This speed-up can be amazing: the authors report needing one third or even one quarter the time they needed before. About the Book You'll find reliable and practical advice that works on the job. Improve problem exploration, generate new analytical approaches, and fine-tune your data pipelines-all while developing an intuition about the risks and errors that still come with AI tools. In the end, you'll be able to do significantly more work, do it faster, and get better results, without breaking a sweat. Assuming only that you know the foundations, this friendly book guides you through the entire analysis process-from gathering and preparing raw data, data cleaning, generating code-based solutions, selecting statistical tools, and finally creating effective data presentations. With clearly-explained prompts to extract, interpret, and present data, it will raise your skills to a whole different level. What's Inside Write great prompts for ChatGPT Perform end-to-end descriptive analytics Set up an AI-friendly data analytics environment Evaluate the quality of your data Develop a strategic analysis plan Generate code to analyze non-text data Explore text data directly with ChatGPT Prepare reliable reports About the Reader About the Authors Authors Artur Guja, Dr. Marlena Siwiak, and Dr. Marian Siwiak are experienced data scientists with backgrounds in business, scientific research, and finance. The technical editor on this book was Mike Jensen. Rapidgator https://rg.to/file/99a34600c92cb250dcc2c822ca96010d/rnegn.Starting.Data.Analytics.with.Generative.AI.and.Python.Video.Edition.part1.rar.html https://rg.to/file/869b6cbde06a8852a9d55630dac76802/rnegn.Starting.Data.Analytics.with.Generative.AI.and.Python.Video.Edition.part2.rar.html https://rg.to/file/fa3a94005e30f4fc26491f8af2ba1d61/rnegn.Starting.Data.Analytics.with.Generative.AI.and.Python.Video.Edition.part3.rar.html Fikper Free Download https://fikper.com/zcB23zauG3/rnegn.Starting.Data.Analytics.with.Generative.AI.and.Python.Video.Edition.part1.rar.html https://fikper.com/TispKhcWZe/rnegn.Starting.Data.Analytics.with.Generative.AI.and.Python.Video.Edition.part2.rar.html https://fikper.com/iThSBkgMOC/rnegn.Starting.Data.Analytics.with.Generative.AI.and.Python.Video.Edition.part3.rar.html : No Password - Links are Interchangeable

Free Download Excel Data Analytics Mastery - From Basics to Advanced Published: 3/2025 Created by: Abdul Wahab MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch Level: All | Genre: eLearning | Language: English | Duration: 10 Lectures ( 3h 16m ) | Size: 1.6 GB Data to Decisions: Mastering Excel for Real-World Insights What you'll learn Learn how to clean, process, and interpret data using Excel, ensuring even non-technical learners can confidently handle real-world datasets. Understand data trends and patterns to make informed decisions, empowering you with the art of transforming raw data into actionable insights. Acquire practical skills in managing with Excel and creating compelling visualizations. Combine techniques from various platforms to build robust, end-to-end data analysis projects, bridging the gap between technical and non-technical perspectives. Requirements Familiarity with using a computer and navigating files is enough; no advanced skills required. Whether you're a beginner or looking to enhance your skills, a keen interest in data analysis is all you need. This course is designed for both technical and non-technical learners, so no previous coding or analytics experience is necessary. Description This comprehensive course is your gateway into the dynamic world of data analysis using Excel, where you'll learn to transform raw data into clear, actionable insights. Designed for both beginners and professionals, the curriculum covers essential techniques in data cleaning, organization, analysis, and visualization using Excel's powerful features. You'll gain hands-on experience working with real-world datasets, enabling you to apply your skills in business, finance, marketing, and other data-driven fields.Throughout the course, you'll build a strong foundation in analytical thinking and data-driven decision-making by mastering PivotTables, Power Query, Power Pivot, advanced formulas, and data validation. You'll learn how to identify trends, uncover hidden patterns, and create dynamic reports and dashboards to support strategic business decisions. Additionally, you'll explore best practices for ensuring data accuracy and efficiency, helping you streamline your workflow and enhance productivity.By integrating theoretical concepts with hands-on projects, this course ensures you gain practical expertise in Excel functions, data modeling, automation with macros, and interactive visualizations. Whether you're looking to kickstart your career in data analytics or enhance your existing skill set, this course offers a balanced blend of technical proficiency and strategic insight. You'll also develop problem-solving abilities that allow you to manipulate complex datasets with confidence and precision.By the end of this course, you'll be equipped to confidently analyze, interpret, and present data using Excel, helping you make data-driven decisions with ease. Start your journey today and unlock the full potential of Excel in data analytics! Who this course is for Non-Technical Learners: If you're new to coding or data analysis, you'll appreciate the step-by-step guidance in using Excel and PowerBI to unlock the power of your data. Aspiring Data Analysts: Ideal for students, career changers, or professionals aiming to enhance their analytical capabilities with practical, hands-on projects. Business Decision Makers: Managers and analysts looking to translate data into strategic insights will find value in learning methods that bridge the gap between raw data and actionable business intelligence. Homepage: https://www.udemy.com/course/excel-data-analytics-mastery/ Rapidgator https://rg.to/file/ca900faf5108181dd4056cc77afbb780/cjrnv.Excel.Data.Analytics.Mastery.From.Basics.to.Advanced.part1.rar.html https://rg.to/file/213c0a8c4bb1b70ac6a1270d11583e85/cjrnv.Excel.Data.Analytics.Mastery.From.Basics.to.Advanced.part2.rar.html Fikper Free Download https://fikper.com/JJ3jjt8iUb/cjrnv.Excel.Data.Analytics.Mastery.From.Basics.to.Advanced.part1.rar.html https://fikper.com/c1cY7ZOmt6/cjrnv.Excel.Data.Analytics.Mastery.From.Basics.to.Advanced.part2.rar.html : No Password - Links are Interchangeable

Free Download Rust Data Engineering and Analytics - Production Ready 2025 Published: 3/2025 MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch Language: English | Duration: 1h 10m | Size: 641 MB Rust Data Engineering / Analytics - Automated Pipelines Ready for Production with Docker and Elusion library What you'll learn Data Engineering and Data Analysis Data Wrangling with DataFrame API Functions Query OPTIMIZATION with VIEWS and CACHING REST API, Azure BLOB storage Pipeline Scheduling Production Depoloyment with Docker Requirements No experience nor Rust knowledge needed Basic SQL and DataFrame knowledge needed Description Level Up Your Data Game: Build Production-Ready Pipelines with RustIn this course you will learn how to create Automated Data Engineering / Analytics Pipeline that is ready to be pushed into production. You will learn how to use the most feature rich Rust DataFrame library - Elusion - to accomplish data cleaning, aggregations, pivoting and more...Tired of clunky data pipelines? Get ready to supercharge your data engineering skills with Rust's most powerful DataFrame library!What You'll Master:Lightning-fast data processing with ElusionProfessional-grade data cleaning techniquesAdvanced aggregations that reveal hidden insightsDynamic pivoting that transforms your analysisProduction-ready pipeline architecture that scalesWhy This Course Matters:The demand for efficient, reliable data pipelines has never been higher. While Python solutions struggle with performance bottlenecks, Rust offers unprecedented speed and memory safety. Elusion brings the power of Rust to data engineering, enabling you to build systems that process millions of rows in seconds.Course Highlights:Real-world Projects: Apply your skills to industry-relevant challengesPerformance Optimization: Learn how to squeeze every ounce of performance from your data operationsError Handling: Build robust pipelines that gracefully manage exceptionsDeployment Strategies: Master CI/CD integration for your data workflowsMonitoring & Maintenance: Implement logging and alerting to keep your pipelines healthyWho Should Attend:Whether you're a data engineer looking to level up your toolkit, a software developer curious about data processing, or a data scientist tired of waiting for analyses to complete, this course will transform how you work with data.Stop wrestling with inefficient tools. Join us and build blazing-fast, rock-solid data pipelines that are ready for the real world from day one.Elusion + Your Skills = Data Engineering Mastery Who this course is for Data Engineers and Data Analysts Rust Beginners Homepage: https://www.udemy.com/course/rust-data-engineering-analytics-elusion/ Rapidgator https://rg.to/file/174cd27cf7c0a5c3b60ac4bf0aae3dcb/svzfd.Rust.Data.Engineering.and.Analytics..Production.Ready.2025.rar.html Fikper Free Download https://fikper.com/z7nIssUUVq/svzfd.Rust.Data.Engineering.and.Analytics..Production.Ready.2025.rar.html : No Password - Links are Interchangeable

Released: 02/2025 Free Download Duration: 1h 47m | .MP4 1280x720, 30 fps(r) | AAC, 48000 Hz, 2ch | 260 MB Level: Intermediate | Genre: eLearning | Language: English Organizations in nearly every industry are seeking and hiring data scientists, but even though data analytics skills are highly valued, individuals with this skill set can't make an impact unless middle and senior management know how to leverage analytics for the long-term benefit of their organization. The challenge is that most of the people overseeing advanced analytics don't have backgrounds in data science themselves. In this course, Keith McCormick shows executives who aren't fluent in data analytics how to hire data science professionals, manage data science teams, and transform their business with effectively deployed advanced analytics. Learn how to actively parti[beeep]te in a discussion about which type of analytics may address your business problem, have a better appreciation of problem-solving from a data scientist's point of view, think strategically about hiring and technology for advanced analytics, and consider various options for organizational structure and the enterprise-wide management of analytics. Homepage: https://www.linkedin.com/learning/predictive-analytics-essential-training-for-executives-25301424 Rapidgator https://rg.to/file/901dc69a1e5d7340dcd561f2b2633bc5/hbcul.Predictive.Analytics.Essential.Training.for.Executives.2025.rar.html Fikper Free Download https://fikper.com/gNKjvzCKlK/hbcul.Predictive.Analytics.Essential.Training.for.Executives.2025.rar.html : No Password - Links are Interchangeable

Free Download Learning Elastic Stack for Data Analytics & Cyber Security Published: 3/2025 Created by: Motasem Hamdan MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz, 2 Ch Level: Beginner | Genre: eLearning | Language: English | Duration: 9 Lectures ( 1h 18m ) | Size: 873 MB Master Elastic Stack for Data Analysis & Cybersecurity Investigations What you'll learn Elastic Stack Components Elastic Stack Queries Elastic Stack Agents Elastic Stack Installation Requirements Basic knowledge in networking Basic knowledge in networking Basic knowledge in IT concepts Description This course is designed to help you master the Elastic Stack for data analytics and cyber security. You will learn how to configure Elasticsearch, visualize data using Kibana, and craft queries using the Kibana Query Language (KQL). The course also includes a hands-on cyber security investigation where you will analyze a hacked website using Elastic Stack.What is Elastic Stack?Elastic stack is the collection of different open source components linked together to help users take the data from any source and in any format and perform a search, analyze and visualize the data in real-time.What is Elastic Search?Elasticsearch is a full-text search and analytics engine used to store JSON-formated documents. Elasticsearch is an important component used to store, analyze, perform correlation on the data, etc.Why Elastic Stack?Elastic Stack or Elastic, Logstash & Kibana are mainly used for:Data analytics.Security and threat detection.Performance monitoring.What you'll learnFundamentals of Elastic Stack & its componentsSetting up and configuring ElasticsearchBuilding dashboards and visualizationsCrafting KQL queries for data extraction & analyticsCyber security investigation using Elastic StackWho Is This Course For?Data Analysts looking to leverage Elasticsearch for data processingCyber Security Professionals investigating security threatsIT and DevOps engineers implementing log analytics solutionsAnyone interested in learning the power of the Elastic Stack Who this course is for IT Professionals Cyber Security Professionals Data Analysts Homepage: https://www.udemy.com/course/learning-elastic-stack-for-data-analytics-cyber-security/ DOWNLOAD NOW: Learning Elastic Stack for Data Analytics & Cyber Security Rapidgator https://rg.to/file/b04e395d0a945eb499d444493e37e883/jhwlx.Learning.Elastic.Stack.for.Data.Analytics..Cyber.Security.rar.html Fikper Free Download https://fikper.com/nb4tMvHZQX/jhwlx.Learning.Elastic.Stack.for.Data.Analytics..Cyber.Security.rar.html : No Password - Links are Interchangeable

Free Download Udemy - Data Analytics Complete course ( English) Published: 2/2025 MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch Language: English | Duration: 30h 39m | Size: 15.6 GB Learn multiple tools in data analytics stack through this course, all in one bundle! What you'll learn Understand and learn different tool in data analytics. Be ready to appear for interviews and crack them easily Become independent to maximum level in handling tasks End-to-end project covering entire lifecycle Requirements There are no prerequistes for this course, learn everything from scratch. Description Note: This is an English course, same course is available in Hindi.This course covers multiple tools and technologies needed to become a data analyst.The best part is there are no pre-requisites!Anyone can enroll and learn through this course.Our videos are simple to understand, to the point, short and yet covering everything you need.The content we are offering in this course is immense and requires full dedication, self -discipline and daily learning to ensure a completion and to make you independent skilled professional.We have trained 1000's of students and shaped their career and you could be the next one, join us by enrolling in the course and benefit immensely through our course offering.You will get best of both quality and quantity!There are no prerequisites.All you need to do is follow the sequence in this course designed for you.In this course you will learn below tools and technologies from scratch:SQL : Learn structured query language in Microsoft SQL Server.Data warehousing : Learn fundamental concepts of data warehousing.POWER BI : Learn POWER BI in depth including concepts, reporting, DAX and Power bi service.Databricks: Learn databricks Overview, the leading data platform.Python programming: Learn programming in python with simple way. Who this course is for This course for one who is looking to transition into data analytics as well as for existing data analyst professionals. 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Free Download Microsoft Fabric Analytics Engineer Implement and Manage Semantic Models Released 4/2024 By Nikola Ilic MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch Level: Intermediate | Genre: eLearning | Language: English + subtitle | Duration: 1h 48m | Size: 255 MB Designing scalable and performant semantic models is one of the key Requirements in enterprise-grade environments. This course will teach you how to implement and manage optimal semantic models to support efficient business decision-making. There is a huge difference between semantic models that just work and semantic models that work efficiently. In this course, Microsoft Fabric Analytics Engineer: Implement and Manage Semantic Models, you'll learn to design optimal semantic models to support large enterprises. First, you'll explore various data modeling concepts and techniques. Next, you'll discover how to leverage different advanced concepts to enhance your semantic models. Finally, you'll learn how to leverage external tools to improve the performance of semantic models. When you're finished with this course, you'll have a foundational understanding of advanced data modeling concepts and techniques in Microsoft Fabric that will enable you to design optimal enterprise-scale semantic models and get you ready for the DP-600 exam. Homepage: https://www.pluralsight.com/courses/microsoft-fabric-analytics-engineer-semantic-models-cert DOWNLOAD NOW: Microsoft Fabric Analytics Engineer Implement and Manage Semantic Models Fileaxa https://fileaxa.com/0d1dkzlyxtjs/polzv.Pluralsight..Microsoft.Fabric.Analytics.Engineer.Implement.and.Manage.Semantic.Models.rar TakeFile https://takefile.link/vx2ivzfj7azs/polzv.Pluralsight..Microsoft.Fabric.Analytics.Engineer.Implement.and.Manage.Semantic.Models.rar.html Rapidgator https://rg.to/file/160766e8fdf3f58eea91a533ab807b26/polzv.Pluralsight..Microsoft.Fabric.Analytics.Engineer.Implement.and.Manage.Semantic.Models.rar.html Fikper Free Download https://fikper.com/eKPVyJqLBN/polzv.Pluralsight..Microsoft.Fabric.Analytics.Engineer.Implement.and.Manage.Semantic.Models.rar.html : No Password - Links are Interchangeable

Free Download Wyckoff Analytics - Linda Bradford Raschke - Her Trades Her Story Join Linda Bradford Raschke in her exclusive presentation on her personal trading journey, philosophies, and strategies. This session is an invaluable opportunity for anyone looking to gain insights into the world of trading from a seasoned expert. What You'll Learn Personal Philosophy and Trading Beliefs Linda will share her personal philosophy and beliefs about the markets and trading. Her unique perspective, developed over years of experience, will offer valuable insights into understanding market dynamics and developing a trader's mindset. Building a Trading System Learn the fundamental elements of building a successful trading system. Linda will discuss common obstacles to success and how to overcome them, providing you with a solid foundation for creating your own trading system. Processes, Routines, and Habits Discover the necessary processes, routines, and habits essential for establishing a successful trading practice. Linda will guide you through the key steps to maintain discipline and consistency in your trading activities. Current Market Review and Q&A Gain insights into current market trends with a comprehensive review, followed by an interactive Q&A session (available on March 21 only). This is your chance to ask Linda direct questions and gain personalized advice. Conclusion Linda Bradford Raschke's presentation is a rare opportunity to learn from one of the best in the industry. With her extensive experience and practical advice, you'll be better equipped to navigate the markets and enhance your trading strategies. Don't miss this chance to elevate your trading knowledge and skills. Sales Page: https://www.wyckoffanalytics.com/demand/linda-bradford-raschke-her-trades-her-story/ Genre / Category Category: Trading, Financial Markets, Investment Strategies, Professional Development DOWNLOAD NOW: Wyckoff Analytics - Linda Bradford Raschke - Her Trades Her Story Rapidgator-->Click Link PeepLink Below Here Contains Rapidgator https://rg.to/folder/7912497/WyckoffAnalyticsLindaBradfordRaschkeHerTradesHerStoryDOWNLOADLINKS.html http://peeplink.in/7fb8c73c31d6 Fileaxa https://fileaxa.com/pmrkwaco7myi/Wyckoff_Analytics__Linda_Bradford_Raschke__Her_Trades_Her_Story.DOWNLOAD.LINKS.rar TakeFile https://takefile.link/ob7a7wqpj9n4/Wyckoff_Analytics__Linda_Bradford_Raschke__Her_Trades_Her_Story.DOWNLOAD.LINKS.rar.html Fikper Free Download https://fikper.com/g3DoIiKRTt/Wyckoff_Analytics__Linda_Bradford_Raschke__Her_Trades_Her_Story.DOWNLOAD.LINKS.rar.html No Password - Links are Interchangeable

Free Download Predictive Customer Analytics (2024) Published 10/2024 Created by Start-Tech Academy MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch Genre: eLearning | Language: English | Duration: 29 Lectures ( 3h 23m ) | Size: 1.68 GB Build predictive machine learning and forecasting models in Excel to build customer decision and customer behavior What you'll learn Discover how to preprocess customer data for predictive modeling using Excel. Master the application of linear regression in Excel to predict customer behavior. Explore the use of logistic regression for customer churn prediction and retention strategies. Analyze customer data using clustering techniques to segment customer groups. Build sales forecasting models using Excel's Solver and time series analysis. Implement XLSTAT for advanced statistical analysis in customer predictions. Develop and run logistic regression models using Excel Macros for automation. Predict future customer behavior with additive and multiplicative time series models. Interpret the results of regression and clustering models to make actionable business decisions. Evaluate the effectiveness of your predictive models in improving customer retention and business strategies. Requirements A PC/ laptop with good internet connection and MS Excel installed on it Description Are you an aspiring data analyst or business professional looking to make data-driven decisions that impact customer behavior and retention? Do you want to leverage Excel to build predictive models without the complexity of advanced coding? If yes, this course is for you.In today's competitive market, understanding customer behavior is key to business success. Predictive Customer Analytics helps you stay ahead by forecasting customer decisions, improving retention, and driving targeted marketing strategies. This course will empower you to use Excel as a powerful tool for building predictive machine learning models and forecasting techniques, even if you're not an expert in data science.In this course, you will:Develop a solid understanding of linear and logistic regression techniques in Excel to predict customer behavior.Master clustering techniques for customer segmentation, identifying key groups within your customer base.Build sales forecasting models using Excel's Solver and time series methods.Implement real-world solutions with case studies, such as predicting customer churn and segmenting customers for better marketing strategies.Why is Predictive Customer Analytics so important? By using Excel, a tool most professionals are already familiar with, you can unlock deeper insights into customer data, enabling better decision-making without needing advanced technical skills. From forecasting sales trends to retaining key customers, predictive analytics is a game-changer for businesses looking to grow and scale.Throughout the course, you will complete hands-on exercises in Excel, including:Preprocessing customer data for linear and logistic regressionBuilding predictive models using XLSTAT and Excel MacrosClustering customer data for segmentation analysisImplementing time series forecasting to predict salesWhat sets this course apart is its focus on practical, easy-to-implement techniques that don't require programming knowledge. You'll learn how to utilize Excel's advanced features to get accurate, actionable results quickly.Ready to transform your customer insights? Enroll today and start building your own predictive models in Excel! Who this course is for Marketing professionals who want to use data to predict customer behavior and enhance targeted campaigns. Sales managers looking to forecast sales trends and improve customer retention strategies. Data analysts who want to build predictive models in Excel without needing complex coding skills. Small business owners aiming to make data-driven decisions to optimize customer acquisition and retention. Homepage https://www.udemy.com/course/predictive-customer-analytics/ Screenshot Rapidgator https://rg.to/file/22f5ee0eb74995ff51792cdfb7a2082e/hmaze.Predictive.Customer.Analytics.2024.part1.rar.html https://rg.to/file/34e18dce1ed2acff4d9463783b285b44/hmaze.Predictive.Customer.Analytics.2024.part2.rar.html Fikper Free Download https://fikper.com/7QwAECQ5io/hmaze.Predictive.Customer.Analytics.2024.part2.rar.html https://fikper.com/Q16PHN9U1L/hmaze.Predictive.Customer.Analytics.2024.part1.rar.html No Password - Links are Interchangeable

Free Download Marketing Analytics in Action Drive Growth and Communication with Data Insights Released: 10/2024 Duration: 28m | .MP4 1280x720, 30 fps(r) | AAC, 48000 Hz, 2ch | 64 MB Level: Intermediate | Genre: eLearning | Language: English In this course, Chris DallaVilla, a key opinion leader in the space, shows you how to harness the power of marketing data analytics and AI to uncover valuable insights and fuel business growth. Learn how to leverage the latest AI tools and techniques to streamline your marketing analytics processes, so that you can make faster, more informed decisions. Gain the skills and confidence to turn data into compelling narratives that inspire action, communication, and growth. Whether you're a seasoned marketer or new to the field, this course will empower you to get the most from your data, connect and communicate with others, unlock creativity, and take your marketing efforts to the next level. Homepage https://www.linkedin.com/learning/marketing-analytics-in-action-drive-growth-and-communication-with-data-insights Rapidgator https://rg.to/file/f3b2260e19283b1716b8c8a210f23ac2/aakvn.Marketing.Analytics.in.Action.Drive.Growth.and.Communication.with.Data.Insights.rar.html Fikper Free Download https://fikper.com/fOx6f3RFoG/aakvn.Marketing.Analytics.in.Action.Drive.Growth.and.Communication.with.Data.Insights.rar.html No Password - Links are Interchangeable

Free Download Linkedin - Adobe Customer Journey Analytics Released 10/2024 With Eric Matisoff MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch Skill level: Intermediate | Genre: eLearning | Language: English + subtitle | Duration: 2h 30m 58s | Size: 372 MB Learn how to use Adobe Customer Journey Analytics to access, analyze, and refine omnichannel data. Course details This course delivers a detailed review of the Adobe Customer Journey Analytics platform. Eric Matisoff explains the unique aspects of Customer Journey Analytics compared to Adobe Analytics, as well as how to apply features for your omnichannel and digital analytics needs. Plus, Eric guides you on how to analyze data using Adobe Product Analytics. Finally, learn several administrative capabilities that are key differentiators of Customer Journey Analytics. Homepage https://www.linkedin.com/learning/adobe-customer-journey-analytics Screenshot Rapidgator https://rg.to/file/1b04abd35ae602314d0251017240e852/iqywc.Adobe.Customer.Journey.Analytics.rar.html Fikper Free Download https://fikper.com/hHzvPcJYtE/iqywc.Adobe.Customer.Journey.Analytics.rar.html No Password - Links are Interchangeable

Free Download Introduction To Business Analytics (2024) Published 10/2024 MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz Language: English | Size: 797.98 MB | Duration: 0h 53m Gain Insight Into Workplace Efficiency, Employee Performance, Advertising ROI And Future Trends For Business Advantage What you'll learn Understand the current roles and applications of business analytics. Recall concepts of business analytics and its wider importance for professional success. Spot different types and sources of data, and how to collect them properly. Visualise data to unlock insightful and meaningful information. Understand when different visualisation tools are appropriate given the source, type and context of the data provided. Implement predictive analytics correctly, from method through to validation. Apply time-series data in a meaningful way to spot trends and patterns. Gain a stronger appreciation of the future of business analytics, and what each trend may mean for your company. Requirements No specific requirements. Description Are you looking to increase your business' profits and ROI using cutting-edge analytics tools? Do you want to better understand the basics of data science, and how to implement those techniques in the real world? Would you like to maximise workplace performance, marketing strategy and overall efficiency, but aren't sure where to start? If you answered yes to any of these questions, then this course is for you! Data is at the heart of every company's success, so it is essential you know the basic analytical concepts and how to apply them correctly. From predicting forecasting to heat mapping, there are endless ways to make use of data for business performance. Analytics can help drive decision-making, quantify risk and even improve task efficiency. First, however, we need to focus on the fundamentals before we can utilise data's endless possibilities. Considering that 63% of companies have implemented either artificial intelligence or machine learning to enhance their analytical capabilities, it is key you stay up to date! Throughout a series of six short video-based lectures, you will learn to navigate the dynamic landscape of business analytics. We will uncover the current roles and applications driving this field, empowering you to grasp its significance for professional triumph. You'll recall vital business analytics concepts through interactive lessons and explore their broader implications. By delving into data visualisation techniques, you'll unlock insightful and meaningful information hidden within data sets. We will guide you to adeptly identify diverse data types and sources, ensuring proficient and ethical data collection methods. You'll develop a keen sense of discernment in selecting appropriate visualisation tools based on data sources, types, and contextual cues. From predictive analytics methods to validation strategies, you'll gain the skills to effectively implement these tools. Moreover, you'll harness the power of time-series data, deciphering trends and patterns that hold valuable insights. As you progress, you'll cultivate a profound understanding of upcoming trends in business analytics, equipping you to anti[beeep]te their impact on your organisation's future. This course paves the way for a transformative journey toward becoming a proficient and forward-thinking business analytics practitioner. By the end of this course, we are confident you will emerge with a robust skill set in business analytics, equipped to discern, analyse and visualise data effectively, make informed decisions using predictive analytics and possess a clear vision of how to leverage emerging trends for your company's strategic advantage. So, are you ready to push your business into the future and revolutionise your processes? Enrol now to learn more! Overview Section 1: Introduction Lecture 1 Introduction To Business Analytics Section 2: Introduction To Business Analytics Lecture 2 Importance Of Analytics In Decision Making And Key Terminologies Lecture 3 Foundations Of Business Analytics Lecture 4 Predictive Analytics Lecture 5 Time Series Analysis Lecture 6 Future Trends In Business Analytics Section 3: Conclusion Lecture 7 Conclusion Managers who want to gain extra insight into workplace tasks and employee performance.,Business owners who want to take their company to the next level using novel and unique methods.,Professionals hoping to use future analytical trends to stay ahead of the curve.,Individuals in marketing or UX hoping to use customer-based data to improve advertising and product experience.,Business leaders seeking practical skills in business analytics, regardless of their initial understanding.,Professionals looking to take a more technical approach to business, using case studies and useful information to motivate important decisions within their company. 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Free Download Expanding Data Analytics And Ai In Internal Audit Published 10/2024 MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz Language: English | Size: 1.16 GB | Duration: 1h 4m Staying on top of the new technology What you'll learn Understand the Role of Data Analytics in Internal Audit: Gain insights into how data analytics can enhance audit quality, efficiency, and effectiveness by ident Explore AI Applications in Auditing: Learn how AI technologies such as machine learning and natural language processing can be used to automate tasks, improve f Develop Strategies for Integrating Data Analytics and AI: Learn best practices for incorporating data analytics and AI into your existing audit framework, from Assess the Benefits and Challenges of AI-Driven Audits: Understand the opportunities AI provides in enhancing audit capabilities while identifying potential cha Implement Advanced Data Analytics Techniques: Acquire practical knowledge of key data analytics techniques, including predictive analytics and data visualizatio Understand Internal Audit's new role as it comes to implementing AI usage in the organization with emphasis on data privacy. This course is designed to discuss the concept/use of data analytics but it is not a guide on how to use that tool. Requirements There are no prerequisites for this course Description Join us for an insightful webinar focused on transforming internal audit practices through advanced data analytics and AI. As organizations face increasing complexities, internal auditors must evolve to stay ahead of emerging risks. This session will explore critical topics like improving data literacy within audit teams, and how educating senior management and the board can lead to more strategic decision-making.We will also address the growing need for real-time threat detection in a fast-paced digital environment and how AI can enhance risk identification. Learn practical steps to implement data-driven audits that provide deeper insights, increased efficiency, and proactive issue resolution. Whether you're looking to build a more data-centric audit function or improve collaboration with leadership on risk management, this webinar offers actionable guidance and industry best practices. This is not just your usual data analytics course. It looks conceptually, as the new cyber dependent world in which we operate.Don't miss this exciting opportunity to stay at the forefront of internal audit innovation, with expert advice on leveraging data and AI to drive impactful change. Perfect for internal audit professionals, data analysts, and business leaders aiming to elevate their approach to risk and performance monitoring. This session will show you why it so important to stay on top of the advancements in technology and how to use it to your advantage. Overview Section 1: Understanding Data Analytics and its evolution within Auditing Lecture 1 Introduction Section 2: Benefits of Data Analytics Lecture 2 Understanding the Benefits and Taking Inventory Section 3: Preparing for AI Lecture 3 Preparing for AI Section 4: AI and Data Analytics Merge Lecture 4 AI and Data Analytics Merge Section 5: Conclusion Lecture 5 Recap and Wrap Up Internal auditors,Audit Management,IT auditors,CIOs Screenshot Homepage https://www.udemy.com/course/expanding-data-analytics-and-ai-in-internal-audit/ Rapidgator https://rg.to/file/5ddbc7de975a01de748c6456bfd9eeee/tasyw.Expanding.Data.Analytics.And.Ai.In.Internal.Audit.part1.rar.html https://rg.to/file/ceaf762fd59160c9724ea1e901c8eafd/tasyw.Expanding.Data.Analytics.And.Ai.In.Internal.Audit.part2.rar.html Fikper Free Download https://fikper.com/kHWszX5YnB/tasyw.Expanding.Data.Analytics.And.Ai.In.Internal.Audit.part1.rar.html https://fikper.com/oY3pY1MD0l/tasyw.Expanding.Data.Analytics.And.Ai.In.Internal.Audit.part2.rar.html No Password - Links are Interchangeable

Free Download Excel Predictive Analytics, Automation, and AI - No-Code Published 10/2024 MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch Language: English | Duration: 3h 57m | Size: 1.82 GB Microsoft Excel Predictive Analytics, Automation, and AI Tools: The Complete No-Code Guide for Every Professional What you'll learn Master Predictive Analytics Using Excel Students will learn how to use Excel's built-in tools and functions, such as LINEST and TREND Automate Repetitive Tasks with Macros and VBA Learners will gain the skills to create and implement Excel macros and basic VBA to automate repetitive tasks Apply Advanced Forecasting Techniques Students will explore and apply advanced forecasting methods, such as exponential smoothing to predict trends Learners will develop dynamic, interactive dashboards using PowerPivot, Power BI, and Excel's advanced charting tools to present insights effectively. Requirements Basic Understanding of Excel Students should have a basic familiarity with Excel, including knowledge of standard functions like SUM, AVERAGE, and simple cell formatting. Access to Excel Software Learners will need access to Microsoft Excel (preferably version 2021 or Excel 365) to follow along with the exercises and practical applications. No Coding Experience Required No prior programming or coding knowledge is needed, as this course focuses on no-code solutions for predictive analytics and automation using Excel. A Desire to Learn Predictive Analytics While no advanced math or analytics background is required, students should be motivated to explore how data-driven decisions can be made using Excel's tools. Description Here's a course description for Excel Predictive Analytics, Automation, and AI : No-Code.Unlock the full potential of Excel with this comprehensive course designed to take you from the basics of predictive analytics to advanced forecasting, automation, and data visualization-all without writing a single line of code.In this course, you'll learn how to use Excel's powerful tools to analyze data, make accurate predictions, and automate repetitive tasks, allowing you to save time and drive smarter business decisions. From forecasting sales trends to building dynamic dashboards, this course is packed with practical, real-world applications that you can start using immediately.What You'll Learn:Master predictive analytics and forecasting using Excel's built-in functions like LINEST, TREND, and Forecast.ETS.Automate repetitive tasks using Excel macros and VBA to boost efficiency and save time.Create dynamic, interactive dashboards with PowerPivot and Power BI, visualizing key business insights with advanced charts and slicers.Leverage AI tools like ChatGPT to enhance your Excel workflows and improve decision-making.This course is perfect for business professionals, analysts, small business owners, and Excel users looking to take their skills to the next level by integrating automation and data-driven decision-making into their work.No coding required-just a desire to improve your Excel skills and become an expert in predictive analytics and automation! Who this course is for Business Professionals Anyone working in business roles such as finance, marketing, sales, or operations who needs to make data-driven decisions and improve their forecasting capabilities without relying on complex coding. Analysts and Data Enthusiasts People in data analysis roles or those interested in learning practical, no-code methods for performing predictive analytics and creating powerful data visualizations using Excel. Small Business Owners and Entrepreneurs Entrepreneurs looking to optimize their business performance by forecasting sales, automating tasks, and gaining insights from their data using easy-to-understand tools in Excel. Excel Users Seeking Advanced Skills Intermediate Excel users who want to elevate their skills by learning advanced Excel features such as macros, Solver, PowerPivot, and data visualization techniques to boost their productivity and analysis capabilities. Homepage https://www.udemy.com/course/excel-predictive-analytics-automation-and-ai-no-code/ Rapidgator https://rg.to/file/c7dee0a270578da0362ff9186c3fabfe/hnpuy.Excel.Predictive.Analytics.Automation.and.AI..NoCode.part2.rar.html https://rg.to/file/f8a89bb8fb3e8dfd7f976bb03bf97676/hnpuy.Excel.Predictive.Analytics.Automation.and.AI..NoCode.part1.rar.html Fikper Free Download https://fikper.com/7qgOFaU5Es/hnpuy.Excel.Predictive.Analytics.Automation.and.AI..NoCode.part1.rar.html https://fikper.com/Tmxd1AsG1a/hnpuy.Excel.Predictive.Analytics.Automation.and.AI..NoCode.part2.rar.html No Password - Links are Interchangeable

Free Download Excel Analytics - Data Analysis with Pivot-Tables and Charts Last updated 11/2022 Duration: 2h 51m | Video: .MP4, 1920x1080 30 fps | Audio: AAC, 48kHz, 2ch | Size: 1.63 GB Genre: eLearning | Language: English Learn Data Analysis from A to First Project with Pivot-Tables, Pivot-Charts and Advanced Formulas All In One Course. What you'll learn Write advanced formulas including lookup functions and Dynamic Arrays. Get used to the course content by practicing through the different assignments included in the course. A Full Project guidance step-by-step on a real-life databaset How to analyze any data step by step Understand How spreadsheets can be used as a data analysis tool. Gain an immersive understanding of Data (Defination, Categories, Types and Qualities). Understand the differences between Big Data and Traditional Data. Easy Guidance on how to find free datasets for practice. Obtain Knowledge on Data Clearning (Importance and different methods of Data Cleaning). Obtain Knowledge on Data Manipulation (How to extract information out of a dataset). How to use Pivot-Tables and gain an undestanding of its different features. Learn the different types of charts and how to use them properly. Requirements Microsoft Excel 2014 and Above For Mac Users, You might find a different interface when it comes to Pivot-Table Panel Description Why should you enroll in this course? This course covers all aspects of Excel Analytics starting from downloading a dataset to analyzing and creating a full project. It covers the fundamentals of Data and Quality data to have a good basis before getting into data analysis. It's suitable for beginner and intermediate levels to up their skills to advanced. It covers all business categories therefore, No matter what industry you're working in/want to work in, This course is for you. As a result of this course, you will be able to work on Excel Analytics projects on your own and make money freelancing. On-Video and Off-Video full project, Step-by-Step, in addition to practice tests. All your queries and questions will be answered by the instructor directly. Finally, This course is updated regularly to match the latest updates in regard to data analysis and Excel in particular. What will you learn in this course? 1- Data Data Analysis surely starts with Data, Hence, During Section 1, You will learn What's Data? Starting with its definition up to categories and qualities What are the Data Types in Excel? How to find a dataset? How to Navigate through a dataset? How to Autofil Data in Excel? 2- Data Cleansing Data Cleansing is the process of clearing a dataset of any duplicates, blanks, or inconsistencies and making sure your dataset contains quality data What are the traits of quality data? How to identify duplicates and blanks? Essential excel formulas (TRIM, UPPER, lower, Proper, Substitute, Concatenation) Filter and Sort Features How to change Data Types Text to Column How to Format data as a table? 3- Data Manipulation Data Manipulation is the process of manipulating data to extract relevant and key information from your dataset Statistical Formulas or Functions (Mean, Median, Mode, Min, Max, Average) Data Manipulation formulas (SUM, VLOOKUP, HLOOKUP) Logical Functions (IF, IFS, SUMIF, COUNT, COUNTIF, COUNTIFS, COUNTBLANKS) 4- Analyze Data Stage 4 is analyzing data using Pivot-Tables to gain more insights by creating a pivot table based on different rows/columns/filters and calculations Introduction to Pivot-tables to understand what it is and why it is important How to create a Pivot-Table? How to Format Data in a Pivot-Table? How to apply calculations on data in a Pivot-Table? How to Sort Data in a Pivot-Table? What are Slicers? How to use them and Why they are important? How to create automated recommended Pivot-Tables? 5- Data Visualization Finally Data Visualization, This is the final stage where you get to present your insights and analysis using Charts and Graphs, Charts are important as each Chart Type could identify hidden patterns and trends Introduction to important Chart Types such as (Bar Charts, Column Charts, Line Charts, Combo Charts, Pie Charts, and Doughnut Charts) How to create a Pivot-Chart? How to Apply a Slicer to a Pivot-Chart? How to Manually Style your Pivot-Chart? 6- Final Project (Step-by-Step) In the final section of the course, we will run through a hands-on data analysis project where you will make use of the knowledge you have gained throughout the course. What makes this course different from the other courses? This course is complete and precise, Hence, You won't have to take another course in Excel Analytics. This course teaches you everything about data analysis and guides you through your first data analysis project. Less than 8 hours avg response time (By the instructor) Assessment (First Project) evaluation in less than 24 hours by the instructor It offers auto-generated subtitles in more than 3 languages including (Arabic, Hindi, and Spanish) Regularly updated downloadable resources. What our students say about this course I would say this course is just straight to the point and exactly as described, i would definitely recommend it to any one who looks to start learning data analysis using Excel, Thank you Moustafa! I like it so far very to the point and basic so anyone can catch on. I am doing work to up my career skills and finding this course was exactly what I needed! awesome course. The course materials are easy to follow even for novices and the instructor teaches very well explained. I will recommend this class to whom want to learn data analytics with excel. This course is complete as you will learn all that you need to get your hands dirty in the field of Data Analysis, You will obtain the important intellectual and technical skills to start your first project. Enroll with us, We're looking forward to becoming a part of your success. Who this course is for Anyone using Excel and wants to dive into the world of Data Analysis Homepage https://www.udemy.com/course/microsoft-excel-analytics Screenshot Rapidgator https://rg.to/file/21846201eebbabe3f26d4a7d60fe2d31/lnkio.Excel.Analytics..Data.Analysis.with.PivotTables.and.Charts.part2.rar.html https://rg.to/file/ab5197996b69acdcae73df036181b03a/lnkio.Excel.Analytics..Data.Analysis.with.PivotTables.and.Charts.part1.rar.html Fikper Free Download https://fikper.com/e74GG1MWgo/lnkio.Excel.Analytics..Data.Analysis.with.PivotTables.and.Charts.part2.rar.html https://fikper.com/j7biZOOygG/lnkio.Excel.Analytics..Data.Analysis.with.PivotTables.and.Charts.part1.rar.html No Password - Links are Interchangeable

Free Download Data Engineering using AWS Data Analytics Last updated 2/2023 Created by Durga Viswanatha Raju Gadiraju,Pratik Kumar,Sathvika Dandu,Madhuri Gadiraju,Sai Varma,Phani Bhushan Bozzam MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch Genre: eLearning | Language: English + subtitle | Duration: 434 Lectures ( 26h 15m ) | Size: 7.77 GB Build Data Engineering Pipelines on AWS using Data Analytics Services - Glue, EMR, Athena, Kinesis, Lambda, Redshift What you'll learn Data Engineering leveraging Services under AWS Data Analytics AWS Essentials such as s3, IAM, EC2, etc Understanding AWS s3 for cloud based storage Understanding details related to virtual machines on AWS known as EC2 Managing AWS IAM users, groups, roles and policies for RBAC (Role Based Access Control) Managing Tables using AWS Glue Catalog Engineering Batch Data Pipelines using AWS Glue Jobs Orchestrating Batch Data Pipelines using AWS Glue Workflows Running Queries using AWS Athena - Server less query engine service Using AWS Elastic Map Reduce (EMR) Clusters for building Data Pipelines Using AWS Elastic Map Reduce (EMR) Clusters for reports and dashboards Data Ingestion using AWS Lambda Functions Scheduling using AWS Events Bridge Engineering Streaming Pipelines using AWS Kinesis Streaming Web Server logs using AWS Kinesis Firehose Overview of data processing using AWS Athena Running AWS Athena queries or commands using CLI Running AWS Athena queries using Python boto3 Creating AWS Redshift Cluster, Create tables and perform CRUD Operations Copy data from s3 to AWS Redshift Tables Understanding Distribution Styles and creating tables using Distkeys Running queries on external RDBMS Tables using AWS Redshift Federated Queries Running queries on Glue or Athena Catalog tables using AWS Redshift Spectrum Requirements A Computer with at least 8 GB RAM Programming Experience using Python is highly desired as some of the topics are demonstrated using Python SQL Experience is highly desired as some of the topics are demonstrated using SQL Nice to have Data Engineering Experience using Pandas or Pyspark This course is ideal for experienced data engineers to add AWS Analytics Services as key skills to their profile Description Data Engineering is all about building Data Pipelines to get data from multiple sources into Data Lakes or Data Warehouses and then from Data Lakes or Data Warehouses to downstream systems. As part of this course, I will walk you through how to build Data Engineering Pipelines using AWS Data Analytics Stack. It includes services such as Glue, Elastic Map Reduce (EMR), Lambda Functions, Athena, EMR, Kinesis, and many more.Here are the high-level steps which you will follow as part of the course.Setup Development EnvironmentGetting Started with AWSStorage - All about AWS s3 (Simple Storage Service)User Level Security - Managing Users, Roles, and Policies using IAMInfrastructure - AWS EC2 (Elastic Cloud Compute)Data Ingestion using AWS Lambda FunctionsOverview of AWS Glue ComponentsSetup Spark History Server for AWS Glue JobsDeep Dive into AWS Glue CatalogExploring AWS Glue Job APIsAWS Glue Job BookmarksDevelopment Life Cycle of PysparkGetting Started with AWS EMRDeploying Spark Applications using AWS EMRStreaming Pipeline using AWS KinesisConsuming Data from AWS s3 using boto3 ingested using AWS KinesisPopulating GitHub Data to AWS DynamodbOverview of Amazon AWS AthenaAmazon AWS Athena using AWS CLIAmazon AWS Athena using Python boto3Getting Started with Amazon AWS RedshiftCopy Data from AWS s3 into AWS Redshift TablesDevelop Applications using AWS Redshift ClusterAWS Redshift Tables with Distkeys and SortkeysAWS Redshift Federated Queries and SpectrumHere are the details about what you will be learning as part of this course. We will cover most of the commonly used services with hands-on practice which are available under AWS Data Analytics.Getting Started with AWSAs part of this section, you will be going through the details related to getting started with AWS.Introduction - AWS Getting StartedCreate s3 BucketCreate AWS IAM Group and AWS IAM User to have required access on s3 Bucket and other servicesOverview of AWS IAM RolesCreate and Attach Custom AWS IAM Policy to both AWS IAM Groups as well as UsersConfigure and Validate AWS CLI to access AWS Services using AWS CLI CommandsStorage - All about AWS s3 (Simple Storage Service)AWS s3 is one of the most prominent fully managed AWS services. All IT professionals who would like to work on AWS should be familiar with it. We will get into quite a few common features related to AWS s3 in this section.Getting Started with AWS S3Setup Data Set locally to upload to AWS s3Adding AWS S3 Buckets and Managing Objects (files and folders) in AWS s3 bucketsVersion Control for AWS S3 BucketsCross-Region Replication for AWS S3 BucketsOverview of AWS S3 Storage ClassesOverview of AWS S3 GlacierManaging AWS S3 using AWS CLI CommandsManaging Objects in AWS S3 using CLI - LabUser Level Security - Managing Users, Roles, and Policies using IAMOnce you start working on AWS, you need to understand the permissions you have as a non-admin user. As part of this section, you will understand the details related to AWS IAM users, groups, roles as well as policies.Creating AWS IAM UsersLogging into AWS Management Console using AWS IAM UserValidate Programmatic Access to AWS IAM UserAWS IAM Identity-based PoliciesManaging AWS IAM GroupsManaging AWS IAM RolesOverview of Custom AWS IAM PoliciesManaging AWS IAM users, groups, roles as well as policies using AWS CLI CommandsInfrastructure - AWS EC2 (Elastic Cloud Compute) BasicsAWS EC2 Instances are nothing but virtual machines on AWS. As part of this section, we will go through some of the basics related to AWS EC2 Basics.Getting Started with AWS EC2Create AWS EC2 Key PairLaunch AWS EC2 InstanceConnecting to AWS EC2 InstanceAWS EC2 Security Groups BasicsAWS EC2 Public and Private IP AddressesAWS EC2 Life CycleAllocating and Assigning AWS Elastic IP AddressManaging AWS EC2 Using AWS CLIUpgrade or Downgrade AWS EC2 InstancesInfrastructure - AWS EC2 AdvancedIn this section, we will continue with AWS EC2 to understand how we can manage EC2 instances using AWS Commands and also how to install additional OS modules leveraging bootstrap scripts.Getting Started with AWS EC2Understanding AWS EC2 MetadataQuerying on AWS EC2 MetadataFitering on AWS EC2 MetadataUsing Bootstrapping Scripts with AWS EC2 Instances to install additional softwares on AWS EC2 instancesCreate an AWS AMI using AWS EC2 InstancesValidate AWS AMI - LabData Ingestion using Lambda FunctionsAWS Lambda functions are nothing but serverless functions. In this section, we will understand how we can develop and deploy Lambda functions using Python as a programming language. We will also see how to maintain a bookmark or checkpoint using s3.Hello World using AWS LambdaSetup Project for local development of AWS Lambda FunctionsDeploy Project to AWS Lambda consoleDevelop download functionality using requests for AWS Lambda FunctionsUsing 3rd party libraries in AWS Lambda FunctionsValidating AWS s3 access for local development of AWS Lambda FunctionsDevelop upload functionality to s3 using AWS Lambda FunctionsValidating AWS Lambda Functions using AWS Lambda ConsoleRun AWS Lambda Functions using AWS Lambda ConsoleValidating files incrementally downloaded using AWS Lambda FunctionsReading and Writing Bookmark to s3 using AWS Lambda FunctionsMaintaining Bookmark on s3 using AWS Lambda FunctionsReview the incremental upload logic developed using AWS Lambda FunctionsDeploying AWS Lambda FunctionsSchedule AWS Lambda Functions using AWS Event BridgeOverview of AWS Glue ComponentsIn this section, we will get a broad overview of all important Glue Components such as Glue Crawler, Glue Databases, Glue Tables, etc. We will also understand how to validate Glue tables using AWS Athena. AWS Glue (especially Glue Catalog) is one of the key components in the realm of AWS Data Analytics Services.Introduction - Overview of AWS Glue ComponentsCreate AWS Glue Crawler and AWS Glue Catalog Database as well as TableAnalyze Data using AWS AthenaCreating AWS S3 Bucket and Role to create AWS Glue Catalog Tables using Crawler on the s3 locationCreate and Run the AWS Glue Job to process data in AWS Glue Catalog TablesValidate using AWS Glue Catalog Table and by running queries using AWS AthenaCreate and Run AWS Glue TriggerCreate AWS Glue WorkflowRun AWS Glue Workflow and ValidateSetup Spark History Server for AWS Glue JobsAWS Glue uses Apache Spark under the hood to process the data. It is important we setup Spark History Server for AWS Glue Jobs to troubleshoot any issues.Introduction - Spark History Server for AWS GlueSetup Spark History Server on AWSClone AWS Glue Samples repositoryBuild AWS Glue Spark UI ContainerUpdate AWS IAM Policy PermissionsStart AWS Glue Spark UI ContainerDeep Dive into AWS Glue CatalogAWS Glue has several components, but the most important ones are nothing but AWS Glue Crawlers, Databases as well as Catalog Tables. In this section, we will go through some of the most important and commonly used features of the AWS Glue Catalog.Prerequisites for AWS Glue Catalog TablesSteps for Creating AWS Glue Catalog TablesDownload Data Set to use to create AWS Glue Catalog TablesUpload data to s3 to crawl using AWS Glue Crawler to create required AWS Glue Catalog TablesCreate AWS Glue Catalog Database - itvghlandingdbCreate AWS Glue Catalog Table - ghactivityRunning Queries using AWS Athena - ghactivityCrawling Multiple Folders using AWS Glue CrawlersManaging AWS Glue Catalog using AWS CLIManaging AWS Glue Catalog using Python Boto3Exploring AWS Glue Job APIsOnce we deploy AWS Glue jobs, we can manage them using AWS Glue Job APIs. In this section we will get overview of AWS Glue Job APIs to run and manage the jobs.Update AWS IAM Role for AWS Glue JobGenerate baseline AWS Glue JobRunning baseline AWS Glue JobAWS Glue Script for Partitioning DataValidating using AWS AthenaUnderstanding AWS Glue Job BookmarksAWS Glue Job Bookmarks can be leveraged to maintain the bookmarks or checkpoints for incremental loads. In this section, we will go through the details related to AWS Glue Job Bookmarks.Introduction to AWS Glue Job BookmarksCleaning up the data to run AWS Glue JobsOverview of AWS Glue CLI and CommandsRun AWS Glue Job using AWS Glue BookmarkValidate AWS Glue Bookmark using AWS CLIAdd new data to the landing zone to run AWS Glue Jobs using BookmarksRerun AWS Glue Job using BookmarkValidate AWS Glue Job Bookmark and Files for Incremental runRecrawl the AWS Glue Catalog Table using AWS CLI CommandsRun AWS Athena Queries for Data ValidationDevelopment Lifecycle for PysparkIn this section, we will focus on the development of Spark applications using Pyspark. We will use this application later while exploring EMR in detail.Setup Virtual Environment and Install PysparkGetting Started with PycharmPassing Run Time ArgumentsAccessing OS Environment VariablesGetting Started with SparkCreate Function for Spark SessionSetup Sample DataRead data from filesProcess data using Spark APIsWrite data to filesValidating Writing Data to FilesProductionizing the CodeGetting Started with AWS EMR (Elastic Map Reduce)As part of this section, we will understand how to get started with AWS EMR Cluster. We will primarily focus on AWS EMR Web Console. Elastic Map Reduce is one of the key service in AWS Data Analytics Services which provide capability to run applications which process large scale data leveraging distributed computing frameworks such as Spark.Planning for AWS EMR ClusterCreate AWS EC2 Key Pair for AWS EMR ClusterSetup AWS EMR Cluster with Apache SparkUnderstanding Summary of AWS EMR ClusterReview AWS EMR Cluster Application User InterfacesReview AWS EMR Cluster MonitoringReview AWS EMR Cluster Hardware and Cluster Scaling PolicyReview AWS EMR Cluster ConfigurationsReview AWS EMR Cluster EventsReview AWS EMR Cluster StepsReview AWS EMR Cluster Bootstrap ActionsConnecting to AWS EMR Master Node using SSHDisabling Termination Protection for AWS EMR Cluster and Terminating the AWS EMR ClusterClone and Create a New AWS EMR ClusterListing AWS S3 Buckets and Objects using AWS CLI on AWS EMR ClusterListing AWS S3 Buckets and Objects using HDFS CLI on AWS EMR ClusterManaging Files in AWS S3 using HDFS CLI on AWS EMR ClusterReview AWS Glue Catalog Databases and TablesAccessing AWS Glue Catalog Databases and Tables using AWS EMR ClusterAccessing spark-sql CLI of AWS EMR ClusterAccessing pyspark CLI of AWS EMR ClusterAccessing spark-shell CLI of AWS EMR ClusterCreate AWS EMR Cluster for NotebooksDeploying Spark Applications using AWS EMRAs part of this section, we will understand how we typically deploy Spark Applications using AWS EMR. We will be using the Spark Application we deployed earlier.Deploying Applications using AWS EMR - IntroductionSetup AWS EMR Cluster to deploy applicationsValidate SSH Connectivity to Master node of AWS EMR ClusterSetup Jupyter Notebook Environment on AWS EMR ClusterCreate required AWS s3 Bucket for AWS EMR ClusterUpload GHActivity Data to s3 so that we can process using Spark Application deployed on AWS EMR ClusterValidate Application using AWS EMR Compatible Versions of Python and SparkDeploy Spark Application to AWS EMR Master NodeCreate user space for ec2-user on AWS EMR ClusterRun Spark Application using spark-submit on AWS EMR Master NodeValidate Data using Jupyter Notebooks on AWS EMR ClusterClone and Start Auto Terminated AWS EMR ClusterDelete Data Populated by GHAcitivity Application using AWS EMR ClusterDifferences between Spark Client and Cluster Deployment Modes on AWS EMR ClusterRunning Spark Application using Cluster Mode on AWS EMR ClusterOverview of Adding Pyspark Application as Step to AWS EMR ClusterDeploy Spark Application to AWS S3 to run using AWS EMR StepsRunning Spark Applications as AWS EMR Steps in client modeRunning Spark Applications as AWS EMR Steps in cluster modeValidate AWS EMR Step Execution of Spark ApplicationStreaming Data Ingestion Pipeline using AWS KinesisAs part of this section, we will go through details related to the streaming data ingestion pipeline using AWS Kinesis which is a streaming service of AWS Data Analytics Services. We will use AWS Kinesis Firehose Agent and AWS Kinesis Delivery Stream to read the data from log files and ingest it into AWS s3.Building Streaming Pipeline using AWS Kinesis Firehose Agent and Delivery StreamRotating Logs so that the files are created frequently which will be eventually ingested using AWS Kinesis Firehose Agent and AWS Kinesis Firehose Delivery StreamSet up AWS Kinesis Firehose Agent to get data from logs into AWS Kinesis Delivery Stream.Create AWS Kinesis Firehose Delivery StreamPlanning the Pipeline to ingest data into s3 using AWS Kinesis Delivery StreamCreate AWS IAM Group and User for Streaming Pipelines using AWS Kinesis ComponentsGranting Permissions to AWS IAM User using Policy for Streaming Pipelines using AWS Kinesis ComponentsConfigure AWS Kinesis Firehose Agent to read the data from log files and ingest it into AWS Kinesis Firehose Delivery Stream.Start and Validate AWS Kinesis Firehose AgentConclusion - Building Simple Steaming Pipeline using AWS Kinesis FirehoseConsuming Data from AWS s3 using Python boto3 ingested using AWS KinesisAs data is ingested into AWS S3, we will understand how data can ingested in AWS s3 can be processed using boto3.Customizing AWS s3 folder using AWS Kinesis Delivery StreamCreate AWS IAM Policy to read from AWS s3 BucketValidate AWS s3 access using AWS CLISetup Python Virtual Environment to explore boto3Validating access to AWS s3 using Python boto3Read Content from AWS s3 objectRead multiple AWS s3 ObjectsGet the number of AWS s3 Objects using MarkerGet the size of AWS s3 Objects using MarkerPopulating GitHub Data to AWS DynamodbAs part of this section, we will understand how we can populate data to AWS Dynamodb tables using Python as a programming language.Install required libraries to get GitHub Data to AWS Dynamodb tables.Understanding GitHub APIsSetting up GitHub API TokenUnderstanding GitHub Rate LimitCreate New Repository for sinceExtracting Required Information using PythonProcessing Data using PythonGrant Permissions to create AWS dynamodb tables using boto3Create AWS Dynamodb TablesAWS Dynamodb CRUD OperationsPopulate AWS Dynamodb TableAWS Dynamodb Batch OperationsOverview of Amazon AWS AthenaAs part of this section, we will understand how to get started with AWS Athena using AWS Web console. We will also focus on basic DDL and DML or CRUD Operations using AWS Athena Query Editor.Getting Started with Amazon AWS AthenaQuick Recap of AWS Glue Catalog Databases and TablesAccess AWS Glue Catalog Databases and Tables using AWS Athena Query EditorCreate a Database and Table using AWS AthenaPopulate Data into Table using AWS AthenaUsing CTAS to create tables using AWS AthenaOverview of Amazon AWS Athena ArchitectureAmazon AWS Athena Resources and relationship with HiveCreate a Partitioned Table using AWS AthenaDevelop Query for Partitioned ColumnInsert into Partitioned Tables using AWS AthenaValidate Data Partitioning using AWS AthenaDrop AWS Athena Tables and Delete Data FilesDrop Partitioned Table using AWS AthenaData Partitioning in AWS Athena using CTASAmazon AWS Athena using AWS CLIAs part of this section, we will understand how to interact with AWS Athena using AWS CLI Commands.Amazon AWS Athena using AWS CLI - IntroductionGet help and list AWS Athena databases using AWS CLIManaging AWS Athena Workgroups using AWS CLIRun AWS Athena Queries using AWS CLIGet AWS Athena Table Metadata using AWS CLIRun AWS Athena Queries with a custom location using AWS CLIDrop AWS Athena table using AWS CLIRun CTAS under AWS Athena using AWS CLIAmazon AWS Athena using Python boto3As part of this section, we will understand how to interact with AWS Athena using Python boto3.Amazon AWS Athena using Python boto3 - IntroductionGetting Started with Managing AWS Athena using Python boto3List Amazon AWS Athena Databases using Python boto3List Amazon AWS Athena Tables using Python boto3Run Amazon AWS Athena Queries with boto3Review AWS Athena Query Results using boto3Persist Amazon AWS Athena Query Results in Custom Location using boto3Processing AWS Athena Query Results using PandasRun CTAS against Amazon AWS Athena using Python boto3Getting Started with Amazon AWS RedshiftAs part of this section, we will understand how to get started with AWS Redshift using AWS Web console. We will also focus on basic DDL and DML or CRUD Operations using AWS Redshift Query Editor.Getting Started with Amazon AWS Redshift - IntroductionCreate AWS Redshift Cluster using Free TrialConnecting to Database using AWS Redshift Query EditorGet a list of tables querying information schemaRun Queries against AWS Redshift Tables using Query EditorCreate AWS Redshift Table using Primary KeyInsert Data into AWS Redshift TablesUpdate Data in AWS Redshift TablesDelete data from AWS Redshift tablesRedshift Saved Queries using Query EditorDeleting AWS Redshift ClusterRestore AWS Redshift Cluster from SnapshotCopy Data from s3 into AWS Redshift TablesAs part of this section, we will go through the details about copying data from s3 into AWS Redshift tables using the AWS Redshift Copy command.Copy Data from s3 to AWS Redshift - IntroductionSetup Data in s3 for AWS Redshift CopyCopy Database and Table for AWS Redshift Copy CommandCreate IAM User with full access on s3 for AWS Redshift CopyRun Copy Command to copy data from s3 to AWS Redshift TableTroubleshoot Errors related to AWS Redshift Copy CommandRun Copy Command to copy from s3 to AWS Redshift tableValidate using queries against AWS Redshift TableOverview of AWS Redshift Copy CommandCreate IAM Role for AWS Redshift to access s3Copy Data from s3 to AWS Redshift table using IAM RoleSetup JSON Dataset in s3 for AWS Redshift Copy CommandCopy JSON Data from s3 to AWS Redshift table using IAM RoleDevelop Applications using AWS Redshift ClusterAs part of this section, we will understand how to develop applications against databases and tables created as part of AWS Redshift Cluster.Develop application using AWS Redshift Cluster - IntroductionAllocate Elastic Ip for AWS Redshift ClusterEnable Public Accessibility for AWS Redshift ClusterUpdate Inbound Rules in Security Group to access AWS Redshift ClusterCreate Database and User in AWS Redshift ClusterConnect to the database in AWS Redshift using psqlChange Owner on AWS Redshift TablesDownload AWS Redshift JDBC Jar fileConnect to AWS Redshift Databases using IDEs such as SQL WorkbenchSetup Python Virtual Environment for AWS RedshiftRun Simple Query against AWS Redshift Database Table using PythonTruncate AWS Redshift Table using PythonCreate IAM User to copy from s3 to AWS Redshift TablesValidate Access of IAM User using Boto3Run AWS Redshift Copy Command using PythonAWS Redshift Tables with Distkeys and SortkeysAs part of this section, we will go through AWS Redshift-specific features such as distribution keys and sort keys to create AWS Redshift tables.AWS Redshift Tables with Distkeys and Sortkeys - IntroductionQuick Review of AWS Redshift ArchitectureCreate multi-node AWS Redshift ClusterConnect to AWS Redshift Cluster using Query EditorCreate AWS Redshift DatabaseCreate AWS Redshift Database UserCreate AWS Redshift Database SchemaDefault Distribution Style of AWS Redshift TableGrant Select Permissions on Catalog to AWS Redshift Database UserUpdate Search Path to query AWS Redshift system tablesValidate AWS Redshift table with DISTSTYLE AUTOCreate AWS Redshift Cluster from Snapshot to the original stateOverview of Node Slices in AWS Redshift ClusterOverview of Distribution Styles related to AWS Redshift tablesDistribution Strategies for retail tables in AWS Redshift DatabasesCreate AWS Redshift tables with distribution style allTroubleshoot and Fix Load or Copy ErrorsCreate AWS Redshift Table with Distribution Style AutoCreate AWS Redshift Tables using Distribution Style KeyDelete AWS Redshift Cluster with a manual snapshotAWS Redshift Federated Queries and SpectrumAs part of this section, we will go through some of the advanced features of Redshift such as AWS Redshift Federated Queries and AWS Redshift Spectrum.AWS Redshift Federated Queries and Spectrum - IntroductionOverview of integrating AWS RDS and AWS Redshift for Federated QueriesCreate IAM Role for AWS Redshift ClusterSetup Postgres Database Server for AWS Redshift Federated QueriesCreate tables in Postgres Database for AWS Redshift Federated QueriesCreating Secret using Secrets Manager for Postgres DatabaseAccessing Secret Details using Python Boto3Reading Json Data to Dataframe using PandasWrite JSON Data to AWS Redshift Database Tables using PandasCreate AWS IAM Policy for Secret and associate with Redshift RoleCreate AWS Redshift Cluster using AWS IAM Role with permissions on secretCreate AWS Redshift External Schema to Postgres DatabaseUpdate AWS Redshift Cluster Network Settings for Federated QueriesPerforming ETL using AWS Redshift Federated QueriesClean up resources added for AWS Redshift Federated QueriesGrant Access on AWS Glue Data Catalog to AWS Redshift Cluster for SpectrumSetup AWS Redshift Clusters to run queries using SpectrumQuick Recap of AWS Glue Catalog Database and Tables for AWS Redshift SpectrumCreate External Schema using AWS Redshift SpectrumRun Queries using AWS Redshift SpectrumCleanup the AWS Redshift Cluster Who this course is for Beginner or Intermediate Data Engineers who want to learn AWS Analytics Services for Data Engineering Intermediate Application Engineers who want to explore Data Engineering using AWS Analytics Services Data and Analytics Engineers who want to learn Data Engineering using AWS Analytics Services Testers who want to learn key skills to test Data Engineering applications built using AWS Analytics Services Homepage https://www.udemy.com/course/data-engineering-using-aws-analytics-services/ Screenshot Rapidgator https://rg.to/file/2920699636897ec371102bdb027e8885/nwnrk.Data.Engineering.using.AWS.Data.Analytics.part05.rar.html https://rg.to/file/2b9aa74769b487eaaedd3eec96345e51/nwnrk.Data.Engineering.using.AWS.Data.Analytics.part04.rar.html https://rg.to/file/45d0ce3bc16db1d6999d3e6f18531e4c/nwnrk.Data.Engineering.using.AWS.Data.Analytics.part06.rar.html https://rg.to/file/d29ebd836544f98050324f6aa8bef726/nwnrk.Data.Engineering.using.AWS.Data.Analytics.part08.rar.html https://rg.to/file/d6f9f7479e24d0907c1621c594edb1fc/nwnrk.Data.Engineering.using.AWS.Data.Analytics.part03.rar.html https://rg.to/file/e60b71f472370ab29b7e10f24d6cbe91/nwnrk.Data.Engineering.using.AWS.Data.Analytics.part02.rar.html https://rg.to/file/e7a08371221bd4424901c60b4e7c8dd4/nwnrk.Data.Engineering.using.AWS.Data.Analytics.part01.rar.html https://rg.to/file/ef32aa5500311afe27cc6fad7604a04d/nwnrk.Data.Engineering.using.AWS.Data.Analytics.part07.rar.html Fikper Free Download https://fikper.com/1gyNST3T5B/nwnrk.Data.Engineering.using.AWS.Data.Analytics.part02.rar.html https://fikper.com/BbGZKWTfP1/nwnrk.Data.Engineering.using.AWS.Data.Analytics.part01.rar.html https://fikper.com/DJBmRaMzGu/nwnrk.Data.Engineering.using.AWS.Data.Analytics.part03.rar.html https://fikper.com/SXxm2gI5gG/nwnrk.Data.Engineering.using.AWS.Data.Analytics.part08.rar.html https://fikper.com/V3HWO9bEX3/nwnrk.Data.Engineering.using.AWS.Data.Analytics.part05.rar.html https://fikper.com/m68l9B0z0U/nwnrk.Data.Engineering.using.AWS.Data.Analytics.part06.rar.html https://fikper.com/yW1sDrNVjo/nwnrk.Data.Engineering.using.AWS.Data.Analytics.part07.rar.html https://fikper.com/zvCGisvXzn/nwnrk.Data.Engineering.using.AWS.Data.Analytics.part04.rar.html No Password - 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Free Download Data Analytics Guide with Microsoft Excel and ChatGPT Published 10/2024 Created by Being Commerce,Being Commerce MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch Genre: eLearning | Language: English | Duration: 48 Lectures ( 14h 32m ) | Size: 8.21 GB Master Data Analytics with Microsoft Excel and ChatGPT: Unleash the Power of Data! What you'll learn Understanding data analytics fundamentals. Navigating Microsoft Excel for data-related tasks. Learning basic and advanced Excel functions. Data cleaning, sorting, and filtering. How to use Excel's Power Query Editor for data transformation. Mastering Pivot Tables for visualization. Automating data processes using ChatGPT. Using logical operators and nested formulas. Creating professional data reports. Applying data aggregation and text functions. Real-world case studies for practical learning. Requirements A computer with Microsoft Excel installed. Basic computer literacy. No prior data analytics or Excel experience is required. Description Welcome to "Data Analytics Guide with Microsoft Excel and ChatGPT"! This course is designed to transform your understanding of data analytics, even if you have no prior experience. Data is the new gold, and knowing how to analyze it can elevate your professional and personal life. With this course, you will become a master of data analytics using Microsoft Excel, one of the most powerful and widely-used tools in the industry.Why this course stands out is its unique integration of Microsoft Excel with AI technology, specifically ChatGPT. Whether you're a beginner or someone looking to sharpen your skills, this course is structured in a way that ensures you're comfortable while learning. Imagine having the power of Excel, combined with AI-driven insights and formulas from ChatGPT, to analyze and manipulate data like never before!This course starts from the very basics, making it perfect for those with little to no experience in Excel. You will begin by understanding what data analytics is and why it's critical in today's business world. From there, you'll be guided step-by-step through mastering Excel's core functions, data cleaning, and formula application. Throughout the journey, ChatGPT will be introduced to show you how to automate and streamline your workflow, making your data analysis faster, more efficient, and precise.Data Analytics is not just a technical skill, but an essential one that opens doors to countless opportunities. Every business, organization, and entrepreneur relies on data-driven decisions to stay competitive, and you can be at the forefront of that decision-making. If you skip this course, you risk falling behind in a world where data literacy is no longer a choice, but a necessity. Don't let that happen. Enroll today and become a data expert, confident in your ability to deliver impactful insights and make smarter decisions. Who this course is for Beginners wanting to learn data analytics from scratch. Professionals looking to boost their career by adding data analytics to their skill set. Small business owners and entrepreneurs who want to make data-driven decisions. Students interested in learning how to work with Excel efficiently. Anyone who wants to automate data processes using AI tools like ChatGPT. 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Free Download Create and Share Analytics with Jupyter Notebooks Duration: 2h 12m | Video: .MP4, 1280x720 30 fps | Audio: AAC, 48 kHz, 2ch | Size: 312 MB Genre: eLearning | Language: English This course covers the important aspects of working with Jupyter notebooks, including installation and the role of kernels, magic functions, and running shell commands. In addition, the power of cloud-hosted Jupyter notebooks is explored on AWS, Microsoft Azure as well as the Google Cloud Platform. Python has exploded in popularity in recent years, largely because it makes analyzing and working with data so incredibly simple. Jupyter is an execution environment rather than a fully-fledged IDE, but even so, notebooks have various important features that are worth understanding thoroughly. In this course, Create and Share Analytics with Jupyter Notebooks, you will learn how Jupyter notebooks are a key driver of Python's popularity, by providing an incredibly intuitive, interactive environment for executing Python programs. First, you will learn how to get up and running with Jupyter notebooks, and how best to leverage features such as markdown to enhance the readability of your code. Next, you will discover how more advanced features such as magic functions work, and how the next generation offering from Jupyter, named JupyterLab goes even further towards a fully-fledged development environment. Finally, you will round out your knowledge by working with cloud-hosted Jupyter notebooks on each of the major cloud platforms. When you're finished with this course, you will have the skills and knowledge to leverage the full power of Jupyter notebooks and Jupyterlab, particularly in the context of cloud-hosted notebooks for distributed and collaborative use-cases. Homepage https://www.pluralsight.com/courses/create-share-analytics-jupyter-notebooks Rapidgator https://rg.to/file/c3c88df5a6984262a474886bf7597e93/ofhik.Create.and.Share.Analytics.with.Jupyter.Notebooks.rar.html Fikper Free Download https://fikper.com/Nn8MzQFLcT/ofhik.Create.and.Share.Analytics.with.Jupyter.Notebooks.rar.html No Password - Links are Interchangeable

Free Download Building Your First Python Analytics Solution Duration: 2h 46m | Video: .MP4, 1280x720 30 fps | Audio: AAC, 48 kHz, 2ch | Size: 382 MB Genre: eLearning | Language: English This course covers the important aspects of choosing a development environment for Python, the differences between Conda and Pip for working with Python libraries, popular IDEs such as PyCharm, IDLE, Eclipse, and Spyder, as well as running Python on the cloud. Python has exploded in popularity in recent years, largely because it makes analyzing and working with data so incredibly simple. Despite its great success as a prototyping tool, Python is still relatively unproven for large, enterprise-scale development. Homepage https://www.pluralsight.com/courses/building-first-python-analytics-solution Rapidgator https://rg.to/file/2e9cfdb917163d3a123626831e5bf881/uxzwp.Building.Your.First.Python.Analytics.Solution.rar.html Fikper Free Download https://fikper.com/MCJ0rhjXGs/uxzwp.Building.Your.First.Python.Analytics.Solution.rar.html No Password - Links are Interchangeable

Free Download Advanced L&D Analytics From Insights To Impact Published 10/2024 MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz Language: English | Size: 250.09 MB | Duration: 0h 44m Transform Learning with Data-Driven Insights: Master L&D Analytics for Measurable Impact and Continuous Improvement What you'll learn Master the fundamentals of data analytics in L&D to make informed decisions. Discover how data analytics enhances L&D initiatives for better training outcomes. Identify key data sources for effective L&D analytics to focus on what matters. Generate training effectiveness reports to showcase the success of your programs. Produce reports on learner progress and performance to support individual journeys. Create reports on learner's engagement and parti[beeep]tion to enhance training involvement. Develop reports on content effectiveness to evaluate and improve your training materials. Summary Requirements L&D or HR Experience Description Here are the key benefits and top learnings from this course:Gain a solid understanding of data analytics in Learning & Development (L&D), empowering you to make smarter, data-driven decisions for improving learning strategies.Discover the advantages of using data to inform L&D strategies, ensuring alignment with business objectives and enhancing decision-making capabilities.Learn effective methods for collecting and analyzing training data, building a strong foundation for leveraging L&D analytics to boost program effectiveness.Master the creation of Training Effectiveness Reports, allowing you to assess the success of your programs, improve their design, and clearly demonstrate return on investment (ROI) to stakeholders.Track learner development with Learner Progress and Performance Reports, ensuring your workforce meets their learning and performance milestones.Measure engagement levels through Engagement and Parti[beeep]tion Reports, fostering higher levels of involvement in learning programs and ensuring employees stay motivated and engaged.Assess the success and relevance of learning content using Content Effectiveness and Utilization Reports, allowing you to optimize resource allocation and improve training outcomes.Leverage data insights to enhance learner experiences, boost retention, and continuously improve the quality and impact of your training programs.Understand how data can drive continuous improvement and innovation, ensuring your learning programs remain relevant and effective over time.Equip yourself with practical techniques to identify trends, spot skill gaps, and optimize your L&D efforts, using data to drive growth and development.Use analytics to demonstrate the tangible impact of learning initiatives on business outcomes and stakeholder satisfaction, showing the value of your L&D programs.This course is ideal for L&D professionals aiming to integrate data analytics into their strategy and maximize the effectiveness of their training programs. Overview Section 1: Introduction Lecture 1 Introduction (Advanced L&D Analytics: From Insights to Impact) Section 2: Advantages of Implementing Data Analytics in L&D Lecture 2 Advantages of Implementing Data Analytics in L&D Section 3: Collecting Data for L&D Analytics Lecture 3 Collecting Data for L&D Analytics Section 4: L&D Analytics Report Introduction Lecture 4 Generating L&D Analytics Report Section 5: Report Type 1: Training Effectiveness Report Lecture 5 Report 1: Training Feedback Lecture 6 Report 2: Pre-Post Assessment Result Lecture 7 Report 3: Self & Manager feedback Lecture 8 Report 4: Impact of training Lecture 9 Report 5: Return on Investment Section 6: Report 2: Engagement and Parti[beeep]tion Reports Lecture 10 Attendance rate in In-Person & virtual sessions Report Lecture 11 Interactive Activities Report Lecture 12 Click-Through Rates for E-Learning content Report Lecture 13 Time Spent on Modules Report Lecture 14 Login Frequency Report Lecture 15 Course Completion Rates Report Section 7: Report 3: Learner's Progress and Performance Reports Lecture 16 Training Completion Rate Report Lecture 17 Dropout Rates and Reasons Report Lecture 18 Performance in Quizzes and Exams Report Lecture 19 Learning Paths and Milestone Achievements Report Lecture 20 Time Taken to Complete Courses Report Section 8: Report 4: Content Effectiveness And Utilization Report Lecture 21 Most and Least Accessed Materials Reports Lecture 22 Completion Rates Reports Lecture 23 Time Spent on Content Report Section 9: Summary Lecture 24 Summary L&D Professionals, HR Heads Homepage https://www.udemy.com/course/advanced-lnd-analytics/ Rapidgator https://rg.to/file/58ac1700125d116c614f02b66b4eb1fb/cihck.Advanced.LD.Analytics.From.Insights.To.Impact.rar.html Fikper Free Download https://fikper.com/20eQsF0OhY/cihck.Advanced.LD.Analytics.From.Insights.To.Impact.rar.html No Password - Links are Interchangeable

Free Download Udemy - vPractical Text Analytics Using Spacy V3.0 Published 10/2024 MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz Language: English | Size: 1.16 GB | Duration: 2h 0m How to extract information WITHOUT building custom Machine Learning models What you'll learn Understand the spaCy document object How spaCy pipelines work How to use Rule based Matching for Information Extraction A system for practical, iterative Text Analytics using the itables library Requirements Intermediate Knowledge of Python programming Basic knowledge of the pandas dataframe library Description What is text analytics?I like this definition: "Text analytics is the process of transforming unstructured text documents into usable, structured data. Text analysis works by breaking apart sentences and phrases into their components, and then evaluating each part's role and meaning using complex software rules and machine learning algorithms."[Source: Lexalytics website]In spaCy, you can use machine learning algorithms in two ways1) pretrained models provided by spaCy and other organizations - for example the en_core_web_md, which I use in this course, is a pretrained model provided by Explosion, the company which created spaCy2) custom machine learning models that you train on your data - which is often referred to in the documentation as "statistical models"Why not statistical models?This is what the makers of spaCy say in their documentation:"For complex tasks, it's usually better to train a statistical entity recognition model. However, statistical models require training data, so for many situations, rule-based approaches are more practical. This is especially true at the start of a project: you can use a rule-based approach as part of a data collection process, to help you "bootstrap" a statistical model.Training a model is useful if you have some examples and you want your system to be able to generalize based on those examples. It works especially well if there are clues in the local context. For instance, if you're trying to detect person or company names, your application may benefit from a statistical named entity recognition model.Rule-based systems are a good choice if there's a more or less finite number of examples that you want to find in the data, or if there's a very clear, structured pattern you can express with token rules or regular expressions. For instance, country names, IP addresses or URLs are things you might be able to handle well with a purely rule-based approach."Just to clarify, I am not against developing statistical models - but as the documentation states quite clearly, it is often more practical to start with rules based systems. One of my main aims in this course is to provide a solid understanding of what you can and cannot do using just a rules based system - in fact I use only one dataset in this entire course so it is a lot easier for the students to make this distinction.When you combine a rules based system with the data visualization technique I describe in this course, you will also gain a very good understanding of your dataset. You can then use this understanding to improve your statistical model if you choose to build one. In my view, most people barely scratch the surface when it comes to using spaCy rules for text analytics. I hope this course will provide them a lot of new insight into how to approach this task. Overview Section 1: About this course Lecture 1 How this course is different from other spaCy courses Lecture 2 The best dataset for learning text analytics Section 2: Exploring spaCy document objects Lecture 3 Import libraries Lecture 4 Splitting text into sentences Lecture 5 Splitting text into words Lecture 6 Part-of-speech tagging Lecture 7 Stop words and punctuation Lecture 8 Text spans Lecture 9 Dependency Parse Tree Lecture 10 Named Entity Recognition Lecture 11 Token is_ attributes Lecture 12 Token like_ attributes Lecture 13 More token attributes Lecture 14 Remaining token attributes Lecture 15 Visualizing the Subtree Lecture 16 Visualizing the token head Section 3: spaCy pipelines Lecture 17 Display pipeline Lecture 18 Tokenizer is unique Lecture 19 tagger Lecture 20 parser Lecture 21 attribute_ruler Lecture 22 lemmatizer Lecture 23 ner Section 4: Rule based matching Lecture 24 Token matcher Lecture 25 Dependency Matcher based on position Lecture 26 Dependency Matcher based on the parse tree Lecture 27 Phrase matcher Section 5: Download the Jupyter notebook Lecture 28 Download the Jupyter notebook used in this course Data Science practitioners who want to use spaCy and Natural Language Processing,Anyone who has a spreadsheet where one of the columns is a paragraph of text and wants to know how to extract useful information from that text to use with the filters you can apply on the OTHER columns (sort, less than, greater than etc) in spreadsheet tools like Excel and Airtable Homepage https://www.udemy.com/course/practical-text-analytics-using-spacy-v3/ Rapidgator https://rg.to/file/62de6a95c15c9caec322b44adc37b8d3/zefsq.Practical.Text.Analytics.Using.Spacy.V3.0.part1.rar.html https://rg.to/file/ebe4aa0823cc80bc955727b0d97e63a3/zefsq.Practical.Text.Analytics.Using.Spacy.V3.0.part2.rar.html Fikper Free Download https://fikper.com/mEBhv5CBte/zefsq.Practical.Text.Analytics.Using.Spacy.V3.0.part1.rar https://fikper.com/S8KuPYpfKq/zefsq.Practical.Text.Analytics.Using.Spacy.V3.0.part2.rar No Password - Links are Interchangeable