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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 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 Udemy - Biomarkers 2.0 Predictive Power With Ai Published 10/2024 MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz Language: English | Size: 857.48 MB | Duration: 0h 0m This 1-2 hour workshop introduces parti[beeep]nts to AI's transformative role in biomarker discovery. What you'll learn Advanced Introduction to AI-Driven Biomarkers AI's Role in Predictive Biomarkers for Complex Diseases Deep Dive into AI Models for Biomarker Identification Data Management, Model Interpretation, and Ethical Considerations Future Directions in AI-Enhanced Biomarker Research Requirements No prior experience in AI or biomarker research is necessary to enroll in this workshop. We welcome parti[beeep]nts from diverse backgrounds, including those new to the field. This workshop is designed to provide a supportive learning environment where foundational concepts will be introduced and built upon throughout the course. Join us to enhance your understanding and skills in this exciting and rapidly evolving area of research! Description AimTo equip PhD scholars and academicians with advanced skills in AI-driven biomarker discovery. This workshop focuses on the role of AI in identifying predictive biomarkers for complex diseases such as cancer, cardiovascular, and neurological disorders, emphasizing emerging research trends, AI models, and ethical implications.Workshop ObjectivesUnderstand the integration of AI in biomarker discovery.Analyze AI models for predicting complex diseases.Learn model validation techniques for AI-driven biomarkers.Address ethical and data challenges in AI biomarker research.Explore AI applications in precision medicine and translational research.Workshop StructureModule 1: Advanced Introduction to AI-Driven BiomarkersIntroduction to Biomarkers: Classical Methods vs. AI IntegrationOverview of traditional biomarker discovery methodsIntroduction to AI's role in transforming biomarker discoveryHistorical perspective of biomarker discoveryThe rise of AI in predictive biomarker developmentModule 2: AI's Role in Predictive Biomarkers for Complex DiseasesTheoretical exploration of machine learning (ML) and deep learning (DL) techniquesCase studies on AI-based biomarkers in complex diseases (Cancer, Cardiovascular, Neurological)Journal reviews on AI-driven biomarkersCase studies from recent research in the fieldModule 3: Deep Dive into AI Models for Biomarker IdentificationAccuracy, precision, and generalizability of AI in biomarker discoveryTheoretical exploration of validation techniquesLarge-scale omics data handlingAI's role in data preprocessing, feature selection, and overcoming challengesModule 4: Data Management, Model Interpretation, and Ethical ConsiderationsAI's role in minimizing overfitting and biasChallenges in interpretability and transparency in biomarker modelsTheoretical frameworks on ethical and legal considerationsResponsible use of AI in healthcare biomarker researchModule 5: Future Directions in AI-Enhanced Biomarker ResearchThe role of AI in the development of precision medicine biomarkersTranslational research and its importance in healthcareAI's contribution to systems biology and biomarker discoveryParti[beeep]nt's EligibilityAI researchers, bioinformaticians, medical researchers, healthcare professionals, and academic scholars.Workshop OutcomesMaster AI techniques for identifying predictive biomarkers.Learn to apply ML and DL models in biomarker research.Handle and preprocess large-scale biological datasets.Explore case studies in cancer, cardiovascular, and neurological research.Address ethical challenges and apply AI models responsibly. Overview Section 1: Introduction Lecture 1 Advanced Introduction to AI-Driven Biomarkers Lecture 2 AI's Role in Predictive Biomarkers for Complex Diseases Lecture 3 Deep Dive into AI Models for Biomarker Identification Lecture 4 Data Management, Model Interpretation, and Ethical Considerations Lecture 5 Future Directions in AI-Enhanced Biomarker Research Lecture 6 Ethical & Legal Challenges Module Lecture 7 Future Directions in AI Module AI researchers, bioinformaticians, medical researchers, healthcare professionals, and academic scholars. Homepage https://www.udemy.com/course/biomarkers-20-predictive-power-with-ai/ Rapidgator https://rg.to/file/58d18ec4754925497ddf58cf10c7e5e1/yevlc.Biomarkers.2.0.Predictive.Power.With.Ai.rar.html Fikper Free Download https://fikper.com/mzhasgRiau/yevlc.Biomarkers.2.0.Predictive.Power.With.Ai.rar No Password - Links are Interchangeable

Free Download Driving Digital Transformation with Generative AI and Predictive AI Technologies Released 9/2024 MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch Skill Level: Intermediate | Genre: eLearning | Language: English + srt | Duration: 1h 9m | Size: 170 MB Digital transformation has been redefined and reshaped with the adoption of enhanced, modern generative AI and predictive AI technologies. Join LinkedIn Top Voice and best-selling author Thomas Erl as he explores the creative ways in which generative AI and predictive AI features and functions can be incorporated into digital transformations to help organizations better plan, design, deliver and work with contemporary, sophisticated digital business solutions. Learn how incorporating AI can help automate complex tasks, elevate customer experiences, promote product innovation, and more. Also, gain valuable insights into the significant risks and challenges that come with increased AI adoption within digital transformations, and how to avoid them. This course is for anyone interested in understanding how advancements in AI have evolved the practice of digital transformation, how to realize their benefit potential, and how to evade associated pitfalls. Homepage https://www.linkedin.com/learning/driving-digital-transformation-with-generative-ai-and-predictive-ai-technologies TakeFile https://takefile.link/wkng76hsoiq3/kuwjm.Driving.Digital.Transformation.with.Generative.AI.and.Predictive.AI.Technologies.rar.html Rapidgator https://rg.to/file/1560fd4af2374f3c94aecd22ef2a80f2/kuwjm.Driving.Digital.Transformation.with.Generative.AI.and.Predictive.AI.Technologies.rar.html Fikper Free Download https://fikper.com/hHTTgpklj1/kuwjm.Driving.Digital.Transformation.with.Generative.AI.and.Predictive.AI.Technologies.rar.html No Password - Links are Interchangeable

Free Download GenAI and Predictive AI Architecture Foundations Released: 09/2024 Duration: 1h 16m | .MP4 1280x720, 30 fps(r) | AAC, 48000 Hz, 2ch | 157 MB Level: Intermediate | Genre: eLearning | Language: English Get a clear understanding of how AI solutions actually work, starting with their basic architectures and advancing to system components and architectural differences between generative AI and predictive AI systems. Join LinkedIn Top Voice and best-selling author Thomas Erl as he breaks down and explains, in plain English, the foundational building blocks and the primary moving parts behind contemporary AI solution environments. This course provides genuine insight into how AI systems function in the real world, and is essential for professionals already working with application and enterprise architectures, as well as professionals in the AI and data science fields. Homepage https://www.linkedin.com/learning/genai-and-predictive-ai-architecture-foundations?u=121350530 TakeFile https://takefile.link/ng378cbfiiuv/wmlwn.GenAI.and.Predictive.AI.Architecture.Foundations.rar.html Rapidgator https://rg.to/file/96dcdb1f7b91625374811c94b2392617/wmlwn.GenAI.and.Predictive.AI.Architecture.Foundations.rar.html No Password - Links are Interchangeable