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Free Download Python Dsa Bootcamp - Master Data Structures & Algorithms Published: 3/2025 MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz Language: English | Size: 1.47 GB | Duration: 8h 18m Master Data Structures and Algorithms: Build Efficient Solutions with Trees, Graphs, Sorting, and Searching Techniques What you'll learn Understand and define key data structures such as arrays, linked lists, stacks, and queues. Analyze algorithm efficiency using Big O notation and identify time and space complexity. Implement common algorithms for searching and sorting, including binary search and quicksort. Solve complex problems using advanced data structures like trees, graphs, and hash tables. Requirements Basic understanding of programming concepts (variables, loops, and conditionals). Familiarity with at least one programming language (e.g., Python, Java, or C++). No prior experience with data structures or algorithms is required; you will learn everything you need to know. Description In this comprehensive course, you will dive deep into the world of data structures and algorithms, which are essential for any aspiring software developer. Understanding these concepts is crucial for writing efficient code and solving complex problems. Throughout the course, you will learn to implement and utilize key data structures such as arrays, linked lists, stacks, and queues. These foundational structures will serve as the building blocks for more advanced topics.As you progress, you will explore advanced data structures like trees and graphs, which are vital for representing hierarchical data and relationships. You will gain hands-on experience through coding exercises that reinforce your understanding and application of these concepts. Additionally, you will learn to analyze algorithm efficiency using Big O notation, allowing you to evaluate the performance of your code in terms of time and space complexity.The course will also cover essential algorithms for searching and sorting, including linear search, binary search, quicksort, and mergesort. By mastering these algorithms, you will be equipped to tackle a variety of programming challenges effectively.By the end of the course, you will have the skills and confidence to optimize your solutions and improve your coding proficiency. Join us to enhance your problem-solving abilities and take your programming skills to the next level!What you will learn:Fundamental Data Structures: Understand and implement basic data structures such as arrays, linked lists, stacks, and queues, and learn when to use each.Advanced Data Structures: Explore more complex structures like trees (binary trees, AVL trees, and binary search trees) and graphs (directed and undirected), including their properties and applications.Algorithm Analysis: Analyze the efficiency of algorithms using Big O notation, and learn to evaluate time and space complexity to make informed decisions about code performance.Searching Algorithms: Master various searching techniques, including linear search and binary search, and understand their use cases and performance implications.Sorting Algorithms: Implement and compare different sorting algorithms, such as bubble sort, selection sort, quicksort, and mergesort, to understand their strengths and weaknesses.Recursion: Learn the principles of recursion and how to apply it to solve problems, including recursive algorithms for searching and sorting.Problem-Solving Techniques: Develop critical thinking and problem-solving skills through hands-on coding exercises and real-world projects that challenge you to apply what you've learned. This course is designed for aspiring software developers, computer science students, and anyone interested in enhancing their problem-solving skills through data structures and algorithms. Whether you're a beginner looking to build a strong foundation or an experienced programmer wanting to refresh your knowledge, this course will provide valuable insights and practical skills. Bookmark message Copy message Homepage: https://www.udemy.com/course/python-dsa-bootcamp-master-data-structures-algorithms/ DOWNLOAD NOW: Python Dsa Bootcamp - Master Data Structures & Algorithms Rapidgator https://rg.to/file/930cfc64dfe7ff5fa3e8bc66e387c29d/retck.Python.Dsa.Bootcamp..Master.Data.Structures..Algorithms.part1.rar.html https://rg.to/file/e9f829d5f0602f84d828f27aeb3c7dd1/retck.Python.Dsa.Bootcamp..Master.Data.Structures..Algorithms.part2.rar.html Fikper Free Download https://fikper.com/Ql9EwVtJ8B/retck.Python.Dsa.Bootcamp..Master.Data.Structures..Algorithms.part1.rar.html https://fikper.com/Oi3foHk3Yn/retck.Python.Dsa.Bootcamp..Master.Data.Structures..Algorithms.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 Linkedin - Using AI for Data-Driven Insights Released 03/2025 With Justin Bateh MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch Skill Level: Intermediate | Genre: eLearning | Language: English + subtitle | Duration: 58m 45s | Size: 136 MB This course equips business professionals with practical AI tools to transform raw data into actionable insights, enabling more accurate and informed decision-making in real-time. Course details The course is designed for those looking to enhance their decision-making capabilities using artificial intelligence, particularly through ChatGPT, without needing advanced technical skills. With AI, you can turn raw data into powerful insights that drive smarter, faster decisions. Move beyond using outdated data or, worse, "going with your gut," and join instructor Justin Bateh as he shares practical AI tools that can help you make more accurate and informed decisions. Homepage: https://www.linkedin.com/learning/using-ai-for-data-driven-insights Fileaxa https://fileaxa.com/wrqs8neonw2p/fziee.Linkedin..Using.AI.for.DataDriven.Insights.rar TakeFile https://takefile.link/01cf03nqlxj4/fziee.Linkedin..Using.AI.for.DataDriven.Insights.rar.html Rapidgator https://rg.to/file/225bad64b1352a2e2b2c1822d00df516/fziee.Linkedin..Using.AI.for.DataDriven.Insights.rar.html Fikper Free Download https://fikper.com/Y9uyZKfnS0/fziee.Linkedin..Using.AI.for.DataDriven.Insights.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 Snowflake - A Comprehensive Guide To Cloud Data Warehousing Published: 3/2025 MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz Language: English | Size: 14.77 GB | Duration: 22h 49m Snowflake training: from beginner to advanced. Transform data strategy, build rapid data insights, accelerate analytics. What you'll learn Understand data warehousing & cloud computing and Snowflake's unique architecture. Set up and navigate Snowflake, creating databases, schemas, and tables. Load and manage structured & semi-structured data (JSON, ORC, Parquet). Optimize virtual warehouses for cost and performance efficiency. Implement data ingestion & real-time streaming using Snowpipe and staging. Use Time Travel & Zero Copy Cloning for data recovery and replication. Improve query performance with caching, clustering, and search optimization. Manage secure data sharing & access control with RBAC. Utilize advanced Snowflake features like table streams, tasks, and UDFs. Monitor and optimize Snowflake costs using pricing and resource analysis. Integrate Snowflake with BI & data tools like Tableau, Power BI, and Spark. Apply security best practices including encryption and row/column-level security. Automate workflows using Snowflake tasks. Gain hands-on experience through assignments, labs, and real-world use cases. Requirements Enthusiasm and determination to make your mark on the world! Description A warm welcome to the Snowflake: A Comprehensive Guide to Cloud Data Warehousing course by Uplatz.Snowflake is a cloud-based data platform that provides data warehousing, data engineering, data lakes, and analytics capabilities. It is built on top of cloud infrastructure providers like AWS, Azure, and Google Cloud. Unlike traditional databases, Snowflake separates compute and storage, allowing for scalability, high performance, and cost efficiency.Snowflake enables businesses to store, process, and analyze massive amounts of structured and semi-structured data in a highly secure, scalable, and serverless manner.How Snowflake Works?Snowflake operates using a multi-cluster shared data architecture, which consists of three key layers:Storage LayerStores structured and semi-structured data in a compressed, optimized, and columnar format.Data is automatically partitioned and distributed across multiple storage units for high availability.Compute Layer (Virtual Warehouses)Virtual warehouses (clusters) process queries and workloads independently.Compute and storage are decoupled, meaning warehouses can scale up/down without affecting stored data.Multiple warehouses can run concurrently, allowing multiple users and teams to work on different workloads.Cloud Services LayerManages security, metadata, query optimization, and authentication.Supports features like auto-scaling, automatic failover, and query optimization.Core Features of SnowflakeMulti-Cloud SupportRuns seamlessly on AWS, Azure, and Google Cloud, allowing businesses to choose their preferred cloud provider.Separation of Compute and StorageUsers can scale compute resources independently from storage, reducing costs by paying only for what is used.Instant & Elastic ScalabilitySnowflake automatically scales up or down based on workload demands, ensuring high performance and efficiency.Zero-Copy CloningUsers can create multiple copies of a dataset without duplicating storage, making it easier to test and develop without extra cost.Data Sharing & CollaborationSnowflake enables secure data sharing across different accounts, organizations, and cloud providers without the need to copy data.Time Travel & Fail-SafeTime Travel allows users to restore data from historical snapshots (up to 90 days).Fail-Safe provides additional protection for recovering lost data.Support for Semi-Structured DataNatively supports JSON, Avro, ORC, Parquet, and XML, allowing schema-on-read flexibility.Automatic Performance OptimizationSnowflake automatically optimizes storage and query execution without requiring manual indexing or tuning.Built-in Security & ComplianceFeatures end-to-end encryption, access control, and role-based security.Complies with GDPR, HIPAA, SOC 2, and other industry standards.Snowpark & Python SupportSnowflake's Snowpark allows developers to use Python, Java, and Scala for data transformation and machine learning.Benefits of Learning SnowflakeHigh Demand for Snowflake ProfessionalsMany companies are migrating to cloud-based data platforms, making Snowflake skills highly valuable in the job market.Better Career OpportunitiesSnowflake knowledge opens doors to roles like Data Engineer, Data Analyst, Cloud Data Architect, and Snowflake Consultant.Competitive SalariesSnowflake professionals earn high salaries, as demand exceeds supply in the job market.Ease of Learning & UseUnlike traditional databases, Snowflake requires minimal administration, making it easier for beginners to learn.Cloud & Big Data ExpertiseLearning Snowflake enhances cloud computing and data warehousing skills, which are essential in the modern data-driven industry.Integration with BI & AI ToolsSnowflake integrates with Tableau, Power BI, Looker, Python, TensorFlow, and many other analytics and AI tools.Future-Proof TechnologySnowflake is growing rapidly as enterprises shift to cloud-based, scalable solutions.By mastering Snowflake, professionals can position themselves at the forefront of cloud data warehousing, analytics, and big data processing, making it a valuable skill for future-proofing careers in data engineering, analytics, and cloud computing.Snowflake: A Comprehensive Guide to Cloud Data Warehousing - Course CurriculumSection 1: Introduction to SnowflakeOverview of Data WarehousingImportance of Cloud ComputingThe Snowflake Story: Evolution & Use CasesSection 2: Getting Started with SnowflakeSigning Up for SnowflakeExploring the Snowflake UICreating Databases, Schemas, and TablesLoading Data into a TableSetting Up Essential Snowflake ToolsAssignment: Create, Load & Query a TableSection 3: Snowflake Compute - Virtual WarehousesCreating Virtual WarehousesWarehouse Sizes & ScalabilityMaximized vs. Auto Scaling ModesMulti-Cluster Warehouse Scaling PoliciesAssignment: Create a New Virtual WarehouseSection 4: Architecture, Features & PricingSnowflake Key Concepts & ArchitectureCloud Platform Support & Global RegionsSnowflake Editions & ReleasesUnderstanding Snowflake PricingData Integration & InteroperabilityQuiz: Snowflake ConceptsSection 5: Loading & Unloading Structured DataData Ingestion Methods & Best PracticesSteps for Managing Data LoadsPreparing & Staging DataLoading Data from Internal & External StagesSnowpipe: Real-Time Data LoadingQuiz: Data Ingestion in SnowflakeSection 6: Semi-Structured Data HandlingLoading & Unloading JSON DataRunning Analytics on JSON DataWorking with ORC & Parquet FormatsAssignment: Load JSON Data from an S3 BucketSection 7: Data Transformations & StagingQuerying & Transforming Data in Staged FilesMetadata Insights for Staged FilesTransformations During Data LoadSection 8: Managing Databases, Tables & ViewsTemporary, Transient & Permanent TablesExternal Tables & Their UsesOverview of Views & Materialized ViewsTable Design ConsiderationsSection 9: Time Travel, Failsafe & Zero Copy ClonesTime Travel: Restoring to a Specific PointAssignment: Implement Time Travel & RecoveryUnderstanding Failsafe & Storage UtilizationAssignment: Analyze Storage Used by Fail-SafeZero Copy Cloning & Cloning with Time TravelQuiz: Time Travel & Zero Copy ClonesSection 10: Performance OptimizationOptimization Strategies in SnowflakeUsing Dedicated Virtual WarehousesScaling Out with Multi-Cluster Virtual WarehousesMaximizing Query Cache UtilizationLab: Query Caching in ActionClustering Large Tables for Better PerformanceLab: Implementing Cluster KeysSearch Optimization TechniquesQuiz: Performance OptimizationSection 11: Secure Data SharingSecure Data Sharing ConceptsSharing Data with Snowflake & Non-Snowflake UsersAssignment: Share a Table with Another UserLab: Sharing Schemas, Databases & ViewsQuiz: Secure Data SharingSection 12: Snowflake Access ManagementSnowflake's Role-Based Access Control ModelRole Hierarchy: ACCOUNTADMIN, SYSADMIN, SECURITYADMINManaging Custom Roles & PermissionsLab: Assigning Privileges via Custom RolesQuiz: Snowflake Access ManagementSection 13: Advanced FeaturesChange Tracking with Table StreamsAutomating Workflows with TasksUser-Defined Functions (UDFs) & Stored ProceduresColumn-Level & Row-Level SecurityImplementing Resource Monitors Overview Section 1: Introduction to Data Warehouse Lecture 1 Part 1 - Introduction to Data Warehouse Lecture 2 Part 2 - Introduction to Data Warehouse Section 2: Dimensional Modelling Lecture 3 Dimensional Modelling Section 3: ETL and ELT in Data Warehouse Lecture 4 ETL and ELT in Data Warehouse Section 4: Introduction to Snowflake and its Architecture Lecture 5 Introduction to Snowflake and its Architecture Section 5: Snowflake Database and Pricing Lecture 6 Snowflake Database and Pricing Section 6: Snowflake Cost Management Lecture 7 Snowflake Cost Management Section 7: Loading Data into Snowflake Lecture 8 Loading Data into Snowflake Section 8: Transformation while Loading the Data Lecture 9 Transformation while Loading the Data Section 9: Copy Option Lecture 10 Copy Option Section 10: Loading of Semi-structured Data (JSON) Lecture 11 Loading of Semi-structured Data (JSON) Section 11: Loading of Parquet Data and File Format Object Lecture 12 Loading of Parquet Data and File Format Object Section 12: Performance Optimization in Snowflake Lecture 13 Part 1 - Performance Optimization in Snowflake Lecture 14 Part 2 - Performance Optimization in Snowflake Section 13: Uploading Data from AWS to Snowflake Lecture 15 Uploading Data from AWS to Snowflake Section 14: Unloading Data from Snowflake to AWS Lecture 16 Unloading Data from Snowflake to AWS Section 15: Snowpipe Lecture 17 Snowpipe Section 16: Stream Lecture 18 Part 1 - Stream Lecture 19 Part 2 - Stream Section 17: Zero-Copy Cloning and Swapping Lecture 20 Zero-Copy Cloning and Swapping Section 18: Time Travel Lecture 21 Time Travel Lecture 22 Time Travel - Practical Section 19: Fail Safe Lecture 23 Fail Safe Section 20: Types of Tables in Snowflake Lecture 24 Types of Tables in Snowflake Section 21: Snowflake Access Management Lecture 25 Part 1 - Snowflake Access Management Lecture 26 Part 2 - Snowflake Access Management Section 22: Snowflake interview Questions Lecture 27 Snowflake interview Questions Data Engineers - To learn how to design and optimize Snowflake-based ETL/ELT pipelines.,Data Analysts - To perform high-performance SQL queries and optimize reporting workloads.,Data Scientists - To leverage Snowflake's powerful compute capabilities for large-scale data analysis.,Database Administrators (DBAs) - To understand multitenancy, storage, and security features in Snowflake.,Cloud Engineers - To manage virtual warehouses, scaling policies, and cloud integrations.,Business Intelligence (BI) Developers - To work with structured and semi-structured data using tools like Tableau, Power BI, and Looker.,ETL Developers - To learn data ingestion, transformation, and loading best practices in Snowflake.,Security Engineers - To implement role-based access control (RBAC), encryption, and data governance.,IT Managers - To understand cost optimization, pricing, and scaling strategies.,Software Engineers - To learn how to use Snowflake's UDFs, stored procedures, and automation tools.,Solution Architects - To design scalable, secure, and optimized cloud data platforms.,Aspiring Data Engineers & Analysts - To gain hands-on skills in data warehousing and cloud analytics.,IT Professionals Transitioning to Cloud & Big Data - To stay relevant in the evolving cloud-based data ecosystem. 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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

Free Download Personal Data Protection Law (Pdpl - Ksa) - Implementation Published: 3/2025 MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz Language: English | Size: 2.19 GB | Duration: 6h 19m A simplified implementation approach for Personal Data Protection Law (PDPL) of Kingdom of Saudi Arabia What you'll learn Learn to implement Privacy Policies and Procedures from the scratch Gain a clear understanding of the core principles, rights, and obligations outlined in the Saudi Arabia Personal Data Protection Law (PDPL). Learn practical steps to implement PDPL Requirements, including policies, procedures, and controls to ensure compliance. Utilize ready-to-use templates for Privacy Policy, Records, Impact Assessments (DPIA), Risk Assessment, Breach notification, and other compliance activitie Understand how to handle data access, correction, deletion, and portability requests in compliance with PDPL. Learn about the legal bases for data processing under PDPL, including obtaining consent, legitimate interest, and regulatory Requirements. Understand PDPL's restrictions on data transfers outside Saudi Arabia and learn how to comply with data localization Requirements. Understand the roles and responsibilities of Data Controllers and Processors in ensuring PDPL compliance. Requirements No prior experience or knowledge is required. We have designed the course from the basic level. Description The Personal Data Protection Law (PDPL) of Saudi Arabia sets strict regulations on how organizations collect, process, store, and transfer personal data. Non-compliance can result in legal penalties and reputational damage. This course provides a practical and simplified approach to implementing PDPL compliance with ready-to-use templates and real-world guidance.Designed for privacy officers, compliance professionals, IT security teams, auditors, HR managers, and business leaders, this course offers step-by-step guidance, practical insights, and pre-built templates to streamline compliance efforts.What You Will Get in This Course:Ready-Made Templates for Quick Implementation - Includes Privacy Procedures and Guidelines, consent forms, data protection policies, DPIA forms, breach notification templates, data processing agreements, and more.Key Provisions of PDPL - Understand the law's Requirements and core principles.Step-by-Step PDPL Compliance Implementation - Learn practical steps to comply with PDPL.Managing Data Subject Rights - Handling access, correction, deletion, and portability requests.Legal Bases for Processing Personal Data - Consent, legitimate interest, and regulatory Requirements.Cross-Border Data Transfer Compliance - Navigating Saudi Arabia's data localization Requirements.Conducting Data Protection Impact Assessments (DPIA) - Identifying risks and mitigation strategies.Incident Response and Breach Management - Ensuring compliance with PDPL's breach notification rules.Why Take This Course?Practical implementation focus - Move beyond theory and apply PDPL in real-world scenarios.Expert guidance - Learn from industry professionals with deep knowledge of data privacy laws.Time-saving templates - Get access to consent forms, policies, agreements, and compliance checklists.Clear and simplified content - Designed for both beginners and experienced professionals.By the end of this course, you will have the knowledge, tools, and ready-made templates needed to successfully implement PDPL compliance in your organization and avoid legal risks. Overview Section 1: Personal Data Protection Law (The Law) Lecture 1 Introduction Lecture 2 Article 1 (Law) - Terms & Definitions - Video Lecture Lecture 3 Article 1 (Law) - Terms & Definitions - Legal Text Lecture 4 Article 2 (Law) - Scope of the Law - Video Lecture Lecture 5 Article 2 (Law) - Scope of the Law - Legal Text Lecture 6 Article 3 (Law) - Relationship with Other Laws - Video Lecture Lecture 7 Article 3 (Law) - Relationship with Other Laws - Legal Text Lecture 8 Article 4 (Law) - Data Subject Rights - Video Lecture Lecture 9 Article 4 (Law) - Data Subject Rights - Legal Text Lecture 10 Article 5 (Law) & Article 6 (law) - Restriction for Other Usage - Video Lecture Lecture 11 Article 5 (Law) & Article 6 (Law) - Restriction for Other Usage - Legal Text Lecture 12 Article 7 (Law) - Consent should not be forced - Video Lecture Lecture 13 Article 7 (Law) - Consent should not be forced - Legal Text Lecture 14 Article 8 (Law) - Selecting and Monitoring Data Processors - Video Lecture Lecture 15 Article 8 (Law) - Selecting and Monitoring Data Processors - Legal Text Lecture 16 Article 9 (Law) - Restrictions for Data Access - Video Lecture Lecture 17 Article 9 (Law) - Restrictions for Data Access - Legal Text Lecture 18 Article 10 (Law) - Data Collection and Processing Rules - Video Lecture Lecture 19 Article 10 (Law) - Data Collection and Processing Rules - Legal Text Lecture 20 Article 11 (Law) - Purpose and Methods of Data Collection - Video Lecture Lecture 21 Article 11 (Law) - Purpose and Methods of Data Collection - Legal Text Lecture 22 Article 12 (Law) - Privacy Policy Requirements - Video Lecture Lecture 23 Article 12 (Law) - Privacy Policy Requirements - Legal Text Lecture 24 Article 13 (Law) - Information to Data Subjects - Video Lecture Lecture 25 Article 13 (Law) - Information to Data Subjects - Legal Text Lecture 26 Article 14 (Law) - Ensuring Data Accuracy - Video Lecture Lecture 27 Article 14 (Law) - Ensuring Data Accuracy - Legal Text Lecture 28 Article 15 (Law) - Conditions for Data Disclosure - Video Lecture Lecture 29 Article 15 (Law) - Conditions for Data Disclosure - Legal Text Lecture 30 Article 16 (Law) - Restrictions on Data Disclosure - Video Lecture Lecture 31 Article 16 (Law) - Restrictions on Data Disclosure - Legal Text Lecture 32 Article 17 (Law) - Notification of Data Amendments - Video Lecture Lecture 33 Article 17 (Law) - Notification of Data Amendments - Legal Text Lecture 34 Article 18 (Law) - Data Retention and Destruction - Video Lecture Lecture 35 Article 18 (Law) - Data Retention and Destruction - Legal Text Lecture 36 Article 19 (Law) - Data Protection Measures - Video Lecture Lecture 37 Article 19 (Law) - Data Protection Measures - Legal Text Lecture 38 Article 20 (Law) - Breach Notification - Video Lecture Lecture 39 Article 20 (Law) - Breach Notification - Legal Text Lecture 40 Article 21 (Law) - Responding to Data Subject Requests - Video Lecture Lecture 41 Article 21 (Law) - Responding to Data Subject Requests - Legal Text Lecture 42 Article 22 (Law) - Impact Assessments for Data Processing - Video Lecture Lecture 43 Article 22 (Law) - Impact Assessments for Data Processing - Legal Text Lecture 44 Article 23 (Law) - Additional Controls for Health Data - Video Lecture Lecture 45 Article 23 (Law) - Additional Controls for Health Data - Legal Text Lecture 46 Article 24 (Law) - Additional Controls for Credit Data - Video Lecture Lecture 47 Article 24 (Law) - Additional Controls for Credit Data - Legal Text Lecture 48 Article 25 (Law) - Advertising or Awareness Materials - Video Lecture Lecture 49 Article 25 (Law) - Advertising or Awareness Materials - Legal Text Lecture 50 Article 26 (Law) - Data Processing for Marketing - Video Lecture Lecture 51 Article 26 (Law) - Data Processing for Marketing - Legal Text Lecture 52 Article 27 (Law) - Research and Statistics - Video Lecture Lecture 53 Article 27 (Law) - Research and Statistics - Legal Text Lecture 54 Article 28 (Law) - Copying Official Documents - Video Lecture Lecture 55 Article 28 (Law) - Copying Official Documents - Legal Text Lecture 56 Article 29 (Law) - Transferring Data Outside the Kingdom - Video Lecture Lecture 57 Article 29 (Law) - Transferring Data Outside the Kingdom - Legal Text Lecture 58 Article 30 (Law) - Competent Authority's Role - Video Lecture Lecture 59 Article 30 (Law) - Competent Authority's Role - Legal Text Lecture 60 Article 31 (Law) - Record-Keeping Requirements - Video Lecture Lecture 61 Article 31 (Law) - Record-Keeping Requirements - Legal Text Lecture 62 Article 32 (Law) - Repealed - Legal Text Lecture 63 Article 33 (Law) - Licensing and Compliance Monitoring - Legal Text Lecture 64 Article 34 (Law) - Complaint Handling - Video Lecture Lecture 65 Article 34 (Law) - Complaint Handling - Legal Text Lecture 66 Article 35 (Law) - Penalties for Sensitive Data Violations - Video Lecture Lecture 67 Article 35 (Law) - Penalties for Sensitive Data Violations - Legal Text Lecture 68 Article 36 (Law) - General Penalties - Video Lecture Lecture 69 Article 36 (Law) - General Penalties - Legal Text Lecture 70 Article 37 (Law) - Inspection and Control Powers - Legal Text Lecture 71 Article 38 (Law) - Confiscation and Penalty Decisions - Video Lecture Lecture 72 Article 38 (Law) - Confiscation and Penalty Decisions - Legal Text Lecture 73 Article 39 (Law) - Disciplinary Actions - Video Lecture Lecture 74 Article 39 (Law) - Disciplinary Actions - Legal Text Lecture 75 Article 40 (Law) - Compensation for Damages - Video Lecture Lecture 76 Article 40 (Law) - Compensation for Damages - Legal Text Lecture 77 Article 41 (Law) - Confidentiality Obligation - Video Lecture Lecture 78 Article 41 (Law) - Confidentiality Obligation - Legal Text Lecture 79 Article 42 (Law) - Issuance of Regulations - Legal Text Lecture 80 Article 43 (Law) - Effective Date of the Law - Legal Text Section 2: The Implementing Regulation of PDPL (Implementing Regulation) Lecture 81 Article 1 (Implementing Regulation) - Terms & Definitions - Legal Text Lecture 82 Article 2 (Implementing Regulation) - Personal / Family Use - Video Lecture Lecture 83 Article 2 (Implementing Regulation) - Personal / Family Use - Legal Text Lecture 84 Article 3 (Implementing Regulation) - Data Subject Rights - Video Lecture Lecture 85 Article 3 (Implementing Regulation) - Data Subject Rights - Legal Text Lecture 86 Article 4 (Implementing Regulation) - Right to be Informed - Video Lecture Lecture 87 Article 4 (Implementing Regulation) - Right to be Informed - Legal Text Lecture 88 Article 5 - Right to Access Personal Data - Video Lecture Lecture 89 Article 5 - Right to Access Personal Data - Legal Text Lecture 90 Article 6 - Right to Request Access to Personal Data - Video Lecture Lecture 91 Article 6 - Right to Request Access to Personal Data - Legal Text Lecture 92 Article 7 - Correction of Personal Data - Video Lecture Lecture 93 Article 7 - Correction of Personal Data - Legal Text Lecture 94 Article 8 - Destruction of Personal Data - Video Lecture Lecture 95 Article 8 - Destruction of Personal Data - Legal Text Lecture 96 Article 9 (Implementing Regulation) - Anonymisation - Video Lecture Lecture 97 Article 9 (Implementing Regulation) - Anonymisation - Legal Text Lecture 98 Article 10 - Means of Communication - Video Lecture Lecture 99 Article 10 - Means of Communication - Legal Text Lecture 100 Article 11 (Implementing Regulation) - Consent - Video Lecture Lecture 101 Article 11 (Implementing Regulation) - Consent - Legal Text Lecture 102 Article 12 (Implementing Regulation) - Consent withdrawal - Video Lecture Lecture 103 Article 12 (Implementing Regulation) - Consent withdrawal - Legal Text Lecture 104 Article 13 (Implementing Regulation) - Legal Guardian - Video Lecture Lecture 105 Article 13 (Implementing Regulation) - Legal Guardian - Legal Text Lecture 106 Article 14 - Actual Interest of Data Subject - Video Lecture Lecture 107 Article 14 - Actual Interest of Data Subject - Legal Text Lecture 108 Article 15 - Collecting Data from Third Parties - Video Lecture Lecture 109 Article 15 - Collecting Data from Third Parties - Legal Text Lecture 110 Article 16 - Processing for Legitimate Interest - Video Lecture Lecture 111 Article 16 - Processing for Legitimate Interest - Legal Text Lecture 112 Article 17 - Choosing the Processor - Video Lecture Lecture 113 Article 17 - Choosing the Processor - Legal Text Lecture 114 Article 18 - Further Processing of Personal Data - Video Lecture Lecture 115 Article 18 - Further Processing of Personal Data - Legal Text Lecture 116 Article 19 (Implementing Regulation) - Data Minimisation - Video Lecture Lecture 117 Article 19 (Implementing Regulation) - Data Minimisation - Legal Text Lecture 118 Article 20 - Disclosure of Personal Data - Video Lecture Lecture 119 Article 20 - Disclosure of Personal Data - Legal Text Lecture 120 Article 21 - Public Interest Purposes - Video Lecture Lecture 121 Article 21 - Public Interest Purposes - Legal Text Lecture 122 Article 22 - Correction of Personal Data - Video Lecture Lecture 123 Article 22 - Correction of Personal Data - Legal Text Lecture 124 Article 23 (Implementing Regulation) - Information Security - Video Lecture Lecture 125 Article 23 (Implementing Regulation) - Information Security - Legal Text Lecture 126 Article 24 - Notification of Personal Data Breach - Video Lecture Lecture 127 Article 24 - Notification of Personal Data Breach - Legal Text Lecture 128 Article 25 (Implementing Regulation) - Impact Assessment - Video Lecture Lecture 129 Article 25 (Implementing Regulation) - Impact Assessment - Legal Text Lecture 130 Article 26 - Processing Health Data - Video Lecture Lecture 131 Article 26 - Processing Health Data - Legal Text Lecture 132 Article 27 - Processing Credit Data - Video Lecture Lecture 133 Article 27 - Processing Credit Data - Legal Text Lecture 134 Article 28 - Advertising or Awareness Purposes - Video Lecture Lecture 135 Article 28 - Advertising or Awareness Purposes - Legal Text Lecture 136 Article 29 (Implementing Regulation) - Direct Marketing - Video Lecture Lecture 137 Article 29 (Implementing Regulation) - Direct Marketing - Legal Text Lecture 138 Article 30 - Scientific, Research, or Statistical Purposes - Video Lecture Lecture 139 Article 30 - Scientific, Research, or Statistical Purposes - Legal Text Lecture 140 Article 31 - Photographing or Copying Official Documents - Video Lecture Lecture 141 Article 31 - Photographing or Copying Official Documents - Legal Text Lecture 142 Article 32 - Data Protection Officer - Video Lecture Lecture 143 Article 32 - Data Protection Officer - Legal Text Lecture 144 Article 33 - Records of Processing Activities - Video Lecture Lecture 145 Article 33 - Records of Processing Activities - Legal Text Lecture 146 Article 34 - National Register of Controllers - Video Lecture Lecture 147 Article 34 - National Register of Controllers - Legal Text Lecture 148 Article 35 - Accreditation bodies - Legal Text Lecture 149 Article 36 - Auditing - Legal Text Lecture 150 Article 37 - Filing and Processing Complaints - Video Lecture Lecture 151 Article 37 - Filing and Processing Complaints - Legal Text Lecture 152 Article 38 - Publication and Enforcement - Legal Text Section 3: Regulation on Personal Data Transfer Outside the Kingdom (Transfer Regulation) Lecture 153 Article 1 (Transfer Regulation) - Terms & Definitions - Legal Text Lecture 0 Article 2 (Transfer Regulation) - Other Purposes - Video Lecture Lecture 154 Article 2 (Transfer Regulation) - Other Purposes - Legal Text Lecture 0 Article 3 - Adequate Level of Protection for Personal Data - Video Lecture Lecture 155 Article 3 - Adequate Level of Protection for Personal Data - Legal Text Lecture 0 Article 4 (Transfer Regulation) - Exempted Cases - Video Lecture Lecture 156 Article 4 (Transfer Regulation) - Exempted Cases - Legal Text Lecture 0 Article 5 (Transfer Regulation) - Subsequent Transfer - Video Lecture Lecture 157 Article 5 (Transfer Regulation) - Subsequent Transfer - Legal Text Lecture 0 Article 6 (Transfer Regulation) - Revocation of Exemption - Video Lecture Lecture 158 Article 6 (Transfer Regulation) - Revocation of Exemption - Legal Text Lecture 0 Article 7 (Transfer Regulation) - Risk Assessment - Video Lecture Lecture 159 Article 7 (Transfer Regulation) - Risk Assessment - Legal Text Lecture 0 PDPL Implementation - Step 1 Lecture 0 PDPL Implementation - Step 2 Lecture 0 PDPL Implementation - Step 3 Privacy and Data Protection Officers - Individuals responsible for ensuring compliance with PDPL and implementing data protection strategies.,Compliance and Legal Professionals - Lawyers, consultants, and compliance officers who need to understand PDPL regulations and how they impact business operations.,Information Security Professionals - Cybersecurity and IT professionals involved in securing personal data, preventing breaches, and ensuring data privacy compliance.,IT and System Administrators - Professionals responsible for implementing technical and organizational measures to protect personal data.,Risk Management and Audit Professionals - Internal and external auditors, risk managers, and governance teams assessing PDPL compliance within their organizations. 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Free Download Cybersecurity & Cryptography - Secure Data & Networks Published: 2/2025 MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz Language: English | Size: 12.19 GB | Duration: 15h 33m Master Encryption & Cybersecurity: SSL/TLS, Hashing, Digital Certificates & Secure Data What you'll learn Understand symmetric and asymmetric encryption, including AES, RSA, and hybrid encryption methods. Analyze TLS/SSL handshakes, cipher suites, and encryption protocols using Wireshark and OpenSSL. Implement secure cryptographic techniques to protect data integrity, authentication, and confidentiality. reate and manage digital certificates, Certificate Authorities (CAs), and secure key exchange mechanisms. Perform hands-on encryption and decryption using OpenSSL, implementing real-world cryptographic security. Explore hashing techniques (SHA, HMAC, GCM) for data integrity, authentication, and cybersecurity applications. Requirements No prior knowledge required - this course starts from scratch and covers all concepts in a beginner-friendly way. Description This course will teach you cryptography from scratch in a simple and practical way. You will learn how encryption secures the internet, protects data, and prevents cyber attacks.We start with encryption, hashing, and digital certificates before moving to advanced topics like SSL/TLS, secure key exchange, and real-world cybersecurity applications. You will understand how websites like WhatsApp, Gmail, and Zoom use encryption to protect data from hackers and cyber threats.What you will learn:The difference between symmetric and asymmetric encryption (AES, RSA, and more)How SSL/TLS encryption secures websites and online transactionsHashing techniques (SHA, HMAC) for data integrity and authenticationHow to use OpenSSL and Wireshark to analyze encrypted connectionsSecure key exchange methods like Diffie-Hellman and Public Key Infrastructure (PKI)Practical demonstrations on encryption, decryption, and certificate managementWho Is This Course For?Beginners in cybersecurity and ethical hackingIT professionals, developers, and network engineersAnyone interested in secure digital communication and data protectionNo prior knowledge is required. By the end, you will have a strong foundation in cryptography and be able to apply encryption in real-world security scenarios confidently.Join now and start learning how encryption protects sensitive data and secures online communication effectively today. Overview Section 1: CryptoGraphy Training Lecture 1 Introduction to Cryptography : Encryption & Hashing Lecture 2 Cryptography Fundamentals & SSL/TLS Handshake : Secure Your Communication Lecture 3 How Certificates, Encryption & PKI Work Together Lecture 4 Understanding Secure Communication with TLS/SSL and Wireshark Analysis Lecture 5 SSL & TLS Uncovered: The Tech Behind Secure Messaging Lecture 6 Encrypting Files with OpenSSL: Symmetric & Asymmetric Cryptography Lecture 7 Hands-On with OpenSSL & Cryptographic Keys Lecture 8 Symmetric Key Encryption (DES & AES) Lecture 9 How Cryptography Secures the Internet: From TLS to Digital Signature Lecture 10 OpenSSL Deep Dive: Practical Cryptography in Action Lecture 11 AES & Quantum Computing : Can Quantum Computers Crack Encryption? Lecture 12 Hands-On Encryption: Symmetric Cryptography in Action Lecture 13 Block Ciphers & Encryption Modes Lecture 14 How TLS Encryption Keeps Your Data Safe Lecture 15 Advanced Encryption Techniques: CFB Mode in Action Lecture 16 TLS Handshake & Secure Communication Lecture 17 The Role of Hashing in Secure Communication & Data Protection Lecture 18 Encryption, Hashing & Key Exchange in TLS Lecture 19 Inside SSL/TLS: The Security Behind HTTPS Lecture 20 Why Hashing Is Critical for Secure Authentication Lecture 21 Secure Hashing Techniques: Preventing Password Attacks Lecture 22 The Role of Hashing in Cybersecurity & Digital Signatures Lecture 23 Data Integrity & Authentication with Real-World Examples Lecture 24 Symmetric vs. Asymmetric Encryption & Hybrid Encryption Explained Lecture 25 Symmetric Encryption & Key Exchange Challenges (AES Example) Lecture 26 RSA Algorithm & Secure Key Exchange for Cybersecurity Lecture 27 Secure Communication with Asymmetric Cryptography Lecture 28 Mastering Key Exchange with RSA & Diffie-Hellman for Secure Communication Lecture 29 Ensuring Data Integrity & Non-Repudiation in Secure Communication Lecture 30 Digital Signatures Explained: DSA, ECDSA & RSA Algorithms Lecture 31 Secure Communication with Public & Private Keys - RSA, SSH, and Hashing Lecture 32 Securing Data with Cryptography | SSH, RSA, and Hashing Lecture 33 Mastering TLS/SSL: Secure Your Communications with HTTPS & PKI Lecture 34 PKI Infrastructure & SSL/TLS Handshake: Securing Communication Lecture 35 SSL/TLS Handshake : Securing Communication with Cryptography Lecture 36 Root CAs, Sub-CAs & Certificate Chains for Secure Communication Lecture 37 SSL/TLS Deep Dive: Certificates, Handshakes & Secure Communication Lecture 38 Implementing SSL/TLS for Secure Communication Lecture 39 SSL/TLS Certificate Creation & Validation Lecture 40 Secure Your Server with SSL/TLS Lecture 41 Secure Communication with OpenSSL & Wireshark Lecture 42 SSL/TLS Handshake: Encryption, 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Free Download Pluralsight - Introduction to Data Visualization for Data Analysts Released 2/2025 By Ben Howard MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch Level: Beginner | Genre: eLearning | Language: English + subtitle | Duration: 32m 17s | Size: 106 MB Data is everywhere, but seeing it differently unlocks insights. This course teaches you to transform raw data into clear visualizations, solving real-world problems with Excel, Power BI, and Tableau, thereby making data clear and accessible for all. Data is the new gold-no doubt about it. But how do you mine to find it? In this course, Introduction to Data Visualization for Data Analysts, you'll learn how to create high-impact, high-quality data visualizations that effectively find and expose golden nuggets hidden in data. First, you'll explore the fundamentals of data visualization, including its definition and the key components of compelling visual representations. Next, you'll dive into the data visualization workflow, gaining the skills to transform raw data into meaningful visual stories. Finally, you'll discover how data visualizations can solve real-world problems using industry-standard tools like Excel, Power BI, and Tableau. When you're finished with this course, you'll have the expertise to present complex data in a clear, visually engaging way, making it accessible to non-technical audiences. Homepage: https://www.pluralsight.com/courses/introduction-data-visualization-data-analysts DOWNLOAD NOW: Pluralsight - Introduction to Data Visualization for Data Analysts Fileaxa https://fileaxa.com/ileb5az9wcq7/alqps.Introduction.to.Data.Visualization.for.Data.Analysts.rar TakeFile https://takefile.link/sm4lz0ejaoht/alqps.Introduction.to.Data.Visualization.for.Data.Analysts.rar.html Rapidgator https://rg.to/file/d2617650adce45463e8acc84713d28d1/alqps.Introduction.to.Data.Visualization.for.Data.Analysts.rar.html Fikper Free Download https://fikper.com/usFE5cK1Ce/alqps.Introduction.to.Data.Visualization.for.Data.Analysts.rar.html : No Password - Links are Interchangeable

Free Download Pluralsight - Databricks Certified Data Analyst SQL in the Lakehouse Released 2/2025 By Lucian Lazar MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch Level: Beginner | Genre: eLearning | Language: English + subtitle | Duration: 1h 29m | Size: 195 MB Learn to query, analyze, and manage data in Databricks SQL. This course prepares you for the Databricks Certified Data Analyst Associate exam with skills in SQL queries, advanced analytics, and data management in a Lakehouse environment. Data analysts and professionals often struggle with confidently querying and managing data in a modern Lakehouse environment while preparing for the Databricks Certified Data Analyst Associate certification. In this course, Databricks Certified Data Analyst: SQL in the Lakehouse, you'll gain the ability to query, analyze, and manage data efficiently using Databricks SQL. First, you'll explore how to set up and navigate the Databricks environment and write efficient SQL queries to retrieve and refine data. Next, you'll discover techniques for performing advanced data aggregations, such as subtotals, totals, and granular analysis, using tools like GROUP BY, CUBE, and ROLLUP. Finally, you'll learn how to manage structured and nested data while adhering to data quality and consistency standards essential for Lakehouse environments. When you're finished with this course, you'll have the skills and knowledge of Databricks SQL needed to confidently analyze data, optimize query performance, and prepare for the Databricks Certified Data Analyst Associate certification. Homepage: https://app.pluralsight.com/library/courses/databricks-certified-data-analyst-sql-lakehouse-cert/table-of-contents DOWNLOAD NOW: Pluralsight - Databricks Certified Data Analyst SQL in the Lakehouse Fileaxa https://fileaxa.com/925w88k5fh81/evftz.Databricks.Certified.Data.Analyst.SQL.in.the.Lakehouse.rar TakeFile https://takefile.link/ft33rhl2id4k/evftz.Databricks.Certified.Data.Analyst.SQL.in.the.Lakehouse.rar.html Rapidgator https://rg.to/file/81af2eafc4b9e962554be5eaf14c6334/evftz.Databricks.Certified.Data.Analyst.SQL.in.the.Lakehouse.rar.html Fikper Free Download https://fikper.com/jiahX2kaXo/evftz.Databricks.Certified.Data.Analyst.SQL.in.the.Lakehouse.rar.html : No Password - Links are Interchangeable

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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 Data Analysis for Market Research with Excel & Tableau Published: 3/2025 Created by: Christ Raharja MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz, 2 Ch Level: All | Genre: eLearning | Language: English | Duration: 21 Lectures ( 2h 7m ) | Size: 1.23 GB Conduct market segmentation analysis, market trend analysis, and competitor pricing analysis with Excel and Tableau What you'll learn Learn basic fundamentals of market research, such as getting to know its use cases and the difference between quantitative and qualitative market research Learn how to conduct market research for cosmetic product in Excel Learn how to visualize data using bar chart, pie chart, scatter plot in Excel Learn how to conduct market research for restaurant using Tableau Learn how to segment customer data by demographics, such as gender and skin type Learn how to conduct price range analysis Learn how to analyze market share Learn how to find correlation between price and product rating Learn how to segment market by product ingredients Learn how to analyze customer preferences regarding product size and packaging type Learn how to analyze competitors pricing strategies based on restaurant type Learn how to conduct price positioning analysis based on cuisine type Learn how to conduct location based pricing analysis Learn how to analyze the relationship between restaurant facility and pricing Learn how to analyze the relationship between food prices and ratings Learn how to clean dataset by removing missing values and duplicates Learn how to analyze and visualize market research data using Julius AI Requirements No previous experience in market research is required Basic knowledge in statistics Description Welcome to Data Analysis for Market Research with Excel & Tableau course. This is a comprehensive project based course where you will learn how to analyze market trends, segment customer data, evaluate competitor strategies, and visualize data using Microsoft Excel and Tableau. This course is a perfect combination between statistics and business intelligence, making it an ideal opportunity to practice your analytical skills while improving your technical knowledge in market research methodologies. In the introduction session, you will learn the basic fundamentals of market research, such as getting to know its use cases, step by step process, and also learn the difference between quantitative and qualitative market research. Then, in the next section, we will find and download market research dataset from Kaggle, it is a platform that provides a wide range of datasets from various industries. Afterward, we will set up browser based Microsoft Excel, enabling us to have the necessary tools to perform data analysis and visualization effectively. We will go through the basic functionalities like sorting, filtering, conditional formatting, and pivot tables to organize and summarize data efficiently. Following that, we will clean the market research data, specifically we will remove missing values and duplicates, making sure the dataset is accurate and ready for analysis. Then, after that, we will conduct exploratory data analysis to identify patterns, trends, and key insights within the dataset. This will help us better understand the structure of the data and gain a clear Overview of its composition and relationships between variables. Then, in the next section, we will conduct extensive market research for cosmetic products using Microsoft Excel. In the first section, we will segment customer data by skin type. This will enable us to identify which skin concerns are most addressed by brands and optimize product offerings based on demand. Next, we will analyze the price range by category. This will allow us to assess pricing strategies, identify affordability trends, and find gaps in premium or budget-friendly markets. Following that, we will analyze market share. This will enable us to determine industry leaders, track emerging competitors, and uncover opportunities for new product launches. Then, in the next section, we will find the correlation between price and customer reviews. This will enable us to assess whether higher-priced products receive better ratings and guide pricing and marketing decisions. Next, we will analyze ingredient-based segmentation. This will assist us to identify trending ingredients, consumer preferences, and how brands differentiate their formulations. In the next section, we will then segment products by gender. This will enable us to understand market demand for male and females. After that, we will conduct a product size preference analysis. This helps determine which product sizes are most favored by consumers, allowing brands to optimize packaging and distribution strategies. In the last section, we will also segment products by packaging type. This will enable us to identify packaging trends, sustainability preferences, and functional design choices that influence purchases. Then, in the next section, we will conduct market research for restaurants using Tableau. In the first section, we will analyze restaurant type pricing strategies to understand how different restaurant types position their prices. Next, we will examine cuisine type and price positioning to identify which cuisines are premium or budget-friendly. Following that, we will conduct a location-based competitor pricing analysis to compare restaurant prices across different areas. Then, we will assess the impact of online ordering on ratings and pricing to determine if it influences customer perception and pricing strategies. In addition, we will find correlation between price and rating to see if higher-rated restaurants tend to have higher prices. Lastly, at the end of the course, we will also learn to analyze data using AI, where you can input any data and let AI automatically extract valuable insights from the data.First of all, before getting into the course, we need to ask ourselves these questions: why should we learn about market research? Well, here is my answer, market research helps businesses understand customer preferences, optimize pricing strategies, and stay ahead of competitors. By analyzing trends and consumer behavior, companies can make data driven decisions, reduce risks, and maximize profitability.Below are things that you can expect to learn from this course:Learn basic fundamentals of market research, such as getting to know its use cases, the difference between quantitative and qualitative research, and understand market research step by step processLearn how to clean dataset by removing missing values and duplicatesLearn how to conduct market research for cosmetic product in ExcelLearn how to visualize data using bar chart, pie chart, scatter plot in ExcelLearn how to segment customer data by demographics, such as gender and skin typeLearn how to conduct price range analysisLearn how to analyze market shareLearn how to find correlation between price and product ratingLearn how to segment market by product ingredientsLearn how to analyze customer preferences regarding product size and packaging typeLearn how to conduct market research for restaurant using TableauLearn how to analyze competitors pricing strategies based on restaurant typeLearn how to conduct price positioning analysis based on cuisines typeLearn how to conduct location based pricing analysisLearn how to analyze the relationship between restaurant facility and pricingLearn how to analyze the relationship between food prices and ratingsLearn how to analyze and visualize market research data using Julius AI Who this course is for Data analysts who are interested in analyzing and visualizing market research data using Microsoft Excel and Tableau Business consultants who are interested in transforming market research data into valuable business insights Homepage: https://www.udemy.com/course/data-analysis-for-market-research-with-excel-tableau/ DOWNLOAD NOW: Data Analysis for Market Research with Excel & Tableau Rapidgator https://rg.to/file/2b2078fa36220aea60c983e47d54489c/qpwyh.Data.Analysis.for.Market.Research.with.Excel..Tableau.part1.rar.html https://rg.to/file/850d40daa273ed5e7c2da3bce223e44f/qpwyh.Data.Analysis.for.Market.Research.with.Excel..Tableau.part2.rar.html Fikper Free Download https://fikper.com/z1iDzYqZt3/qpwyh.Data.Analysis.for.Market.Research.with.Excel..Tableau.part1.rar.html https://fikper.com/TfJ0wXAPCY/qpwyh.Data.Analysis.for.Market.Research.with.Excel..Tableau.part2.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. 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