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epub | 2.63 MB | English | ASIN:9781597801690 | Author: Glen Cook | Year: 2010 Description: Category:Fiction, Science Fiction https://ddownload.com/t7eoxeqt1b5c/Cook.Glen.-.Stars.End.Starfishers.03.-.2010.rar https://rapidgator.net/file/74cd3d8455255cf9d92fbf74be48155f/Cook.Glen.-.Stars.End.Starfishers.03.-.2010.rar https://turbobit.net/wjun3fb1anb1/Cook.Glen.-.Stars.End.Starfishers.03.-.2010.rar.html

epub | 1.06 MB | English | ASIN:9781250858641 | Author: William Deresiewicz | Year: 2022 Description: Category:Sociology, Technology, Nonfiction https://fileaxa.com/s9mm94dfqjxq/The.End.of.Solitude_.Selected.Essays.on.Culture.and.Society.by.William.Deresiewicz..rar https://ddownload.com/sbiqrlmmjv52/The.End.of.Solitude_.Selected.Essays.on.Culture.and.Society.by.William.Deresiewicz..rar https://rapidgator.net/file/7c9134dd63e3f348112db4fdae438ff6/The.End.of.Solitude_.Selected.Essays.on.Culture.and.Society.by.William.Deresiewicz..rar https://turbobit.net/xfnb3mmnwuni/The.End.of.Solitude_.Selected.Essays.on.Culture.and.Society.by.William.Deresiewicz..rar.html

Free Download Snowflake End-to-End Cloud Data Warehousing & Analytics Published 10/2024 Created by Uplatz Training MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch Genre: eLearning | Language: English | Duration: 39 Lectures ( 30h 44m ) | Size: 15.3 GB Build Cloud Data Platform with Snowflake. Accelerate your career in data engineering, data science, and cloud computing. What you'll learn Understand Data Warehousing Fundamentals - Gain foundational knowledge of data warehousing, including concepts and principles, and how they relate to Snowflake. Master Data Modeling Techniques - Learn best practices for designing efficient data models to optimize performance and storage in Snowflake. Explore Snowflake Architecture - Understand Snowflake's unique architecture and how it supports cloud-native data warehousing and analytics. Create and Manage Data Warehouses in Snowflake - Develop practical skills in creating and managing data warehouses using Snowflake's interface and tools. Efficiently Load and Unload Data - Learn to load and unload data using various methods, including from external storage solutions (AWS, Azure, GCP). Effectively Manage Complex Data Formats - Handle complex formats like JSON and Parquet using Snowflake. Implement Data Transformations - Gain expertise in performing transformations during the data loading process to clean and structure data efficiently. Learn Snowflake's performance optimization features - caching, clustering and resource monitoring to ensure cost-effective and high-performance data operations. Leverage Time Travel, Fail Safe, and Zero-Copy Clone - Explore Snowflake's advanced features like Time Travel, Fail Safe, and Zero-Copy Clone for data recovery. Manage Secure Data Sharing - Learn how to securely share data within and outside of Snowflake environments, including with non-Snowflake users. Implement Best Practices for Snowflake Administration - Master account administration, access management, and apply best practices for efficient Snowflake usage Requirements Enthusiasm and determination to make your mark on the world! Description A warm welcome to the Snowflake: End-to-End Cloud Data Warehousing & Analytics course by Uplatz.Snowflake is a cloud-based data warehousing platform designed to handle massive volumes of structured and semi-structured data. It's built from the ground up to leverage cloud infrastructure, offering scalability, performance, and ease of use. Snowflake is not tied to any specific cloud provider; it runs on AWS, Microsoft Azure, and Google Cloud Platform (GCP), providing flexibility for businesses to use their preferred cloud platform.Snowflake's architecture, scalability, and advanced features make it a powerful platform for modern data warehousing, analytics, and data engineering. Its flexibility to handle massive datasets, structured and semi-structured data, and multi-cloud capabilities has positioned it as a preferred choice for businesses looking to leverage cloud-native data platforms.How Snowflake WorksSnowflake operates using a unique architecture that separates storage and compute, allowing for independent scaling of resources. Key methodology in its working involves:Data Storage: Snowflake stores data in a compressed, columnar format on cloud storage. Data is logically organized into databases, schemas, and tables, but physically, Snowflake manages how data is stored and optimized on the backend.Compute Layer (Virtual Warehouses): Compute resources, called virtual warehouses, are independent clusters of resources that process queries and workloads. Virtual warehouses can be scaled up or down based on performance needs and can run multiple, parallel queries without interfering with each other.Cloud Services Layer: This layer manages metadata, optimization, security, and query parsing. It handles authentication, query planning, and transaction management, allowing Snowflake to offer features like automated scaling, data sharing, and access controls.The separation of storage and compute makes Snowflake highly flexible. You can store large volumes of data without worrying about compute costs when the data is not being queried. Conversely, you can scale compute resources for demanding queries without impacting the storage cost.Core Features of SnowflakeSeparation of Storage and Compute: Snowflake allows independent scaling of compute resources (virtual warehouses) and storage. This flexibility helps optimize costs and performance based on workload requirements.Multi-Cloud Availability: Snowflake runs on all major cloud platforms (AWS, Azure, GCP), offering cross-cloud functionality and flexibility in choosing cloud providers.Instant Elasticity: Snowflake can instantly scale compute resources up or down based on workload demands. You can run multiple queries simultaneously without performance degradation.Data Sharing: Snowflake offers secure data sharing across organizations or between Snowflake accounts without moving or copying data. This feature allows real-time data collaboration.Support for Structured and Semi-Structured Data: Snowflake natively supports a wide range of data formats, including JSON, Parquet, Avro, and XML, making it easier to load and query semi-structured data alongside structured data.Zero-Copy Cloning: This feature allows you to create a copy of databases, tables, and schemas instantly without duplicating the data. It enables quick testing or development without additional storage costs.Time Travel and Fail-Safe: Time Travel allows users to access historical data versions for up to 90 days, facilitating recovery from accidental data changes or deletions. Fail-Safe provides an additional data recovery mechanism for a defined period.Automatic Scaling and Concurrency: Snowflake automatically manages concurrency, allowing multiple users to query data simultaneously without affecting performance, and automatically scales up or down depending on demand.Security and Compliance: Snowflake includes robust security features such as end-to-end encryption, role-based access controls, and multi-factor authentication (MFA). It complies with industry standards like GDPR, HIPAA, and SOC 2.Snowpipe: Snowpipe is Snowflake's continuous data ingestion tool that automates loading data from external sources (such as AWS S3, Azure Blob, GCP Storage) into Snowflake in near real-time.Snowflake - Course CurriculumIntroduction to Data Warehouse - part 1Introduction to Data Warehouse - part 2Data Modelling - part 1Data Modelling - part 2Introduction to Snowflake and ArchitectureCreate Datawarehouse in SnowflakeLoad Data in a TableSnowflake Pricing and Resource MonitorLoading Data from External StorageTransformations while LoadingCopy Options and File Formats - part 1Copy Options and File Formats - part 2Loading of JSONLoading of ParquetData UnloadingPerformance Optimizations in SnowflakeCaching and ClusteringLoading Data from AWS External StorageSnowpipe in AWSLoading Data from Azure CloudSnowpipe in AzureLoading and Uploading Data from GCPTime Travel - part 1Time Travel - part 2Fail Safe and Types of TablesZero Copy CloneData Sharing - part 1Data Sharing - part 2Data Sharing with non-Snowflake Users - part 1Data Sharing with non-Snowflake Users - part 2Secure vs Normal ViewData SamplingScheduling TasksMaterialized View - part 1Materialized View - part 2Dynamic Data MaskingAccess Management and Account Administration - part 1Access Management and Account Administration - part 2Best Practices in Snowflake Who this course is for Data Engineers - Looking to build data pipelines and handle data transformations within Snowflake. Data Analysts - Aiming to perform data querying, reporting, and analysis on cloud-based data platforms. Beginners and newbies aspiring for a career in Cloud Data Warehousing and Snowflake. Data Architects - Designing scalable cloud data architectures using Snowflake's features. Solution Architects - Architecting comprehensive solutions that integrate Snowflake for efficient data management and analytics. Cloud Engineers - Implementing and managing cloud infrastructure for data operations on Snowflake. Business Intelligence Professionals - Using Snowflake for analytics, reporting, and generating business insights. ETL Developers - Handling Extract, Transform, Load (ETL) processes using Snowflake for efficient data movement and transformation. Data Scientists - Working with large datasets, performing advanced analytics, and leveraging Snowflake for machine learning workflows. Cloud Data Engineers - Focused on developing data solutions in the cloud using Snowflake's infrastructure. Database Administrators (DBAs) - Transitioning to cloud data platforms like Snowflake for managing and optimizing data storage and access. Developers - Needing to integrate Snowflake with other applications and services. IT Professionals - Transitioning to cloud-based data solutions and aiming to broaden their cloud data expertise. 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Free Download SAP Hybris Commerce - Front End Development Course Published 10/2024 MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch Language: English | Duration: 59m | Size: 567 MB Master Front End with SAP Hybris: Create Dynamic, Accessible, and Optimized Interfaces for High-Performance E-Commerce What you'll learn Learn basic concepts of SAP Hybris Commerce How to create the front end of an e-commerce How to create CMS components How to create high-performance applications Requirements Knowledge in HTML, CSS, and JavaScript Description The SAP Hybris Commerce - Front End Development course is an essential opportunity for developers who wish to specialize in creating dynamic and efficient user interfaces for e-commerce platforms. Throughout the course, parti[beeep]nts learn to use SAP Hybris, one of the leading e-commerce solutions in the market, focusing on the techniques and tools necessary for front-end development.Topics covered include the structure and architecture of SAP Hybris, along with concepts of responsive design. Students are trained to create intuitive and engaging user experiences using HTML5, CSS3, JavaScript, and other cutting-edge technologies.The course also emphasizes best practices for performance optimization, ensuring that the developed websites are fast, accessible, and compatible with various devices. Parti[beeep]nts learn how to write performant code by following principles of efficiency and best development practices to ensure applications run smoothly and responsively, even under high demand.Upon completing the course, parti[beeep]nts will have gained practical skills and theoretical knowledge that enable them to contribute effectively to e-commerce development projects, ensuring a superior shopping experience for end users. This course is ideal for developers looking to enhance their skills and stand out in the competitive tech and e-commerce market.This course equips developers with the skills to create highly efficient, responsive, and user-friendly e-commerce interfaces using SAP Hybris. Who this course is for Developers who want to learn how to create front end using SAP Hybris Homepage https://www.udemy.com/course/sap-hybris-commerce-front-end-development-course/ Screenshot Rapidgator https://rg.to/file/4cd3382aa66648b640fcc421540cbff2/kyykb.SAP.Hybris.Commerce..Front.End.Development.Course.rar.html Fikper Free Download https://fikper.com/d3wcWILOBH/kyykb.SAP.Hybris.Commerce..Front.End.Development.Course.rar.html No Password - Links are Interchangeable

Free Download Oracle Fusion End to End Tax Module Training sessions Last updated 5/2020 Created by Srinibas Mohanty MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch Genre: eLearning | Language: English + subtitle | Duration: 21 Lectures ( 6h 48m ) | Size: 3.13 GB Oracle Cloud Tax Module-R13 What you'll learn Oracle Fusion Tax configuration-R13 Regime to Rate flow for Oracle Fusion Tax Module-R13 Detailed demonstration of real time Tax Scenario Requirements Knowledge of Oracle Fusion core finance is required Description This course is designed to provide a complete understanding on Oracle Fusion Tax Module.It explains and demonstrates all the components for Regime to rate flow as below.It is a step by step guide to create the complete Tax configuration by taking reference country as Germany Tax Regime.Students can take this as a blueprint to setup regime to rate tax flow and scenario for any other country .Tax RegimeTax CodeTax StatusTax JurisdictionTax ZoneTax RatesTax Determination FactorsTax ConditionTax Rules This training also explains the real time tax scenarios with examples and created the complete flow with results.So any Student new to Oracle Tax Module can take this session and at the end of this session can implement Oracle Fusion Tax module with lot of confidenceThe training covers the important checklist to consider while setting up the tax module.It explains how to analyse the client business requirement and configure the tax rule accordingly.It is one of the most comprehensive tax module training which can give clear understanding on Oracle Fusion Tax Concept Who this course is for Oracle Fusion Finance Consultants Oracle Fusion EBS Consultants Students who are preparing for a Job Opportunity in Oracle Cloud Technology Homepage https://www.udemy.com/course/oracle-fusion-end-to-end-tax-module-training/ Screenshot Rapidgator https://rg.to/file/4184cf49c486dec2dd28ca4b93d8b4a2/mhspm.Oracle.Fusion.End.to.End.Tax.Module.Training.sessions.part3.rar.html https://rg.to/file/512fbe57ff030b68c86b43e351f4b94c/mhspm.Oracle.Fusion.End.to.End.Tax.Module.Training.sessions.part2.rar.html https://rg.to/file/9f208816762182bc6046432f578f4adf/mhspm.Oracle.Fusion.End.to.End.Tax.Module.Training.sessions.part4.rar.html https://rg.to/file/f45e5650ab7d8b6f6a8361fc6987a87f/mhspm.Oracle.Fusion.End.to.End.Tax.Module.Training.sessions.part1.rar.html Fikper Free Download https://fikper.com/9qfAC5SBrb/mhspm.Oracle.Fusion.End.to.End.Tax.Module.Training.sessions.part1.rar.html https://fikper.com/TDt5mvMH8f/mhspm.Oracle.Fusion.End.to.End.Tax.Module.Training.sessions.part3.rar.html https://fikper.com/nEWFl0wuYp/mhspm.Oracle.Fusion.End.to.End.Tax.Module.Training.sessions.part2.rar.html https://fikper.com/xB2bxIjplU/mhspm.Oracle.Fusion.End.to.End.Tax.Module.Training.sessions.part4.rar.html No Password - Links are Interchangeable

Free Download Master Microsoft Fabric A Complete End-to-End Project- CICD Published 10/2024 Created by Shanmukh Sattiraju MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch Genre: eLearning | Language: English | Duration: 228 Lectures ( 21h 34m ) | Size: 7 GB Microsoft Fabric from Scratch includes Git, Lakehouse, Warehouse, Synapse Migration, end to end project with CICD- DP600 What you'll learn Understand and implement Microsoft Fabric Learn Data Engineering with Microsoft Fabric Implement Continuous Integration and Continuous Deployment in project Migrate Existing Synapse notebooks to Microsoft Fabric How access control and permissions works in Microsoft Fabric Enable Git and implement in Fabric project Understand OneLake and its features Implement Medallion Architecture with Microsoft Fabric Build an end to end CICD pipeline in Fabric Understand Fabric Lakehouse and its features Use Capacity Metrics App to monitor your items in Workspace Understand Fabric Warehouse and its features Handle different scenarios with Power BI in Fabric Row-level security , Column level security, object level security, Dynamic data masking in Warehouse Incremental loading to ingest data in all layers Update Microsoft Power BI from XMLA endpoint Different ways to refresh semantic models of Power BI Tenant level permissions, Capacity level permissions Workspace level sharing, Item level sharing of Fabric Items Row-level security , Column level security, object level security in Power BI Capacity metrics app different throttling stages Azure data factory vs Fabric data pipelines from On-premise data ingestion Different Medallion Architectural patterns to implement in Fabric Requirements Basic knowledge on Python and SQL Basic knowledge on Azure Cloud An Azure account to perform hands-on practicals No experience on Microsoft Fabric is needed, you will learn everything from scratch Description Unlock the full potential of Microsoft Fabric in this comprehensive course designed for data professionals at all levels. "Master Microsoft Fabric: A Complete End-to-End Project - CICD" takes you on an immersive journey through the core concepts and practical applications of Microsoft Fabric, enabling you to build and deploy advanced data solutions with confidence.The course begins with an in-depth exploration of foundational concepts such as Lakehouse, Warehouse, and OneLake, helping you understand the architecture and functionality of Microsoft Fabric. You'll learn how to leverage the Capacity Metrics App to monitor and manage your resources effectively, ensuring optimal performance for your data projects.As we delve deeper, you'll discover the seamless process of migrating Synapse notebooks to Fabric, gaining hands-on experience with its enhanced features. This migration will empower you to utilize existing resources while maximizing the benefits of the new environment.The course culminates in a capstone project that encompasses all the skills you've acquired. You'll implement a complete end-to-end data solution, focusing on building a robust Continuous Integration and Continuous Deployment (CICD) pipeline. This project not only solidifies your learning but also prepares you for real-world applications.By the end of this course, you will possess the expertise to navigate Microsoft Fabric and implement data solutions that meet today's challenges. Join us and elevate your data skills to the next level! 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Free Download Full Stack Creative Design For End To End Solutions Published 10/2024 MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz Language: English | Size: 669.72 MB | Duration: 15h 31m Master marketing mindset, content, graphic and UI design, video skills, digital media management What you'll learn Master the tools and techniques for creating designs across multimedia, web, video, and UI/UX. Develop strategic content for marketing with a focus on results and brand identity. Leverage AI tools to streamline workflows, enhance creativity, and produce professional-quality output. Build a portfolio that showcases end-to-end design solutions for freelancing, jobs, or business growth. Job and work focused teaching approach Requirements Access to a computer with internet connectivity Enthusiasm for learning creative design, content creation, and marketing No prior experience in design or marketing is needed, as the course will cover everything from fundamentals to advanced techniques. Description Welcome to Full Stack Creative Design: For End-to-End Solutions, a complete and immersive course that will transform you into a well-rounded creative professional. Whether you are just starting out or are looking to expand your skills, this course provides everything you need to become an expert in multiple aspects of design, content creation, and marketing.What makes this course unique is its focus on real-world applications and end-to-end solutions. You won't just learn how to create stunning designs-you'll discover how to market them, manage client projects, and build a thriving freelance or full-time career. This course will guide you through developing an impressive portfolio, understanding pricing strategies, and using AI to enhance your workflows. Most importantly it focuses on the monetization aspects - how to exactly earn with these skills and grow in your career. Key Learning Points:Master multimedia design across graphics, web, video, and digital media management.Develop marketing mindset to help position your creative work for business success.Leverage AI tools to automate tasks, enhance creativity, and improve efficiency.Build a portfolio to attract clients, secure job offers, or grow your own business.If you're looking to become a complete creative professional-capable of handling every aspect of design and content creation-this course is for you! Join now and start your journey toward mastering the full spectrum of creative design and digital marketing. Overview Section 1: Introduction Lecture 1 Introduction Lecture 2 Let's get started Section 2: How to make the most of this program? Lecture 3 How to make the most of this program? Lecture 4 Mindset and approach Section 3: Communication Lecture 5 Communication essentials Lecture 6 Why and how communication skills are critical for the success of a designer Lecture 7 Spoken communication skills Lecture 8 Written communication skills Lecture 9 Tips to improve communications skills Lecture 10 Tips for Learning English communication skills for beginners Lecture 11 Why understanding marketing and business is important for a designer? Section 4: Design process Lecture 12 Design process Section 5: Understanding multimedia project requirements Lecture 13 Process of Understanding Project Requirements Section 6: Ideation and design thinking Lecture 14 Design Thinking and Creative Problem-Solving Lecture 15 Design principles and theory Section 7: Ideation and sketching skills Lecture 16 Ideation process Lecture 17 Getting started with sketching skills Section 8: Smart Project Planning Lecture 18 Smart Project Planning Section 9: Choice of tools Lecture 19 Choice of tools Section 10: Pricing strategy Lecture 20 Pricing strategy Section 11: Content process Lecture 21 Research Lecture 22 Easy content / copy writing Lecture 23 AI tools for content Lecture 24 Why having content skills is critical for a designer? Section 12: Graphic designing Lecture 25 Graphic designing Lecture 26 Building artistic skills Lecture 27 Don't like sketching or don't want to sketch? Don't worry! Lecture 28 Tools for graphic designing Lecture 29 Sectors of graphic design Lecture 30 You need to learn to use these tools Lecture 31 There are 2 types Section 13: Canva Lecture 32 Getting started with Canva Lecture 33 Let's start with the interface Lecture 34 Step-by-step process for creating designs in Canva Lecture 35 Difference between Canva Free and Canva Pro Lecture 36 Formatting text in Canva Lecture 37 Images and graphics in Canva Lecture 38 Creating consistent designs with brand kits Lecture 39 Enhancing Designs in Canva Lecture 40 Designing for Social Media in Canva Lecture 41 Collaborating and Sharing in Canva Lecture 42 Advanced Tips and Tricks in Canva Lecture 43 Earning with Canva design skills Section 14: Adobe Photoshop Lecture 44 Getting started with Adobe Photoshop Lecture 45 Photoshop Installation Lecture 46 Overview of Photoshop interface and workspace Lecture 47 Understanding Photoshop tools and their functions Lecture 48 Exploring the Layers panel Lecture 49 Selection tools and techniques Lecture 50 Refining selections with feathering and masking Lecture 51 Working with layer masks and adjustment layers Lecture 52 Basic photo retouching techniques Lecture 53 Adjusting brightness, contrast, and levels Lecture 54 Content-Aware Fill and healing tools Lecture 55 Dodge and Burn techniques Lecture 56 Using filters and Smart Filters for creative effects Lecture 57 Creating and formatting text layers Lecture 58 Applying layer styles and effects to text Lecture 59 Designing typographic compositions and posters Lecture 60 Image Compositing and Collage Lecture 61 Cutting out and extracting objects from images Lecture 62 Combining multiple images using layers and blending modes Lecture 63 Creating seamless and realistic composites Lecture 64 Introduction to Photo Manipulation Lecture 65 Adding and removing objects in images Lecture 66 Creating surreal and fantasy scenes Lecture 67 Advanced Retouching and Portrait Editing Lecture 68 High-end skin retouching techniques Lecture 69 Teeth whitening and eye enhancements Lecture 70 Portrait lighting and color grading Lecture 71 Working with Smart Objects and Advanced Layers Lecture 72 Non-destructive editing with Smart Objects Lecture 73 Using advanced layer blending modes and opacity adjustments Lecture 74 Mastering essential editing techniques - Part 1 Lecture 75 Mastering essential editing techniques - Part 2 Lecture 76 Mastering essential editing techniques - Part 3 Lecture 77 Mastering essential editing techniques - Part 4 Lecture 78 Mastering essential editing techniques - Part 5 Lecture 79 Image Formats Lecture 80 Projects and Portfolio Development Lecture 81 Tips for building a strong Photoshop portfolio Section 15: Adobe Illustrator Lecture 82 Getting started with Adobe Illustrator Lecture 83 Understanding vector graphics and their advantages Lecture 84 Navigating the workspace and customizing preferences Lecture 85 Using essential tools: Selection Tool, Direct Selection Tool, Pen Tool Lecture 86 Working with shapes: Rectangle, Ellipse, Polygon, and Line Tools Lecture 87 Applying fills and strokes to shapes Lecture 88 Using the Pathfinder panel for shape operations Lecture 89 Working with the Shape Builder Tool Lecture 90 Understanding anchor points and bezier curves Lecture 91 Mastering the Pen Tool for creating precise paths Lecture 92 Editing paths using anchor point manipulation techniques Lecture 93 Creating and editing custom shapes with the Shape Builder Tool Lecture 94 Understanding layers and their importance in organizing artwork Lecture 95 Working with the Layers panel: creating, renaming, reordering, and locking layer Lecture 96 Utilizing layer opacity and blend modes Lecture 97 Using the Appearance panel to apply multiple fills and strokes Lecture 98 Working with Text and Typography Lecture 99 Applying text styles and effects Lecture 100 Converting text to outlines and manipulating it as shapes Lecture 101 Working with type on a path Lecture 102 Applying color and gradients: using the Color panel, Swatches, & Gradient panel Lecture 103 Creating and saving custom color swatches Lecture 104 Applying and editing gradients and gradient meshes Lecture 105 Working with the Recolor Artwork feature Lecture 106 Exploring advanced techniques: blending shapes and colors Lecture 107 Creating and editing custom brushes: artistic brushes, scatter & pattern brushes Lecture 108 Using the Appearance panel for complex effects and transformations Lecture 109 Exporting and saving artwork for different formats and purposes Lecture 110 Understanding file formats: svg, eps, pdf, and more Lecture 111 Preparing artwork for print or web Lecture 112 Tips for efficient workflow, productivity: shortcuts, libraries, templates Section 16: Getting started with Web and User Interface (UI) Design Lecture 113 Getting started with Web and User Interface (UI) Design Lecture 114 Tools for UI designing Lecture 115 Difference between UI design and UX design Section 17: Adobe XD Lecture 116 Overview of the user interface and workspace Lecture 117 Setting up artboards and using grids Lecture 118 Creating and manipulating basic shapes Lecture 119 Understanding typography and using text tools Lecture 120 Creating and customizing buttons, icons, and other UI elements Lecture 121 Using the Repeat Grid feature for efficient design Lecture 122 Introduction to wireframing and its importance in the design process Lecture 123 Building wireframes using XD's tools and components Lecture 124 Creating interactive prototypes with transitions and gestures Lecture 125 Previewing and sharing prototypes for feedback Lecture 126 Understanding responsive design principles Lecture 127 Creating responsive layouts with artboards and responsive resize Lecture 128 Using XD's responsive design features to adapt content for different screen size Lecture 129 Previewing and testing responsive designs Lecture 130 Collaborative design workflows using XD's co-editing and sharing features. Lecture 131 Collaborative Design and Design Systems Lecture 132 Introduction to design systems and their benefits Lecture 133 Using components and character styles for consistent designs Lecture 134 Introduction to user testing and its role in improving UX Lecture 135 Planning and conducting user tests on XD prototypes Lecture 136 Collecting and analyzing feedback from user tests Lecture 137 Iterating and refining designs based on user feedback Lecture 138 Designing micro-interactions to enhance user experience Lecture 139 Exploring XD's animation and timing features Lecture 140 Designing animated transitions between screens Lecture 141 Overview of exporting assets from XD for development Lecture 142 Generating design specs for developers using XD's design handoff feature Lecture 143 Exporting assets in different file formats for various platforms Lecture 144 Reviewing design handoff and collaboration tools compatible with XD Section 18: Figma Lecture 145 Getting started with Figma Lecture 146 Overview of Figma's features and benefits Lecture 147 Creating a Figma account and navigating the interface Lecture 148 Understanding the canvas, layers panel, properties panel, and toolbar Lecture 149 Exploring the essential design tools in Figma's toolbar Lecture 150 Creating and manipulating basic shapes Lecture 151 Working with colors, gradients, and shadows Lecture 152 Introduction to components and styles for design consistency Lecture 153 Understanding layers and layer management techniques Lecture 154 Grouping, renaming, and rearranging layers Lecture 155 Collaborating with team members in real-time Lecture 156 Leaving comments and feedback on designs Lecture 157 Introduction to Figma's prototyping capabilities Lecture 158 Linking screens and creating interactive flows Lecture 159 Previewing and sharing prototypes with others Lecture 160 Working with plugins to extend functionality Lecture 161 Exploring advanced features and shortcuts in Figma Lecture 162 Utilizing design libraries and design systems Lecture 163 Tips for optimizing workflow and productivity in Figma Section 19: Video making Lecture 164 Video making Lecture 165 There are 2 categories Section 20: Canva video Lecture 166 Getting started with Canva Video Lecture 167 Getting started with Canva Video Lecture 168 Customizing Video Templates Lecture 169 Adding Animations and Effects Lecture 170 Incorporating Music and Audio Lecture 171 Advanced Editing Techniques Lecture 172 Pro tips on Creating videos from scratch Lecture 173 Using record yourself feature Lecture 174 Exporting and Sharing Videos in Canva Section 21: Adobe Aftereffects Lecture 175 Overview of After Effects and its capabilities Lecture 176 Exploring the user interface and workspace in after effects Lecture 177 Understanding the basic terminology (composition, layer, keyframes, etc.) Lecture 178 Creating a new composition in after effects Lecture 179 Importing and organizing media files in after effects Lecture 180 Adding, manipulating, and animating layers in After effects Lecture 181 Creating basic animations (position, scale, rotation, opacity) in After effects Lecture 182 Working with the Graph Editor for easing and interpolation in After effects Lecture 183 Using parenting and expressions for advanced animations in After effects Lecture 184 Applying and customizing visual effects in After effects Lecture 185 Working with adjustment layers and masks in After effects Lecture 186 Exploring the Effects & Presets panel in After effects Lecture 187 Creating and saving custom presets Lecture 188 Adding and formatting text layers in After effects Lecture 189 Creating text transitions and kinetic typography Lecture 190 Working with text animators and presets in After effects Lecture 191 Introduction to motion tracking concepts in After effects Lecture 192 Tracking footage using built-in trackers in After effects Lecture 193 Applying tracked data to layers in After effects Lecture 194 Stabilizing shaky footage in After effects Lecture 195 Layer blending modes and transparency in After effects Lecture 196 Green screen keying and chroma keying in After effects Lecture 197 Creating and animating masks in After effects Lecture 198 Composite multiple elements together in After effects Lecture 199 Working with lights and shadows in After effects Lecture 200 Exporting in After effects Section 22: Vyond Lecture 201 Introduction to Vyond as an online platform for creating animated videos Lecture 202 Overview of the features and capabilities of Vyond Lecture 203 Importance and benefits of using animation in storytelling and communication Lecture 204 Vyond Studio interface Lecture 205 Navigating the timeline, character library, scene library, & other key elements Lecture 206 Character customization options in Vyond Lecture 207 How to change facial expressions, clothing, and other character attributes Lecture 208 Exploring the scene and prop libraries in Vyond Lecture 209 Demonstrate how to choose and modify pre-designed scenes and props in Vyond Lecture 210 Importing own images and backgrounds for more customization in Vyond Lecture 211 Basics of animation in Vyond Lecture 212 Adding movements, gestures, and actions to characters in Vyond Lecture 213 Camera angles, transitions, and effects to enhance the visual storytelling Lecture 214 Importance of audio in videos and different approaches to adding it in Vyond Lecture 215 Adding text-based dialogue and choose text-to-speech voices Lecture 216 Exploring advanced animation techniques in Vyond Lecture 217 Creating complex character interactions and choreographed movements Lecture 218 Lip-syncing and synchronized actions in Vyond Lecture 219 Significance of timing and transitions in creating smooth and engaging videos Lecture 220 Refining the timing of animations and transitions between scenes in Vyond Lecture 221 Using the timeline effectively for precise control in Vyond Lecture 222 Audio and visual effects available in Vyond Lecture 223 Adding background music, sound effects, and visual effects to enhance the video Lecture 224 Using effects judiciously to maintain a cohesive narrative in Vyond Lecture 225 Different publishing options in Vyond Lecture 226 Exporting videos in various formats in Vyond Lecture 227 Strategies for sharing videos on social media platforms & embedding them on web Section 23: Adobe Premiere Lecture 228 Understanding the interface and workspace of Adobe Premiere Lecture 229 Importing and organizing media files Lecture 230 Creating a new project and setting up project settings Lecture 231 Basic editing tools and techniques Lecture 232 Timeline navigation and basic video trimming Lecture 233 Advanced editing tools: Ripple, Roll, Slip, Slide, and Trim Lecture 234 Using the razor tool for precise editing Lecture 235 Applying transitions between clips Lecture 236 Creating and editing titles and text overlays Lecture 237 Importing and managing audio files Lecture 238 Adjusting audio levels and using keyframes Lecture 239 Applying audio effects and filters Lecture 240 Working with music and voiceovers Lecture 241 Syncing audio and video tracks Lecture 242 Applying video effects and filters Lecture 243 Working with video transitions and keyframes Lecture 244 Applying color correction and grading Lecture 245 Using adjustment layers for global effects Lecture 246 Introduction to green screen technology and its applications Lecture 247 Techniques for shooting with a green screen Lecture 248 Fine-tuning the key using matte controls and spill suppression Lecture 249 Working with foreground and background elements Lecture 250 Creating and animating text and shapes Lecture 251 Creating and animating Working with layers and blending modes Lecture 252 Keyframing motion and creating animations Lecture 253 Using templates and presets for efficiency Lecture 254 Working with multicamera editing Lecture 255 Using the Warp Stabilizer for image stabilization Lecture 256 Applying advanced audio effects and noise reduction Lecture 257 Understanding different video formats and settings Section 24: Social media essentials Lecture 258 Understanding Social Media Platforms and Their Audiences Lecture 259 Researching Trends and Audience Preferences Lecture 260 Planning and Building a Social Media Calendar Lecture 261 Designing posts Lecture 262 Publishing and Scheduling Content Lecture 263 Using AI Tools for Content Creation and Management Lecture 264 Building Organic Reach and Engagement Lecture 265 Measuring Success and Refining Your Strategy Section 25: Web designing essentials Lecture 266 Getting started with web designing Lecture 267 Domain registration Lecture 268 Hosting Lecture 269 Using website builders Section 26: Zoho Lecture 270 Introduction to Zoho Sites as a website Lecture 271 Exploring the interface and key features of Zoho Sites Lecture 272 Creating a basic website using Zoho Sites' drag-and-drop editor Lecture 273 Customizing templates, adding pages, and managing site navigation Lecture 274 Exploring Zoho Sites' advanced customization options Lecture 275 Working with sections, columns, and widgets Lecture 276 Customizing the site's design, including colors, fonts, and backgrounds Lecture 277 Adding multimedia elements like images, videos, and audio in zoho sites Lecture 278 Introduction to e-commerce and online store management Lecture 279 Difference between zoho sites and zoho commerce Lecture 280 Overview of Zoho Commerce as an e-commerce platform Lecture 281 Setting up a Zoho Commerce store and configuring basic settings Lecture 282 Managing products, categories, and inventory in Zoho Commerce Lecture 283 Customizing the design of Zoho Commerce stores using themes and templates Lecture 284 Modifying the layout and structure of the store's pages Lecture 285 Integrating branding elements and creating a consistent look and feel Lecture 286 Optimizing the user experience and navigation within the online store Lecture 287 Utilizing Zoho Commerce's built-in SEO features Lecture 288 Understanding order management and fulfillment in Zoho Commerce Lecture 289 Setting up payment gateways and configuring secure payment options Lecture 290 Managing shipping methods, rates, and fulfillment options Lecture 291 Handling order processing, tracking, and customer communication Lecture 292 Exploring Zoho Commerce's reporting and analytics features Lecture 293 Developing a marketing strategy for Zoho Commerce stores Lecture 294 Utilizing Zoho Commerce's marketing tools, including discounts and coupons Lecture 295 Integrating email marketing and social media to promote the online store Lecture 296 Exploring additional marketing and growth strategies for e-commerce businesses Lecture 297 Website and store maintenance best practices Lecture 298 Regularly updating and optimizing content on Zoho Sites Lecture 299 Exploring additional integrations and advanced features Section 27: Wix Lecture 300 Introduction to Wix as a website building platform Lecture 301 Exploring the Wix interface and its key features Lecture 302 Understanding the different Wix plans and pricing options Lecture 303 Creating a Wix account and setting up a new website Lecture 304 Navigating the Wix dashboard and website editor Lecture 305 Choosing a template for the website and understanding template customization Lecture 306 Understanding the structure of Wix websites, including pages and menus Lecture 307 Adding, modifying, and organizing pages on the website Lecture 308 Managing site settings, including domain connection and mobile optimization Lecture 309 Exploring Wix's design customization options Lecture 310 Editing website elements using the Wix editor tools Lecture 311 Creating visually appealing layouts using grids, sections, and columns in wix Lecture 312 Understanding the range of Wix apps and features available Lecture 313 Incorporating interactive features such as forms, maps, and social media Lecture 314 Adding and customizing a blog section on the website in wix Lecture 315 Integrating e-commerce functionality and creating an online store Lecture 316 Exploring Wix's SEO tools to improve website visibility Lecture 317 Exploring advanced features in Wix, such as Corvid (Wix Code) Lecture 318 Customizing and extending website functionality using Corvid in wix Lecture 319 Implementing dynamic pages and databases in Wix Lecture 320 Adding advanced features like member areas and bookings in wix Lecture 321 Utilizing Wix's analytics and insights for website performance tracking Lecture 322 Collaborating on a Wix website with team Lecture 323 Previewing, saving, and publishing changes to the live website on wix Lecture 324 Configuring SEO settings for improved search engine visibility on wix Lecture 325 Strategies for maintaining and updating the website over time on wix Lecture 326 Understanding the importance of responsive design for mobile devices on wix Lecture 327 Optimizing the website's layout and design for mobile screens on wix Lecture 328 Previewing and testing the mobile version of the website on wix Lecture 329 Exploring Wix's mobile editor and customization options Lecture 330 Ensuring a seamless user experience across different devices on wix Section 28: Marketing essentials Lecture 331 Introduction to Marketing Lecture 332 Understanding Your Target Audience Lecture 333 Branding and Positioning Lecture 334 Content Marketing Lecture 335 Social Media Marketing Lecture 336 Email Marketing Lecture 337 Paid Advertising (PPC and Display Ads) Lecture 338 Influencer and Affiliate Marketing Lecture 339 Marketing Analytics and KPIs Lecture 340 Scaling Your Marketing Strategy for Growth Section 29: AI tools Lecture 341 Introduction to AI in Design and Creative Industries Lecture 342 AI Tools for Graphic Design Lecture 343 AI Tools for Video Creation and Editing Lecture 344 AI-Powered Content Creation Lecture 345 AI in Social Media Management Lecture 346 Ethics and Future of AI in Design and Content Lecture 347 Conclusion and Resources Section 30: Useful resources Lecture 348 Top free stock libraries Lecture 349 Top free vector libraries Lecture 350 Top free font libraries Lecture 351 Libraries useful for a graphic designer Lecture 352 Libraries useful for a video maker Lecture 353 Libraries useful for a social media professional Section 31: Real time case studies Lecture 354 Reference Section 32: Internship road map and Portfolio Building Lecture 355 Internship road map and Portfolio Building Lecture 356 Guide on getting internship in best companies Section 33: Job search, freelancing and business scaling Lecture 357 Guide on getting the best job offers Lecture 358 Guide on a flourishing freelancing career Lecture 359 Guide on leveraging multimedia skills for scaling business Section 34: Ready to use materials Lecture 360 Intro Lecture 361 Here are your designs Lecture 362 Here is how to design and customize Lecture 363 How to use pro features Section 35: Conclusion Lecture 364 Conclusion Lecture 365 What next? Aspiring Designers: Individuals looking to learn end-to-end design skills, including graphic, UI/UX, web, and video design.,Freelancers & Entrepreneurs: Those wanting to offer creative solutions to clients or enhance their own business with professional content creation.,Marketing Professionals: People looking to integrate design skills with marketing strategies for better brand positioning and audience engagement.,Beginners & Career Changers: No prior experience needed-ideal for those starting from scratch or transitioning into creative fields.,Students: Learners seeking to build a strong design portfolio with practical projects and tools. Homepage https://www.udemy.com/course/become-a-full-stack-creative-designer-for-end-to-end-solutions/ Rapidgator https://rg.to/file/82d878032165e8bd2f6a0117e63a909a/rrxqy.Full.Stack.Creative.Design..For.End.To.End.Solutions.rar.html Fikper Free Download https://fikper.com/h9mdx2RSBN/rrxqy.Full.Stack.Creative.Design..For.End.To.End.Solutions.rar.html No Password - Links are Interchangeable

Free Download Front-End Web Development Learn HTML5 & CSS3 Last updated 1/2024 MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz Language: English | Size: 2.21 GB | Duration: 3h 29m HTML and CSS for beginners: learn how to build websites from scratch including responsive design and SEO What you'll learn Learn how to build web pages Front-end web development HTML5 CSS5 Requirements This course is for beginners with no experience in HTML and CSS No prior knowledge required Description Do you want to learn HTML and CSS from the beginning? Do you want to build modern, responsive websites or start a career in web development? If so, this is the course for you.We will start with the basics of how HTML works and how you write a web page. We will look at theory and practice while you code along with me to get some hands-on experience.We will explore topics such as responsive design, search engine optimisation and the tools that professional web developers use to get the job done.Here is what you will learn:Software tools for creating websitesWhat is HTML and how does it work?HTML tags and best practiceBuilding websites with HTMLWhat is CSS and how does it work?Styling websites with CSSIntroduction to Search Engine Optimisation (SEO)Tools for testing websitesDeep dive on CSS gridOur new deep-dive on CSS grid will teach you how to use the advanced feature's of grid's layout engine to build flexible, responsive and modern layouts using CSS to take advantage of the latest standards. This section includes an overview of grid, teaches you all of the features and includes real-world projects to test your new skills out.By the end of the course, you will have everything you need to build websites in HTML and CSS. Overview Section 1: Introduction Lecture 1 Welcome Lecture 2 Course goals Lecture 3 Course outline Section 2: Setup Lecture 4 Selecting your editor Lecture 5 Best editors for Windows Lecture 6 Best editors for Mac Lecture 7 Browser development tools Lecture 8 Sample code Section 3: HTML foundations Lecture 9 Introduction to HTML Lecture 10 What is HTML? Lecture 11 Anatomy of a page Lecture 12 Semantic tags Lecture 13 Common tags Lecture 14 Layout tags Lecture 15 List of tags Lecture 16 Working with text Lecture 17 Working with images Lecture 18 Image formats Lecture 19 Working with forms Lecture 20 HTML coding challenge Lecture 21 HTML challenge solution Section 4: HTML features Lecture 22 Module introduction Lecture 23 Anchor tags Lecture 24 In-page links Lecture 25 Tables Lecture 26 File uploads Lecture 27 Video Lecture 28 Audio Lecture 29 Preloading media Section 5: CSS foundations Lecture 30 Introduction to CSS Lecture 31 What is CSS? Lecture 32 Creating a stylesheet Lecture 33 Adding styles Lecture 34 Selectors Lecture 35 Types of selectors Lecture 36 Editing CSS live Lecture 37 Properties Lecture 38 Sizing boxes Lecture 39 List of properties Lecture 40 Display property Lecture 41 Designing layouts Lecture 42 Flexbox in detail Lecture 43 Media queries Lecture 44 CSS coding project Lecture 45 CSS project example Section 6: CSS features Lecture 46 Module introduction Lecture 47 Background images Lecture 48 Gradients Lecture 49 Overflow Lecture 50 Pseudo-elements Lecture 51 Transitions Lecture 52 Variables Section 7: Search Engine Optimisation (SEO) Lecture 53 Introduction to SEO Lecture 54 What is SEO? Lecture 55 Modern SEO Lecture 56 Page structure Lecture 57 Meta tags Lecture 58 Robots.txt Section 8: Tools Lecture 59 Introduction to tools Lecture 60 Can I Use Lecture 61 Lighthouse Lecture 62 W3C Validator Lecture 63 Colour tools Section 9: CSS Grid Lecture 64 Introduction to CSS Grid Lecture 65 What is grid? Lecture 66 Browser support Lecture 67 Download the example code Section 10: CSS Grid: Fundamentals Lecture 68 Templates Lecture 69 Repeats Lecture 70 Gaps Lecture 71 Units of measurement Lecture 72 Alignment and justification Lecture 73 Implicit tracks Lecture 74 Positioning items Lecture 75 Areas Lecture 76 Minmax Lecture 77 Autofill Section 11: CSS Grid: Projects Lecture 78 Introduction to projects Lecture 79 Two-column layout Lecture 80 Article blog Lecture 81 Photo blog Lecture 82 Article with breakout Section 12: Conclusion Lecture 83 What's next? Lecture 84 Conclusion Lecture 85 Bonus lecture Anyone looking to learn HTML and CSS,Anyone looking to code their own website Homepage https://www.udemy.com/course/front-end-web-development-html-css/ Rapidgator https://rg.to/file/05e4e97184ab7cc6f7719bc0cb52f93b/xguzt.FrontEnd.Web.Development.Learn.HTML5..CSS3.part3.rar.html https://rg.to/file/c991b7e9f58480f9e5c4d50416f049ad/xguzt.FrontEnd.Web.Development.Learn.HTML5..CSS3.part2.rar.html https://rg.to/file/ef966bd4d5e1b74a8e9f1a2c512d646e/xguzt.FrontEnd.Web.Development.Learn.HTML5..CSS3.part1.rar.html Fikper Free Download https://fikper.com/8x6t1bDJTZ/xguzt.FrontEnd.Web.Development.Learn.HTML5..CSS3.part3.rar.html https://fikper.com/bxkHHWgcKw/xguzt.FrontEnd.Web.Development.Learn.HTML5..CSS3.part2.rar.html https://fikper.com/yZsG4j0Yd8/xguzt.FrontEnd.Web.Development.Learn.HTML5..CSS3.part1.rar.html No Password - Links are Interchangeable

Free Download Complete Mlops Bootcamp With 10+ End To End Ml Projects Published 10/2024 MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz Language: English | Size: 50.09 GB | Duration: 47h 39m End-to-End MLOps Bootcamp: Build, Deploy, and Automate ML with Data Science Projects What you'll learn Build scalable MLOps pipelines with Git, Docker, and CI/CD integration. Implement MLFlow and DVC for model versioning and experiment tracking. Deploy end-to-end ML models with AWS SageMaker and Huggingface. Automate ETL pipelines and ML workflows using Apache Airflow and Astro. Monitor ML systems using Grafana and PostgreSQL for real-time insights. Requirements Basic understanding of Python programming. Familiarity with machine learning concepts and algorithms. Basic knowledge of Git and GitHub for version control. Understanding of Docker for containerization (optional but helpful). Awareness of cloud computing concepts (AWS preferred, but not mandatory). Description Welcome to the Complete MLOps Bootcamp With End to End Data Science Project, your one-stop guide to mastering MLOps from scratch! This course is designed to equip you with the skills and knowledge necessary to implement and automate the deployment, monitoring, and scaling of machine learning models using the latest MLOps tools and frameworks.In today's world, simply building machine learning models is not enough. To succeed as a data scientist, machine learning engineer, or DevOps professional, you need to understand how to take your models from development to production while ensuring scalability, reliability, and continuous monitoring. This is where MLOps (Machine Learning Operations) comes into play, combining the best practices of DevOps and ML model lifecycle management.This bootcamp will not only introduce you to the concepts of MLOps but will take you through real-world, hands-on data science projects. By the end of the course, you will be able to confidently build, deploy, and manage machine learning pipelines in production environments.What You'll Learn:Python Prerequisites: Brush up on essential Python programming skills needed for building data science and MLOps pipelines.Version Control with Git & GitHub: Understand how to manage code and collaborate on machine learning projects using Git and GitHub.Docker & Containerization: Learn the fundamentals of Docker and how to containerize your ML models for easy and scalable deployment.MLflow for Experiment Tracking: Master the use of MLFlow to track experiments, manage models, and seamlessly integrate with AWS Cloud for model management and deployment.DVC for Data Versioning: Learn Data Version Control (DVC) to manage datasets, models, and versioning efficiently, ensuring reproducibility in your ML pipelines.DagsHub for Collaborative MLOps: Utilize DagsHub for integrated tracking of your code, data, and ML experiments using Git and DVC.Apache Airflow with Astro: Automate and orchestrate your ML workflows using Airflow with Astronomer, ensuring your pipelines run seamlessly.CI/CD Pipeline with GitHub Actions: Implement a continuous integration/continuous deployment (CI/CD) pipeline to automate testing, model deployment, and updates.ETL Pipeline Implementation: Build and deploy complete ETL (Extract, Transform, Load) pipelines using Apache Airflow, integrating data sources for machine learning models.End-to-End Machine Learning Project: Walk through a full ML project from data collection to deployment, ensuring you understand how to apply MLOps in practice.End-to-End NLP Project with Huggingface: Work on a real-world NLP project, learning how to deploy and monitor transformer models using Huggingface tools.AWS SageMaker for ML Deployment: Learn how to deploy, scale, and monitor your models on AWS SageMaker, integrating seamlessly with other AWS services.Gen AI with AWS Cloud: Explore Generative AI techniques and learn how to deploy these models using AWS cloud infrastructure.Monitoring with Grafana & PostgreSQL: Monitor the performance of your models and pipelines using Grafana dashboards connected to PostgreSQL for real-time insights.Who is this Course For?Data Scientists and Machine Learning Engineers aiming to scale their ML models and automate deployments.DevOps professionals looking to integrate machine learning pipelines into production environments.Software Engineers transitioning into the MLOps domain.IT professionals interested in end-to-end deployment of machine learning models with real-world data science projects.Why Enroll?By enrolling in this course, you will gain hands-on experience with cutting-edge tools and techniques used in the industry today. Whether you're a data science professional or a beginner looking to expand your skill set, this course will guide you through real-world projects, ensuring you gain the practical knowledge needed to implement MLOps workflows successfully.Enroll now and take your data science skills to the next level with MLOps! Overview Section 1: Introduction Lecture 1 Introduction Section 2: IDE's And Code Editors You Can Use Lecture 2 Getting Started With Google Colab Lecture 3 Getting Started With Github Codespace Lecture 4 Anaconda And VS Code Installation Section 3: Python Prerequisites Lecture 5 Getting Started With VS Code And Environment Lecture 6 Python Basics-Syntax and Semantics Lecture 7 Variables In Python Lecture 8 Basics Data Types Lecture 9 Operators In Python Lecture 10 Conditional Statements In Python Lecture 11 Loops In Python Lecture 12 Practical Examples Of List Lecture 13 Sets In Python Lecture 14 Tuples In Python Lecture 15 Dictionaries In Python Lecture 16 Functions In Python Lecture 17 Python Function Examples Lecture 18 Lambda Functions In Python Lecture 19 Map functions In Python Lecture 20 Python Filter Function Lecture 21 Import Modules And Packages In Python Lecture 22 Standard Library Overview Lecture 23 File Operation In Python Lecture 24 Working With File Paths Lecture 25 Exception Handling In Python Lecture 26 OOPS In Python Lecture 27 Inheritance In Python Lecture 28 Polymorphism In Python Lecture 29 Encapsulation In Python Lecture 30 Abstraction In Python Lecture 31 Magic Methods In Python Lecture 32 Custom Exception In Python Lecture 33 Operator OverLoading In Python Lecture 34 Iterators In Python Lecture 35 Generators In Python Lecture 36 Decorators In Python Lecture 37 Working With Numpy In Python Lecture 38 Pandas DataFrame And Series Lecture 39 Data Manipulation And Analysis Lecture 40 Data Source Reading Lecture 41 Logging In Python Lecture 42 Logging With Multiple Loggers Lecture 43 Logging In a Real World Examples Section 4: Complete Flask Tutorial Lecture 44 Introduction To Flask Framework Lecture 45 Understanding A Sample Flask Application Lecture 46 Integrating HTML With Flask Framework Lecture 47 HTTP Verbs Get And Post Lecture 48 Building Dynamic Url With Jinja 2 Lecture 49 Put Delete And API's In Flask Section 5: Git and Github Lecture 50 Getting Started With Git And Github Lecture 51 Part 2- Git Merge,Push, Checkout And Log With Commands Lecture 52 Part 3- Resolving Git Branch Merge Conflict Section 6: Complete MLFLOW Tutorials Lecture 53 Introduction To MLFLOW Lecture 54 Getting Started With MLFLOW Lecture 55 Creating MLFLOW Environment Lecture 56 Getting Started With MLFLow Tracking Server Lecture 57 Deep Diving Into MLFlow Experiments Lecture 58 Getting Started With MLFlow ML Project Lecture 59 First ML Project With MLFLOW Lecture 60 Inferencing Model Artifacts With MLFlow Inferencing Lecture 61 MLFLOW Model Registry Tracking Section 7: ML Project Integration With MLFLOW Tracking Lecture 62 Data Preparation House Price Prediction Lecture 63 Model Building And MLFLOW Tracking Section 8: Deep Learning ANN Model Building Integration With MLFLOW Lecture 64 ANN With MLFLOW- Part 1 Lecture 65 ANN with MLFLOW-Part 2 Section 9: Getting Started With DVC- Data Version Control Lecture 66 Introduction To DVC With Practical Implementation Section 10: Getting Started With Dagshub Lecture 67 Introduction To Dagshub Remote Repository Lecture 68 Creating First Remote Repo Using Dagshub Lecture 69 DVC With Dagshub Remote Repository Section 11: End To End Machine Learning Pipeline Using GIT, DVC,MLFLOW And DAGSHUB Lecture 70 Getting Started With Project Structure Lecture 71 Implemeting Data Preprocessing Pipeline Lecture 72 Implementing Model Training Pipeline with MLFLOW Setup Lecture 73 MLFLOW Experiment Tracking In Dagshub Lecture 74 ML Evaluation Piepline With MLFLOW Lecture 75 Run The Complete Pipeline With DVC Stage And Repro Section 12: MLFLOW With AWS Cloud Lecture 76 Introduction To MLFLOW In AWS Lecture 77 MLFLOW Project Set Up With Installation Lecture 78 Implementing The End To End Project With MLFLOW Lecture 79 AWS Cloud EC2,IAM,S3 Bucket Set Up Lecture 80 AWS EC2 Instance- Setting MLFLOW Tracking Server Section 13: Complete Basic To Advance Dockers Lecture 81 Introduction To Docker Series Lecture 82 What are Dockers And Containers Lecture 83 Docker Images vs Containers Lecture 84 Dockers vs Virtual Machines Lecture 85 Dockers Installation Lecture 86 Creating A Docker Image Lecture 87 Docker Basic Commands Lecture 88 Push Docker Image To Docker Hub Lecture 89 Docker Compose Section 14: Getting Started With Airflow Lecture 90 Introduction To Apache Airflow Lecture 91 Key Components Of Apache Airflow Lecture 92 Why Airflow For MLOPS Lecture 93 Setting Up Airflow With Astro Lecture 94 Building Your First DAG With Airflow Lecture 95 Designing Mathematical Calculation DAG With Airflow Lecture 96 Getting Started With TaskFlow API Using Apache Airflow Section 15: Airflow ETL Pipeline with Postgres and API Integration In ASTRO Cloud And AWS Lecture 97 Introduction To ETL Pipeline Lecture 98 ETL Problem Statement And Project Structure Set Up Lecture 99 Defining ETL DAG With Implementing Steps Lecture 100 Step 1- Setting Up Postgres And Creating Table Task In Postgres Lecture 101 Step 2- NASA API Integration With Extract Pipeline Lecture 102 Step 3- Building Transformation And Load Pipeline Lecture 103 ETL Pipeline Final Implementation With AirFlow Connection Set Up Lecture 104 ETL Pipeline Deployment In Astro Cloud And AWS Section 16: Introduction To Github Actions Lecture 105 What is Github Action and CI CD Pipeline Lecture 106 What is Developers Workflow With Examples Lecture 107 Practicals-Automate Testing Workflow With Python Section 17: End To End Github Action Workflow Project With Dockerhub Lecture 108 Github Action Workflow Project with Docker hub Lecture 109 Setting Project Structure With Github Repo Lecture 110 Setting Up Github Repository Lecture 111 Implementing Project With Flask And Dockers Lecture 112 Building the Yaml file for Dockers Section 18: Getting Started With Your First End To End Data Science Project With Deployment Lecture 113 Project Structure, Github Repo And Environment Set Up Lecture 114 Custom Logging Implementation Lecture 115 Common Utilities Functions Implementation Lecture 116 Step By Step Building Data Ingestion Pipeline- Part 1 Lecture 117 Data Ingestion Pipeline-Part 2 Lecture 118 Complete Data Validation Pipeline Implementation Lecture 119 Complete Data Transformation Pipeline Implementation Lecture 120 Model Trainer Pipeline Implementation Lecture 121 Model Evaluation Pipeline Implementation Lecture 122 Training And Prediction Pipeline With Flask App Section 19: End To End MLOPS Projects With ETL Pipelines- Building Network Security System Lecture 123 Project Structure Set up With Environment Lecture 124 Github Repository Set Up With VS Code Lecture 125 Packaging the Project With Setup.py Lecture 126 Logging And Exception Handling Implementation Lecture 127 Introduction To ETL Pipelines Lecture 128 Setting Up MongoDb Atlas Lecture 129 ETL Pipeline Setup With Python Lecture 130 Data Ingestion Architecture Lecture 131 Implementing Data Ingestion Configuration Lecture 132 Implementing Data Ingestions Component Lecture 133 Implementing Data Validation-Part 1 Lecture 134 Implementing Data Validation- Part 2 Lecture 135 Data Transformation Architecture Lecture 136 Data Transformation Implementation Lecture 137 Model Trainer-Part 1 Lecture 138 Model Trainer And Evaluation With Hyperparameter Tuning Lecture 139 Model Experiment Tracker With MLFlow Lecture 140 MLFLOW Experiment Tracking With Remote Respository Dagshub Lecture 141 Model Pusher Implementation Lecture 142 Model Training Pipeline Implementation Lecture 143 Batch Prediction Pipeline Implementation Lecture 144 Final Model And Artifacts Pusher To AWS S3 buckets Lecture 145 Building Docker Image And Github Actions Lecture 146 Github Action-Docker Image Push to AWS ECR Repo Implementation Lecture 147 Final Deployment To EC2 instance Section 20: End To End DS Project Implementation With Mulitple AWS,Azure Deployment Lecture 148 Github And Code Setup Lecture 149 Project structure Logging And Exception Lecture 150 Project Problem Statement EDA And Model Training Lecture 151 Data Ingestion Implementation Lecture 152 Data Transformation Implementation Lecture 153 Model Trainer Implementation Lecture 154 Hyperparameter Tuning Implementation Lecture 155 Building Prediction Pipeline Lecture 156 Deployment AWS Beanstalk Lecture 157 Deployment In EC2 Instance Lecture 158 Deployment In Azure Web App Section 21: Build, Train ,Deploy And Create Endpoints For ML Project Using AWS Sagemaker Lecture 159 Introduction To AWS Sagemaker Amd Project Set up Lecture 160 EDA,AWS IAM, S3 Set up With Data Ingestion Lecture 161 Implementing Training Script For AWS Sagemaker Lecture 162 Training With An On Spot Instance In AWS Sagemaker Lecture 163 Deployment Of Endpoint With AWS Sagemaker And Inferencing Section 22: Grafana-Open Source Tool For Data Visualization And Monitoring Lecture 164 Introduction To Grafana Open Source Tool Lecture 165 Grafana Cloud Set Up And Problem Statement Lecture 166 Visualization Implementation With Grafana Cloud And Postgresql In AWS Section 23: Generative AI Series With AWS LLMOPS Lecture 167 LifeCycle Of Gen AI Projects In Cloud Lecture 168 Blog Generation Generative AI App Using AWS Lambda And Bedrock Lecture 169 Deployment Of HuggingFace LLM Model In AWS Sagemaker Lecture 170 End To End GENAI App Using NVIDIA NIM Data Scientists and Machine Learning Engineers looking to scale and deploy ML models.,DevOps professionals wanting to integrate ML pipelines.,Software Engineers interested in transitioning to MLOps.,Beginners with basic ML knowledge aiming to learn end-to-end deployment.,IT professionals eager to understand MLOps tools and practices for real-world projects. 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Free Download Udemy - Texturing High-End Fashion And Tactical Assets Published 10/2024 MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz Language: English | Size: 3.07 GB | Duration: 3h 23m Advanced Techniques for Texturing Bags, Boots, Caps, and Gloves with Substance Painter and Marmoset Toolbag 4 What you'll learn Master the process of texturing a leather Dior bag, including applying realistic leather materials, stitching, and worn details, then rendering it professionall Gain skills in creating realistic textures for tactical boots and navy caps, learning how to solve UV issues, curvature/thickness edge problems Learn how to use Substance Painter's newest version 9, including advanced baking techniques for complex models and the Same Mesh Name workflow Understand how to optimize your texturing workflow, create dynamic masks with anchor points, and produce high-quality renders in Marmoset Toolbag 4 to showcase Requirements Basic Understanding of 3D Modeling Concepts: While this course focuses on texturing, a basic knowledge of 3D modeling will help you follow along more easily. You will need both software tools installed on your computer to parti[beeep]te in the hands-on projects and complete the rendering processes. Your machine should meet the necessary system requirements to smoothly run Substance Painter and Marmoset Toolbag 4, ensuring a seamless learning experience. Whether you're a beginner or intermediate artist, enthusiasm for creating stunning, realistic textures and improving your skills is all you need to succeed. Description Welcome to Mastering Substance Painter: Texturing High-End Fashion and Tactical Assets, a complete, in-depth course designed to elevate your texturing skills in Substance Painter and professional rendering in Marmoset Toolbag 4. This course is perfect for 3D artists, game developers, and anyone passionate about creating high-quality textures for a wide range of 3D assets. Through four unique projects, you'll dive deep into the advanced techniques of texturing various fashion items and tactical gear.Each project showcases real-world assets like designer bags, navy caps, tactical boots, and gloves-helping you develop skills that are essential for creating both fashion-related assets and gear for games or visualization projects. This course will teach you not only how to texture but also how to streamline your workflow, troubleshoot common issues, and bring your models to life with exceptional detail and realism.Guided by an expert 3D artist with years of industry experience, this course breaks down each texturing challenge in Substance Painter, giving you the tools you need to overcome obstacles and master advanced techniques.What You Will Learn:1. Texturing a Dior Leather Bag in Substance PainterIn this first project, we will explore how to texture a high-end Dior leather bag in Substance Painter. 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Another key highlight is mastering the path tool, which allows for precise detailing with ease. Finally, we will tackle UV issues using wrap projection to ensure all areas of your model are perfectly textured.Key Concepts:Solving curvature/thickness edge issues.Creating dynamic masks with anchor points.Using the path tool for rapid detailing.Wrap projection for UV and texturing challenges.3. Tactical Boots Texturing in Substance PainterIn this tutorial, we will cover a tactical boots model that starts off untextured, and we'll transform it into a highly detailed 3D asset in minimal time. This project highlights the efficiency of Substance Painter's tools in creating tactical gear textures. You'll focus on speed without compromising quality, learning how to develop rugged, realistic textures that fit seamlessly into game or animation environments. Re-texturing is a skill every artist should master-similar to relighting scenes for lighting artists-and it's crucial for giving new life to old assets.Key Concepts:Fast, efficient re-texturing techniques.Creating rugged textures for tactical gear.Transforming untextured models quickly.4. Texturing Leather Gloves with Substance Painter's New Path ToolFinally, we will explore Substance Painter's newest version (9), featuring the Path Tool-a fantastic update that allows for incredible precision when adding details. We will texture a pair of leather gloves and incorporate the path tool to streamline the detailing process. Additionally, you'll learn a baking method (Same Mesh Name), which is ideal for complex models. This technique is widely applicable across many projects, saving you time and ensuring higher quality textures.Throughout the tutorial, we'll also be using Evgeniia Petrova's products, which are fantastic resources to enhance your textures. These can be adapted to any project you're working on.Key Concepts:Texturing leather gloves using the new path tool.Baking method for complex models (Same Mesh Name).Incorporating external resources for superior results. Overview Section 1: Dior Bag Lecture 1 01Dior Bag Substance Painter in English Lecture 2 02Dior BagSubstance Painter in English Section 2: Navy Cap Lecture 3 03NavyCap Section 3: Tactical Boots Lecture 4 04Tactical Boots Section 4: Texturing Gloves Lecture 5 05Texturing Gloves Those who are new to Substance Painter but eager to learn advanced texturing techniques and workflows for professional-quality 3D assets.,Artists looking to refine their skills and learn how to handle more complex texturing challenges, like detailed leather, tactical gear, and complex UV maps.,Professionals or hobbyists creating game-ready assets who need to enhance their texturing and rendering skills, producing realistic and efficient textures for game environments or characters.,Anyone in the creative industry who wants to improve their portfolio by mastering the texturing of high-end fashion items or tactical gear for product visualization or 3D art projects. 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Free Download End-to-End Real-World Data Engineering Project with Databricks Released 10/2024 MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch Skill Level: Intermediate | Genre: eLearning | Language: English + srt | Duration: 1h 40m | Size: 225 MB This comprehensive course offers a practical, hands-on approach to building a modern data pipeline using Databricks. Join instructor Deepak Goyal as he guides you through a real-world data engineering project that transforms a data lake into an efficient, analytics-ready solution using the Databricks ecosystem. Learn how an end-to-end project works in Databricks, how to implement the three-layer medallion architecture-bronze, silver, and gold-and how to use Spark SQL in a real-world data project. Ideal for professional data engineers as well as data analysts, this course can help you take your technical skills to the next level and put you in a more in-demand position to land the data role of your dreams. Homepage https://www.linkedin.com/learning/end-to-end-real-world-data-engineering-project-with-databricks TakeFile https://takefile.link/5kae702d84gu/pvirl.EndtoEnd.RealWorld.Data.Engineering.Project.with.Databricks.rar.html Rapidgator https://rg.to/file/f20ff1595449a6dbb29ffb69bb0d58ec/pvirl.EndtoEnd.RealWorld.Data.Engineering.Project.with.Databricks.rar.html Fikper Free Download https://fikper.com/BUCmgx90pF/pvirl.EndtoEnd.RealWorld.Data.Engineering.Project.with.Databricks.rar No Password - Links are Interchangeable

Free Download 19 Generative Ai Real Time Projects End To End Published 10/2024 MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz Language: English | Size: 5.45 GB | Duration: 6h 23m Master Generative AI with 20+ Real-World Projects: Build, Deploy & Scale End-to-End Solutions What you'll learn Develop practical skills in building and deploying generative AI applications using LLM models. Gain hands-on experience in training and fine-tuning LLM models using various datasets. Create diverse applications leveraging the power of these LLM models. End-to-end Projects Using LLM, VectorDB, Langchain, LlamaIndex, Flask, Streamlit, Chainlit and so on. Gain hands-on experience in LLMOps Master Google Vertex AI & AWS Bedrock for Generative AI Project Implementation Requirements Proficiency in Python Programming: Strong understanding of Python syntax and experience with data manipulation libraries (NumPy, Pandas). 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Overview Section 1: Projects Lecture 1 Text summarization with hugging face Lecture 2 Text to Image generation with LLM with hugging face Lecture 3 Text to speech generation with LLM with hugging face Lecture 4 Telegram bot using OpenAI Lecture 5 Finetuning of GPT-3 model for text classification Lecture 6 Audio Transcript Translation with Whishper Lecture 7 Image generation with DALL-E Lecture 8 Custom Website Chatbot Lecture 9 Custom Website Chatbot using Open source LLMs Lecture 10 Build a Q&A App with RAG using Gemini Pro and Langchain Lecture 11 Financial Stock Analysis using LlamaIndex Lecture 12 End to End Medical Chatbot Project with LLM, Pinecone, LangChain Lecture 13 End to End Source Code Analysis with LangChain, OpenAI and ChromaDB Lecture 14 Implementing Zomato chatbot with Chainlit Lecture 15 How to Deploy Generative AI Application as CICD on AWS Lecture 16 RAG on Vertex AI with Vector Search and Gemini Pro Lecture 17 LLM powered application on Vertex AI Lecture 18 Hands-on AWS Bedrock AI Enthusiasts & Beginners: Individuals looking to explore and build a solid foundation in Generative AI through practical projects.,Data Scientists & Machine Learning Engineers: Professionals wanting to expand their skillset by implementing advanced AI models.,Software Developers: Developers interested in transitioning to AI roles and building real-world AI applications.,Researchers & Academics: Those looking to apply Generative AI techniques in research or academic projects. 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Free Download Simplified Machine Learning End To End™ Published 9/2024 MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz Language: English | Size: 3.01 GB | Duration: 7h 15m With Case Study This comprehensive course offers an in-depth journey into Machine Learning and Data Science What you'll learn Introduction to Machine Learning:- Understand the basics and types of Machine Learning. ML Unsupervised Learning:- Learn the concepts and techniques of Unsupervised Learning. Supervised Learning - Regression:- Master regression models for predicting continuous outcomes. Evaluation Metrics for Regression Model:- Evaluate regression models using metrics like MSE, RMSE, and R-squared. Supervised Learning - Classification in Machine Learning:- Learn classification algorithms for categorical predictions. Supervised Learning - Decision Trees:- Understand how Decision Trees work for classification and regression. Unsupervised Learning - Clustering:- Explore clustering techniques to group data points. Unsupervised Learning - DBSCAN Clustering: Apply the DBSCAN algorithm for density-based clustering. Unsupervised Learning - Dimensionality Reduction:- Learn techniques to reduce data dimensions while retaining key information. Unsupervised Learning - Dimensionality Reduction with t-SNE:- Use t-SNE for visualizing high-dimensional data in a reduced form. Model Evaluation and Validation Techniques:- Understand model validation methods like cross-validation. Model Evaluation - Bias-Variance Tradeoffs:- Learn to balance bias and variance for improved model performance. Introduction to Python Libraries for Data Science:- Get familiar with key Python libraries such as NumPy, Pandas, and Scikit-learn. Introduction to Python Libraries for Data Science:- Explore advanced Python libraries used in data analysis and machine learning. Introduction to R Libraries for Data Science:- Learn essential R libraries for data manipulation and modeling. Introduction to R Libraries for Data Science Statistical Modeling:- Apply statistical modeling using R's powerful libraries. Requirements Basic Understanding of Mathematics Familiarity with linear algebra, probability, and statistics is helpful. Basic Analytical and Problem-Solving Skills Ability to think critically and solve complex problems. Anyone can learn this class it is very simple. Description This comprehensive course offers an in-depth journey into Machine Learning and Data Science, designed to equip students with the skills needed to build and evaluate models, interpret data, and solve real-world problems. The course covers both Supervised and Unsupervised Learning techniques, with a strong focus on practical applications using Python and R.Students will explore essential topics like Regression, Classification, Clustering, and Dimensionality Reduction, alongside key model evaluation techniques, including the Bias-Variance Tradeoff and cross-validation. The course also includes an introduction to powerful libraries such as NumPy, Pandas, Scikit-learn, and t-SNE, along with statistical modeling in R.Whether you're a beginner or looking to enhance your knowledge in Machine Learning, this course provides the foundation and advanced insights necessary to master data science tools and methods, making it suitable for aspiring data scientists, analysts, or AI enthusiasts.Introduction to Machine Learning:- Understand the basics and types of Machine Learning.ML Unsupervised Learning:- Learn the concepts and techniques of Unsupervised Learning.Supervised Learning - Regression:- Master regression models for predicting continuous outcomes.Evaluation Metrics for Regression Model:- Evaluate regression models using metrics like MSE, RMSE, and R-squared.Supervised Learning - Classification in Machine Learning:- Learn classification algorithms for categorical predictions.Supervised Learning - Decision Trees:- Understand how Decision Trees work for classification and regression.Unsupervised Learning - Clustering:- Explore clustering techniques to group data points.Unsupervised Learning - DBSCAN Clustering: Apply the DBSCAN algorithm for density-based clustering.Unsupervised Learning - Dimensionality Reduction:- Learn techniques to reduce data dimensions while retaining key information.Unsupervised Learning - Dimensionality Reduction with t-SNE:- Use t-SNE for visualizing high-dimensional data in a reduced form.Model Evaluation and Validation Techniques:- Understand model validation methods like cross-validation.Model Evaluation - Bias-Variance Tradeoffs:- Learn to balance bias and variance for improved model performance.Introduction to Python Libraries for Data Science:- Get familiar with key Python libraries such as NumPy, Pandas, and Scikit-learn.Introduction to Python Libraries for Data Science:- Explore advanced Python libraries used in data analysis and machine learning.Introduction to R Libraries for Data Science:- Learn essential R libraries for data manipulation and modeling.Introduction to R Libraries for Data Science Statistical Modeling:- Apply statistical modeling using R's powerful libraries.Courtesy,Dr. FAK Noble Ai Researcher, Scientists, Product Developer, Innovator & Pure Consciousness ExpertFounder of Noble Transformation Hub TM Overview Section 1: Introduction to Machine Learning Lecture 1 Introduction to Machine Learning Section 2: ML Unsupervised Learning Lecture 2 ML Unsupervised Learning Section 3: Supervised Learning- Regression Lecture 3 Supervised Learning- Regression Section 4: Evaluation Metrics for Regression Model Lecture 4 Evaluation Metrics for Regression Model Section 5: Supervised Learning- Classification in Machine Learning Lecture 5 Supervised Learning- Classification in Machine Learning Section 6: Supervised Learning- Decision Trees Lecture 6 Supervised Learning- Decision Trees Section 7: Unsupervised Learning- Clustering Lecture 7 Unsupervised Learning- Clustering Section 8: Unsupervised Learning DBSCAN Clustering Lecture 8 Unsupervised Learning DBSCAN Clustering Section 9: Unsupervised Learning- Dimensionality Reduction Lecture 9 Unsupervised Learning- Dimensionality Reduction Section 10: Unsupervised Learning- Dimensionality Reduction with t-SNE Lecture 10 Unsupervised Learning- Dimensionality Reduction with t-SNE Section 11: Model Evaluation and Validation Techniques Lecture 11 Model Evaluation and Validation Techniques Section 12: Model Evaluation- Bias-Variance Tradeoffs Lecture 12 Model Evaluation- Bias-Variance Tradeoffs Section 13: Introduction to Python Libraries for Data Science Lecture 13 Introduction to Python Libraries for Data Science Section 14: Introduction to Python Libraries for Data Science Lecture 14 Introduction to Python Libraries for Data Science Section 15: Introduction to R Libraries for Data Science Lecture 15 Introduction to R Libraries for Data Science Section 16: Introduction to R Libraries for Data Science Statistical Modeling Lecture 16 Introduction to R Libraries for Data Science Statistical Modeling Anyone who wants to learn future skills and become Data Scientist, Ai Scientist, Ai Engineer, Ai Researcher & Ai Expert. 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