361 Data Visualization courses

3 QLS Endorsed Diploma | QLS Hard Copy Certificate Included | 10 CPD Courses | Lifetime Access | 24/7 Tutor Support

***24 Hour Limited Time Flash Sale*** Basics of Data Science - CPD Certified Admission Gifts FREE PDF & Hard Copy Certificate| PDF Transcripts| FREE Student ID| Assessment| Lifetime Access| Enrolment Letter In a world where 2.5 quintillion bytes of data are produced every day, how can professionals leverage this data for strategic decision-making and competitive advantage? In the UK, the data science industry is booming, with an estimated increase in demand for data scientists and analytics professionals by over 28% by 2020. This Basics of Data Science bundle gives you diverse analytical skills to launch or advance your analytics career. Designed to cater to the needs of both seasoned professionals and aspiring newcomers, our Basics of Data Science bundle is a comprehensive program that will equip you with the essential skills and knowledge you need to succeed. 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Data Analyst Business Analyst Data Scientist Marketing Analyst Financial Analyst Certificates CPD Accredited Digital certificate Digital certificate - Included CPD Accredited Hard copy certificate Hard copy certificate - Included If you are an international student, then you have to pay an additional 10 GBP for each certificate as an international delivery charge.

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Duration 3 Days 18 CPD hours This course is intended for If you have worked in C++ but want to learn how to make the most of this language, especially for large projects, this course is for you. Overview By the end of this course, you'll have developed programming skills that will set you apart from other C++ programmers. After completing this course, you will be able to: Delve into the anatomy and workflow of C++ Study the pros and cons of different approaches to coding in C++ Test, run, and debug your programs Link object files as a dynamic library Use templates, SFINAE, constexpr if expressions and variadic templates Apply best practice to resource management This course begins with advanced C++ concepts by helping you decipher the sophisticated C++ type system and understand how various stages of compilation convert source code to object code. You'll then learn how to recognize the tools that need to be used in order to control the flow of execution, capture data, and pass data around. By creating small models, you'll even discover how to use advanced lambdas and captures and express common API design patterns in C++. As you cover later lessons, you'll explore ways to optimize your code by learning about memory alignment, cache access, and the time a program takes to run. The concluding lesson will help you to maximize performance by understanding modern CPU branch prediction and how to make your code cache-friendly. Anatomy of Portable C++ Software Managing C++ Projects Writing Readable Code No Ducks Allowed ? Types and Deduction C++ Types Creating User Types Structuring our Code No Ducks Allowed ? Templates and Deduction Inheritance, Polymorphism, and Interfaces Templates ? Generic Programming Type Aliases ? typedef and using Class Templates No Leaks Allowed ? Exceptions and Resources Exceptions in C++ RAII and the STL Move Semantics Name Lookup Caveat Emptor Separation of Concerns ? Software Architecture, Functions, and Variadic Templates Function Objects and Lambda Expressions Variadic Templates The Philosophers' Dinner ? Threads and Concurrency Synchronous, Asynchronous, and Threaded Execution Review Synchronization, Data Hazards, and Race Conditions Future, Promises, and Async Streams and I/O File I/O Implementation Classes String I/O Implementation I/O Manipulators Making Additional Streams Using Macros Everybody Falls, It's How You Get Back Up ? Testing and Debugging Assertions Unit Testing and Mock Testing Understanding Exception Handling Breakpoints, Watchpoints, and Data Visualization Need for Speed ? Performance and Optimization Performance Measurement Runtime Profiling Optimization Strategies Cache Friendly Code

Duration 1 Days 6 CPD hours This course is intended for This course is intended for: Data platform engineers Solutions architects IT professionals Overview In this course, you will learn to: Apply data lake methodologies in planning and designing a data lake Articulate the components and services required for building an AWS data lake Secure a data lake with appropriate permission Ingest, store, and transform data in a data lake Query, analyze, and visualize data within a data lake In this course, you will learn how to build an operational data lake that supports analysis of both structured and unstructured data. You will learn the components and functionality of the services involved in creating a data lake. You will use AWS Lake Formation to build a data lake, AWS Glue to build a data catalog, and Amazon Athena to analyze data. The course lectures and labs further your learning with the exploration of several common data lake Introduction to data lakes Describe the value of data lakes Compare data lakes and data warehouses Describe the components of a data lake Recognize common architectures built on data lakes Data ingestion, cataloging, and preparation Describe the relationship between data lake storage and data ingestion Describe AWS Glue crawlers and how they are used to create a data catalog Identify data formatting, partitioning, and compression for efficient storage and query Lab 1: Set up a simple data lake Data processing and analytics Recognize how data processing applies to a data lake Use AWS Glue to process data within a data lake Describe how to use Amazon Athena to analyze data in a data lake Building a data lake with AWS Lake Formation Describe the features and benefits of AWS Lake Formation Use AWS Lake Formation to create a data lake Understand the AWS Lake Formation security model Lab 2: Build a data lake using AWS Lake Formation Additional Lake Formation configurations Automate AWS Lake Formation using blueprints and workflows Apply security and access controls to AWS Lake Formation Match records with AWS Lake Formation FindMatches Visualize data with Amazon QuickSight Lab 3: Automate data lake creation using AWS Lake Formation blueprints Lab 4: Data visualization using Amazon QuickSight Architecture and course review Post course knowledge check Architecture review Course review