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Overview This comprehensive course on Kotlin Programming : Android Coding will deepen your understanding on this topic. After successful completion of this course you can acquire the required skills in this sector. This Kotlin Programming : Android Coding comes with accredited certification from CPD, which will enhance your CV and make you worthy in the job market. So enrol in this course today to fast track your career ladder. How will I get my certificate? You may have to take a quiz or a written test online during or after the course. After successfully completing the course, you will be eligible for the certificate. Who is This course for? There is no experience or previous qualifications required for enrolment on this Kotlin Programming : Android Coding. It is available to all students, of all academic backgrounds. Requirements Our Kotlin Programming : Android Coding is fully compatible with PC's, Mac's, Laptop, Tablet and Smartphone devices. This course has been designed to be fully compatible with tablets and smartphones so you can access your course on Wi-Fi, 3G or 4G. There is no time limit for completing this course, it can be studied in your own time at your own pace. Career Path Learning this new skill will help you to advance in your career. It will diversify your job options and help you develop new techniques to keep up with the fast-changing world. This skillset will help you to- Open doors of opportunities Increase your adaptability Keep you relevant Boost confidence And much more! Course Curriculum 11 sections • 73 lectures • 05:38:00 total length •Introduction To This Course: 00:02:00 •Windows Setup: 00:13:00 •Mac Setup: 00:10:00 •Linux Setup: 00:12:00 •Online Code Editor: 00:02:00 •Variables: 00:06:00 •Data Types: 00:06:00 •String: 00:05:00 •Array: 00:07:00 •Data Type Conversion: 00:05:00 •Comments: 00:04:00 •Arithmetic Operators: 00:07:00 •Relational Operators: 00:06:00 •Assignment Operators: 00:06:00 •Unary Operators: 00:05:00 •Bitwise Operators: 00:09:00 •Logical Operators: 00:04:00 •Input & Output: 00:03:00 •Conditional if Statement: 00:05:00 •when Statement: 00:07:00 •For Loop: 00:04:00 •while Loop: 00:04:00 •do while Loop: 00:04:00 •Break Statement: 00:04:00 •Continue Statement: 00:04:00 •Basic Functions: 00:03:00 •Function Parameters: 00:04:00 •Return Values: 00:04:00 •Recursion: 00:04:00 •Default & Named Arguments: 00:06:00 •Lambda Function: 00:04:00 •Higher Order Function: 00:05:00 •Inline Function: 00:02:00 •Try Catch Block: 00:04:00 •Try Catch Expression: 00:05:00 •Multiple Catch Block: 00:05:00 •Nested Try Catch Block: 00:05:00 •Finally Block: 00:02:00 •Throw Keyword: 00:02:00 •Nullable & Non Nullable Types: 00:03:00 •Smart Cast: 00:02:00 •Unsafe and Safe Cast: 00:03:00 •Elvis Operator: 00:04:00 •List: listOf Function: 00:06:00 •List: mutableListOf Function: 00:05:00 •List: arrayListOf Function: 00:06:00 •Map: mapOf Function: 00:07:00 •Map: HashMap: 00:08:00 •Map: hashMapOf Function: 00:05:00 •Map: mutableMapOf Function: 00:04:00 •Set: setOf Function: 00:04:00 •Set: mutableSetOf Function: 00:04:00 •Set: HashSet: 00:04:00 •Basic Example: 00:07:00 •Nested and Inner Class: 00:06:00 •Constructors: 00:05:00 •Visibility Modifiers: 00:06:00 •Inheritance: 00:05:00 •Method Overriding: 00:04:00 •Property Overriding: 00:02:00 •Abstract Class: 00:03:00 •Superclass: 00:03:00 •Data Class: 00:05:00 •Multiple Class Inheritance & Interfaces: 00:03:00 •Sealed Class: 00:03:00 •Extension Function: 00:03:00 •Generics: 00:05:00 •Integer Type Range: 00:05:00 •Regex: 00:04:00 •Call Java from Kotlin: 00:03:00 •Call Kotlin from Java: 00:02:00 •Resource: 00:00:00 •Assignment - Kotlin Masterclass Programming Course: Android Coding Bible: 00:00:00

Overview This comprehensive course on Data Science & Machine Learning with R will deepen your understanding on this topic. After successful completion of this course you can acquire the required skills in this sector. This Data Science & Machine Learning with R comes with accredited certification, which will enhance your CV and make you worthy in the job market. So enrol in this course today to fast track your career ladder. How will I get my certificate? You may have to take a quiz or a written test online during or after the course. After successfully completing the course, you will be eligible for the certificate. Who is This course for? There is no experience or previous qualifications required for enrolment on this Data Science & Machine Learning with R. It is available to all students, of all academic backgrounds. Requirements Our Data Science & Machine Learning with R is fully compatible with PC's, Mac's, Laptop, Tablet and Smartphone devices. This course has been designed to be fully compatible with tablets and smartphones so you can access your course on Wi-Fi, 3G or 4G. There is no time limit for completing this course, it can be studied in your own time at your own pace. Career Path Having these various qualifications will increase the value in your CV and open you up to multiple sectors such as Business & Management, Admin, Accountancy & Finance, Secretarial & PA, Teaching & Mentoring etc. Course Curriculum 10 sections • 69 lectures • 22:07:00 total length •Data Science and Machine Learning Introduction: 00:03:00 •What is Data Science: 00:10:00 •Machine Learning Overview: 00:05:00 •Who is This Course for: 00:03:00 •Data Science and Machine Learning Marketplace: 00:05:00 •Data Science and Machine Learning Job Opportunities: 00:03:00 •Getting Started: 00:11:00 •Basics: 00:06:00 •Files: 00:11:00 •RStudio: 00:07:00 •Tidyverse: 00:05:00 •Resources: 00:04:00 •Unit Introduction: 00:30:00 •Basic Type: 00:09:00 •Vector Part One: 00:20:00 •Vectors Part Two: 00:25:00 •Vectors - Missing Values: 00:16:00 •Vectors - Coercion: 00:14:00 •Vectors - Naming: 00:10:00 •Vectors - Misc: 00:06:00 •Creating Matrics: 00:31:00 •List: 00:32:00 •Introduction to Data Frames: 00:19:00 •Creating Data Frames: 00:20:00 •Data Frames: Helper Functions: 00:31:00 •Data Frames Tibbles: 00:39:00 •Intermediate Introduction: 00:47:00 •Relational Operations: 00:11:00 •Conditional Statements: 00:11:00 •Loops: 00:08:00 •Functions: 00:14:00 •Packages: 00:11:00 •Factors: 00:28:00 •Dates and Times: 00:30:00 •Functional Programming: 00:37:00 •Data Import or Export: 00:22:00 •Database: 00:27:00 •Data Manipulation in R Introduction: 00:36:00 •Tidy Data: 00:11:00 •The Pipe Operator: 00:15:00 •The Filter Verb: 00:22:00 •The Select Verb: 00:46:00 •The Mutate Verb: 00:32:00 •The Arrange Verb: 00:10:00 •The Summarize Verb: 00:23:00 •Data Pivoting: 00:43:00 •JSON Parsing: 00:11:00 •String Manipulation: 00:33:00 •Web Scraping: 00:59:00 •Data Visualization in R Section Intro: 00:17:00 •Getting Started: 00:16:00 •Aesthetics Mappings: 00:25:00 •Single Variable Plots: 00:37:00 •Two Variable Plots: 00:21:00 •Facets, Layering, and Coordinate Systems: 00:18:00 •Styling and Saving: 00:12:00 •Creating with R Markdown: 00:29:00 •Introduction to R Shiny: 00:26:00 •A Basic R Shiny App: 00:31:00 •Other Examples with R Shiny: 00:34:00 •Machine Learning Part 1: 00:22:00 •Machine Learning Part 2: 00:47:00 •Starting a Data Science Career Section Overview: 00:03:00 •Data Science Resume: 00:04:00 •Getting Started with Freelancing: 00:05:00 •Top Freelance Websites: 00:05:00 •Personal Branding: 00:05:00 •Importance of Website and Blo: 00:04:00 •Networking Do's and Don'ts: 00:04:00

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