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Duration 4 Days 24 CPD hours This course is intended for This is an introductory-level C++ programming course designed for developers with experience programming in C or other languages. Practical hands-on prior programming experience and knowledge is required. Overview This 'skills-centric' course is about 50% hands-on lab and 50% lecture, designed to train attendees in basic coding with C++, coupling the most current, effective techniques with the soundest industry practices. Our engaging instructors and mentors are highly experienced practitioners who bring years of current 'on-the-job' experience into every classroom. Working in a hands-on learning environment, guided by our expert team, attendees will learn: Writing procedural programs using C++ Using private, public and protected keywords to control access to class members Defining a class in C++ Writing constructors and destructors Writing classes with const and static class members Overloading operators Implementing polymorphic methods in programs Writing programs using file I/O and string streams Using manipulators and stream flags to format output Using the keyword template to write generic functions and classes Writing programs that use generic classes and functions Writing programs that use algorithms and containers of the Standard Library Apply object-oriented design techniques to real-world programming problems Using algorithms and containers of the Standard Library to manipulate string data Understand how C++ protects the programmer from implementation changes in other modules of an application Using try() blocks to trap exceptions Using catch() blocks to handle exceptions Defining exceptions and using throw to trigger them Introduction to C++ Programming / C++ Essentials is a skills-focused, hands-on C++ training course geared for experienced programmers who need to learn C++ coupled with sounds coding skills and best practices for OO development. Students will leave this course armed with the required skills to put foundation-level C++ programming skills right to work in a practical environment. The central concepts of C++ syntax and style are taught in the context of using object-oriented methods to achieve reusability, adaptability and reliability. Emphasis is placed on the features of C++ that support abstract data types, inheritance, and polymorphism. Students will learn to apply the process of data abstraction and class design. Practical aspects of C++ programming including efficiency, performance, testing, and reliability considerations are stressed throughout. Comprehensive hands on exercises are integrated throughout to reinforce learning and develop real competency Moving from C to C++ (Optional) New Compiler Directives Stream Console I/O Explicit Operators Standard Libraries Data Control Capabilities Handling Data New Declaration Features Initialization and Assignment Enumerated Types The bool Type Constant Storage Pointers to Constant Storage Constant Pointers References Constant Reference Arguments Volatile Data Global Data Functions Function Prototypes and Type Checking Default Function Data Types Function Overloading Problems with Function Overloading Name Resolution Promotions and Conversions Call by Value Reference Declarations Call-by-Reference and Reference Types References in Function Return Constant Argument Types Conversion of Parameters Using Default Initializers Providing Default Arguments Inline Functions Operator Overloading Advantages and Pitfalls of Overloading Member Operator Syntax and Examples Class Assignment Operators Class Equality Operators Non-Member Operator Overloading Member and Non-Member Operator Functions Operator Precedence This Pointer Overloading the Assignment Operator Overloading Caveats Creating and Using Objects Creating Automatic Objects Creating Dynamic Objects Calling Object Methods Constructors Initializing Member consts Initializer List Syntax Allocating Resources in Constructor Destructors Block and Function Scope File and Global Scope Class Scope Scope Resolution Operator :: Using Objects as Arguments Objects as Function Return Values Constant Methods Containment Relationships Dynamic Memory Management Advantages of Dynamic Memory Allocation Static, Automatic, and Heap Memory Free Store Allocation with new and delete Handling Memory Allocation Errors Controlling Object Creation Object Copying and Copy Constructor Automatic Copy Constructor Conversion Constructor Streaming I/O Streams and the iostream Library Built-in Stream Objects Stream Manipulators Stream Methods Input/Output Operators Character Input String Streams Formatted I/O File Stream I/O Overloading Stream Operators Persistent Objects Introduction to Object Concepts The Object Programming Paradigm Object-Orientated Programming Definitions Information Hiding and Encapsulation Separating Interface and Implementation Classes and Instances of Objects Overloaded Objects and Polymorphism Declaring and Defining Classes Components of a Class Class Structure Class Declaration Syntax Member Data Built-in Operations Constructors and Initialization Initialization vs. Assignment Class Type Members Member Functions and Member Accessibility Inline Member Functions Friend Functions Static Members Modifying Access with a Friend Class Templates Purpose of Template Classes Constants in Templates Templates and Inheritance Container Classes Use of Libraries Strings in C++ Character Strings The String Class Operators on Strings Member Functions of the String Class Inheritance Inheritance and Reuse Composition vs. Inheritance Inheritance: Centralized Code Inheritance: Maintenance and Revision Public, Private and Protected Members Redefining Behavior in Derived Classes Designing Extensible Software Systems Syntax for Public Inheritance Use of Common Pointers Constructors and Initialization Inherited Copy Constructors Destructors and Inheritance Public, Protected, Private Inheritance Exceptions Types of Exceptions Trapping and Handling Exceptions Triggering Exceptions Handling Memory Allocation Errors C++ Program Structure Organizing C++ Source Files Integrating C and C++ Projects Using C in C++ Reliability Considerations in C++ Projects Function Prototypes Strong Type Checking Constant Types C++ Access Control Techniques Polymorphism in C++ Definition of Polymorphism Calling Overridden Methods Upcasting Accessing Overridden Methods Virtual Methods and Dynamic Binding Virtual Destructors Abstract Base Classes and Pure Virtual Methods Multiple Inheritance Derivation from Multiple Base Classes Base Class Ambiguities Virtual Inheritance Virtual Base Classes Virtual Base Class Information The Standard Template Library STL Containers Parameters Used in Container Classes The Vector Class STL Algorithms Use of Libraries
Duration 2 Days 12 CPD hours This course is intended for Business Analysts, Technical Managers, and Programmers Overview This intensive training course helps students learn the practical aspects of the R programming language. The course is supplemented by many hands-on labs which allow attendees to immediately apply their theoretical knowledge in practice. Over the past few years, R has been steadily gaining popularity with business analysts, statisticians and data scientists as a tool of choice for conducting statistical analysis of data as well as supervised and unsupervised machine learning. What is R ? What is R? ? Positioning of R in the Data Science Space ? The Legal Aspects ? Microsoft R Open ? R Integrated Development Environments ? Running R ? Running RStudio ? Getting Help ? General Notes on R Commands and Statements ? Assignment Operators ? R Core Data Structures ? Assignment Example ? R Objects and Workspace ? Printing Objects ? Arithmetic Operators ? Logical Operators ? System Date and Time ? Operations ? User-defined Functions ? Control Statements ? Conditional Execution ? Repetitive Execution ? Repetitive execution ? Built-in Functions ? Summary Introduction to Functional Programming with R ? What is Functional Programming (FP)? ? Terminology: Higher-Order Functions ? A Short List of Languages that Support FP ? Functional Programming in R ? Vector and Matrix Arithmetic ? Vector Arithmetic Example ? More Examples of FP in R ? Summary Managing Your Environment ? Getting and Setting the Working Directory ? Getting the List of Files in a Directory ? The R Home Directory ? Executing External R commands ? Loading External Scripts in RStudio ? Listing Objects in Workspace ? Removing Objects in Workspace ? Saving Your Workspace in R ? Saving Your Workspace in RStudio ? Saving Your Workspace in R GUI ? Loading Your Workspace ? Diverting Output to a File ? Batch (Unattended) Processing ? Controlling Global Options ? Summary R Type System and Structures ? The R Data Types ? System Date and Time ? Formatting Date and Time ? Using the mode() Function ? R Data Structures ? What is the Type of My Data Structure? ? Creating Vectors ? Logical Vectors ? Character Vectors ? Factorization ? Multi-Mode Vectors ? The Length of the Vector ? Getting Vector Elements ? Lists ? A List with Element Names ? Extracting List Elements ? Adding to a List ? Matrix Data Structure ? Creating Matrices ? Creating Matrices with cbind() and rbind() ? Working with Data Frames ? Matrices vs Data Frames ? A Data Frame Sample ? Creating a Data Frame ? Accessing Data Cells ? Getting Info About a Data Frame ? Selecting Columns in Data Frames ? Selecting Rows in Data Frames ? Getting a Subset of a Data Frame ? Sorting (ordering) Data in Data Frames by Attribute(s) ? Editing Data Frames ? The str() Function ? Type Conversion (Coercion) ? The summary() Function ? Checking an Object's Type ? Summary Extending R ? The Base R Packages ? Loading Packages ? What is the Difference between Package and Library? ? Extending R ? The CRAN Web Site ? Extending R in R GUI ? Extending R in RStudio ? Installing and Removing Packages from Command-Line ? Summary Read-Write and Import-Export Operations in R ? Reading Data from a File into a Vector ? Example of Reading Data from a File into A Vector ? Writing Data to a File ? Example of Writing Data to a File ? Reading Data into A Data Frame ? Writing CSV Files ? Importing Data into R ? Exporting Data from R ? Summary Statistical Computing Features in R ? Statistical Computing Features ? Descriptive Statistics ? Basic Statistical Functions ? Examples of Using Basic Statistical Functions ? Non-uniformity of a Probability Distribution ? Writing Your Own skew and kurtosis Functions ? Generating Normally Distributed Random Numbers ? Generating Uniformly Distributed Random Numbers ? Using the summary() Function ? Math Functions Used in Data Analysis ? Examples of Using Math Functions ? Correlations ? Correlation Example ? Testing Correlation Coefficient for Significance ? The cor.test() Function ? The cor.test() Example ? Regression Analysis ? Types of Regression ? Simple Linear Regression Model ? Least-Squares Method (LSM) ? LSM Assumptions ? Fitting Linear Regression Models in R ? Example of Using lm() ? Confidence Intervals for Model Parameters ? Example of Using lm() with a Data Frame ? Regression Models in Excel ? Multiple Regression Analysis ? Summary Data Manipulation and Transformation in R ? Applying Functions to Matrices and Data Frames ? The apply() Function ? Using apply() ? Using apply() with a User-Defined Function ? apply() Variants ? Using tapply() ? Adding a Column to a Data Frame ? Dropping A Column in a Data Frame ? The attach() and detach() Functions ? Sampling ? Using sample() for Generating Labels ? Set Operations ? Example of Using Set Operations ? The dplyr Package ? Object Masking (Shadowing) Considerations ? Getting More Information on dplyr in RStudio ? The search() or searchpaths() Functions ? Handling Large Data Sets in R with the data.table Package ? The fread() and fwrite() functions from the data.table Package ? Using the Data Table Structure ? Summary Data Visualization in R ? Data Visualization ? Data Visualization in R ? The ggplot2 Data Visualization Package ? Creating Bar Plots in R ? Creating Horizontal Bar Plots ? Using barplot() with Matrices ? Using barplot() with Matrices Example ? Customizing Plots ? Histograms in R ? Building Histograms with hist() ? Example of using hist() ? Pie Charts in R ? Examples of using pie() ? Generic X-Y Plotting ? Examples of the plot() function ? Dot Plots in R ? Saving Your Work ? Supported Export Options ? Plots in RStudio ? Saving a Plot as an Image ? Summary Using R Efficiently ? Object Memory Allocation Considerations ? Garbage Collection ? Finding Out About Loaded Packages ? Using the conflicts() Function ? Getting Information About the Object Source Package with the pryr Package ? Using the where() Function from the pryr Package ? Timing Your Code ? Timing Your Code with system.time() ? Timing Your Code with System.time() ? Sleeping a Program ? Handling Large Data Sets in R with the data.table Package ? Passing System-Level Parameters to R ? Summary Lab Exercises Lab 1 - Getting Started with R Lab 2 - Learning the R Type System and Structures Lab 3 - Read and Write Operations in R Lab 4 - Data Import and Export in R Lab 5 - k-Nearest Neighbors Algorithm Lab 6 - Creating Your Own Statistical Functions Lab 7 - Simple Linear Regression Lab 8 - Monte-Carlo Simulation (Method) Lab 9 - Data Processing with R Lab 10 - Using R Graphics Package Lab 11 - Using R Efficiently
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Advance Your Career This IELTS writing masterclass course will provide you with a fresh opportunity to enter the relevant job market and choose your desired career path. Additionally, you will be able to advance your career, increase your level of competition in your chosen field, and highlight these skills on your resume. Recognised Accreditation This course is accredited by continuing professional development (CPD). CPD UK is globally recognised by employers, professional organisations, and academic institutions, thus a certificate from CPD Certification Service creates value towards your professional goal and achievement. The Quality Licence Scheme is a brand of the Skills and Education Group, a leading national awarding organisation for providing high-quality vocational qualifications across a wide range of industries. What is CPD? Employers, professional organisations, and academic institutions all recognise CPD, therefore a credential from CPD Certification Service adds value to your professional goals and achievements. Benefits of CPD Improve your employment prospects Boost your job satisfaction Promotes career advancement Enhances your CV Provides you with a competitive edge in the job market Demonstrate your dedication Showcases your professional capabilities What is IPHM? The IPHM is an Accreditation Board that provides Training Providers with international and global accreditation. The Practitioners of Holistic Medicine (IPHM) accreditation is a guarantee of quality and skill. Benefits of IPHM It will help you establish a positive reputation in your chosen field You can join a network and community of successful therapists that are dedicated to providing excellent care to their client You can flaunt this accreditation in your CV It is a worldwide recognised accreditation What is Quality Licence Scheme? 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Benefits of Quality License Scheme Certificate is valuable Provides a competitive edge in your career It will make your CV stand out Course Curriculum Introduction Find Out All About This Course in Less Than 00:04:00 IELTS Introduction 00:05:00 IELTS Explaining The Banding System 00:07:00 IELTS What is Task 1 00:07:00 IELTS What is Task 2 00:09:00 IELTS Task Achievement and Task Response 00:09:00 IELTS Coherence and Cohesion 00:04:00 IELTS Vocabulary 00:09:00 IELTS Grammatical Range and Accuracy 00:05:00 IELTS Extra Tips to Prepare for The IELTS 00:06:00 IELTS Task One Example 00:07:00 IELTS Task Two Example 00:06:00 IELTS Task One Structure 00:02:00 IELTS Task Two Structure 00:10:00 IELTS Planning 00:06:00 IELTS Examiners Notes 00:07:00 IELTS Go Through Task 1 00:06:00 IELTS Go Through Task 2 00:05:00 IELTS Tips for The Exam 00:04:00 Thank You 00:01:00 Supplementary Resources Supplementary Resources - IELTS Writing Masterclass 00:00:00 Obtain Your Certificate Order Your Certificate of Achievement 00:00:00 Get Your Insurance Now Get Your Insurance Now 00:00:00 Feedback Feedback 00:00:00