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Duration 5 Days 30 CPD hours This course is intended for This course is designed for students who want to learn the R programming language, particularly students who want to leverage R for data analysis and data science tasks in their organization. The course is also designed for students with an interest in applying statistics to real-world problems. A typical student in this course should have several years of experience with computing technology, along with a proficiency in at least one other programming language. Overview In this course, you will use R to perform common data science tasks.You will: Set up an R development environment and execute simple code. Perform operations on atomic data types in R, including characters, numbers, and logicals. Perform operations on data structures in R, including vectors, lists, and data frames. Write conditional statements and loops. Structure code for reuse with functions and packages. Manage data by loading and saving datasets, manipulating data frames, and more. Analyze data through exploratory analysis, statistical analysis, and more. Create and format data visualizations using base R and ggplot2. Create simple statistical models from data. In our data-driven world, organizations need the right tools to extract valuable insights from that data. The R programming language is one of the tools at the forefront of data science. Its robust set of packages and statistical functions makes it a powerful choice for analyzing data, manipulating data, performing statistical tests on data, and creating predictive models from data. Likewise, R is notable for its strong data visualization tools, enabling you to create high-quality graphs and plots that are incredibly customizable. This course will teach you the fundamentals of programming in R to get you started. It will also teach you how to use R to perform common data science tasks and achieve data-driven results for the business. Lesson 1: Setting Up R and Executing Simple Code Topic A: Set Up the R Development Environment Topic B: Write R Statements Lesson 2: Processing Atomic Data Types Topic A: Process Characters Topic B: Process Numbers Topic C: Process Logicals Lesson 3: Processing Data Structures Topic A: Process Vectors Topic B: Process Factors Topic C: Process Data Frames Topic D: Subset Data Structures Lesson 4: Writing Conditional Statements and Loops Topic A: Write Conditional Statements Topic B: Write Loops Lesson 5: Structuring Code for Reuse Topic A: Define and Call Functions Topic B: Apply Loop Functions Topic C: Manage R Packages Lesson 6: Managing Data in R Topic A: Load Data Topic B: Save Data Topic C: Manipulate Data Frames Using Base R Topic D: Manipulate Data Frames Using dplyr Topic E: Handle Dates and Times Lesson 7: Analyzing Data in R Topic A: Examine Data Topic B: Explore the Underlying Distribution of Data Topic C: Identify Missing Values Lesson 8: Visualizing Data in R Topic A: Plot Data Using Base R Functions Topic B: Plot Data Using ggplot2 Topic C: Format Plots in ggplot2 Topic D: Create Combination Plots Lesson 9: Modeling Data in R Topic A: Create Statistical Models in R Topic B: Create Machine Learning Models in R

Duration 2 Days 12 CPD hours This course is intended for This introduction to Spring development course requires that incoming students possess solid Java programming skills and practical hands-on Java experience. This class is geared for experienced Java developers who are new to Spring, who wish to understand how and when to use Spring in Java and JEE applications. Overview Working in a hands-on learning environment, led by our expert practitioner, students will: Explain the issues associated with complex frameworks such as JEE and how Spring addresses those issues Understand the relationships between Spring and JEE, AOP, IOC and JDBC. Write applications that take advantage of the Spring container and the declarative nature of assembling simple components into applications. Understand how to configure the Spring Boot framework Understand and work on integrating persistence into a Spring application Explain Spring's support for transactions and caching Work with Spring Boot to facilitate Spring setup and configuration Apply Aspect Oriented Programming (AOP) to Spring applications Become familiar with the conditionally loading of bean definitions and Application Contexts Understand how to leverage the power of Spring Boot Use Spring Boot to create and work with JPA repositories Introduction to Spring Boot | Spring Boot Quick Start is a hands-on Spring training course geared for experienced Java developers who need to understand what the Spring Boot is in terms of today's systems and architectures, and how to use Spring in conjunction with other technologies and frameworks. This leading-edge course provides added coverage of Spring's Aspect-Oriented Programming and the use of Spring Boot. Students will gain hands-on experience working with Spring, using Maven for project and dependancy management, and, optionally, a test-driven approach (using JUnit) to the labs in the course. The Spring framework is an application framework that provides a lightweight container that supports the creation of simple-to-complex components in a non-invasive fashion. Spring's flexibility and transparency is congruent and supportive of incremental development and testing. The framework's structure supports the layering of functionality such as persistence, transactions, view-oriented frameworks, and enterprise systems and capabilities. This course targets Spring Boot 2 , which includes full support for Java SE 11 and Java EE 8. Spring supports the use of lambda expressions and method references in many of its APIs. The Spring Framework Understand the value of Spring Explore Dependency Injection (DI) and Inversion of Control (IoC) Introduce different ways of configuring collaborators Spring as an Object Factory Initializing the Spring IoC Container Configuring Spring Managed Beans Introduce Java-based configuration The @Configuration and @Bean annotations Define bean dependencies Bootstrapping Java Config Context Injection in Configuration classes Using context Profiles Conditionally loading beans and configurations Bean Life-Cycle Methods Defining Bean dependencies Introduce Spring annotations for defining dependencies Explore the @Autowired annotation Stereotype Annotations Qualifying injection points Lifecycle annotations Using properties in Java based configuration The @Value annotation Using the Candidate Components Index Introduction to Spring Boot Introduce the basics of Spring Boot Explain auto-configuration Introduce the Spring Initializr application Bootstrapping a Spring Boot application Working with Spring Boot Provide an overview of Spring Boot Introduce starter dependencies Introduce auto-configuration @Enable... annotations Conditional configuration Spring Boot Externalized Configuration Bootstrapping Spring Boot Introduction to Aspect Oriented Programming Aspect Oriented Programming Cross Cutting Concerns Spring AOP Spring AOP in a Nutshell @AspectJ support Spring AOP advice types AspectJ pointcut designators Spring Boot Actuator Understand Spring Boot Actuators Work with predefined Actuator endpoints Enabling Actuator endpoints Securing the Actuator Developing in Spring Boot Introduce Spring Boot Devtools Enable the ConditionEvaluationReport Debugging Spring Boot applications Thymeleaf Provide a quick overview of Thymeleaf Introduce Thymeleaf templates Create and run a Spring Thymeleaf MVC application Additional course details: Nexus Humans Spring Boot Quick Start | Core Spring, Spring AOP, Spring Boot 2.0 and More (TT3322) training program is a workshop that presents an invigorating mix of sessions, lessons, and masterclasses meticulously crafted to propel your learning expedition forward. This immersive bootcamp-style experience boasts interactive lectures, hands-on labs, and collaborative hackathons, all strategically designed to fortify fundamental concepts. Guided by seasoned coaches, each session offers priceless insights and practical skills crucial for honing your expertise. Whether you're stepping into the realm of professional skills or a seasoned professional, this comprehensive course ensures you're equipped with the knowledge and prowess necessary for success. While we feel this is the best course for the Spring Boot Quick Start | Core Spring, Spring AOP, Spring Boot 2.0 and More (TT3322) course and one of our Top 10 we encourage you to read the course outline to make sure it is the right content for you. Additionally, private sessions, closed classes or dedicated events are available both live online and at our training centres in Dublin and London, as well as at your offices anywhere in the UK, Ireland or across EMEA.

Duration 3 Days 18 CPD hours This course is intended for This course is primarily designed for students who want to gain the skills necessary to use VBA to automate tasks in Excel such as collecting data from external sources, cleaning, and manipulating data. The target student may also want to learn how to create custom worksheet functions to streamline worksheet formulas and make complex worksheets easier to support, maintain, and understand. Overview In this course, you will develop and deploy VBA modules to solve business problems. You will: Identify general components of VBA and their appropriate use in solving business solutions. Record VBA macros to automate repetitive tasks. Use reference tools built into Excel to get help on VBA programming language and objects used in the Excel VBA environment. Write VBA code to create a custom worksheet function. Eliminate, avoid, or handle errors in VBA code, and optimize its performance. Control how and when macros run. Develop UserForm objects to create custom dialog boxes and windows. Use VBA to read and write data from local files and cloud services. Use VBA to clean and transform data. Run programs and commands outside of Excel and share VBA projects with other users VBA (Visual Basic for Applications) enables you to enhance and extend the capabilities of Microsoft© Excel© and other applications in the Microsoft© Office application suite. You can use VBA to perform tasks that would be difficult or impossible to do using only worksheet functions, and you can automate a wide range of tasks involving the collection, processing, analysis, and visualization of data. This course will give you a good foundation for understanding, creating, and using VBA in your own Excel workbooks, show you how to work with data across different applications, and how to package the macros and functions you create so you can back them up, move them to other computers, and share them with other users Prerequisites To ensure your success in this course, you should be an experienced Excel user who is comfortable creating and working with Excel workbooks, including tasks such as entering worksheet formulas, using absolute and relative addressing, formatting cells, and creating pivot tables and charts. This level of skill could be acquired by taking the Microsoft Excel for Office 365? (Desktop or Online) courses, Parts 1, 2, and 3 1 - Using VBA to Solve Business Problems Topic A: Use Macros to Automate Tasks in Excel Topic B: Identify Components of Macro-Enabled Workbooks Topic C: Configure the Excel VBA Environment 2 - Automating Repetitive Tasks Topic A: Use the Macro Recorder to Create a VBA Macro Topic B: Record a Macro with Relative Addressing Topic C: Delete Macros and Modules Topic D: Identify Strategies for Using the Macro Recorder 3 - Getting Help on VBA Topic A: Use VBA Help Topic B: Use the Object Browser to Discover Objects You Can Use in VBA Topic C: Use the Immediate Window to Explore Object Properties and Methods 4 - Creating Custom Worksheet Functions Topic A: Create a Custom Function Topic B: Make Decisions in Code Topic C: Work with Variables Topic D: Perform Repetitive Tasks 5 - Improving Your VBA Code Topic A: Debug VBA Errors Topic B: Deal with Errors Topic C: Improve Macro Performance 6 - Controlling How and When Macros Run Topic A: Prompt the User for Information Topic B: Configure Macros to Run Automatically 7 - Developing Custom Forms Topic A: Display a Custom Dialog Box Topic B: Program Form Events 8 - Using VBA to Work with Files Topic A: Use VBA to Get File and Directory Structure Topic B: Use VBA to Read Text Files Topic C: Use VBA to Write Text Files 9 - Using VBA to Clean and Transform Data Topic A: Automate Power Query Topic B: Transform Data Using VBA and Workbook Functions Topic C: Use Regular Expressions Topic D: Manage Errors in Data 10 - Extending the Programming Environment Beyond the Workbook Topic A: Run Other Programs and Commands Topic B: Share Your VBA Projects

Python Course, code the Hangman. Basic Python Course covers in one hour the coding of an interesting app. Any one very welcome. Our Style: Hands-on, Practical Location: Online, Instructor-led Download: anaconda.com Duration: 1 Hour Times: arrange a time for your time zone

Powerful 1-hour Python workshop course understand Python Basics. Practical. Instructor-led. Online. Learn to code a Password Validator in 1 hour. 

Duration 4 Days 24 CPD hours This course is intended for This in an intermediate-level Java development course geared for students experienced with Java and Spring programming essentials. This course does not cover Java or Spring development basics. Overview Working within in an engaging, hands-on learning environment, guided by our expert team, attendees will: Understand the ReactiveX specification Understand the basics of Reactive Programming Discuss the advantages and limitations of Observables Write a client application capable of handling Reactive events Apply operators to event streams to filter, modify and combine the objects emitted by event publishers Select the appropriate type of Event Source Use both Cold and Hot Observables Deal with backpressure problems in reactive programming Develop a reactive web application using Spring WebFlux Define application flows of a WebFlux application Use the WebClient API to work with both synchronous and streaming APIs Develop Unit and Integration tests to test WebFlux endpoints Creating a reactive REST endpoint Become familiar with the basics of WebSockets Create a WebSocket endpoint using Spring Create a WebSocket client Understand the basics of NoSQL Become familiar with the basics of MongoDB Understand how the data in MongoDB can be retrieved using a Reactive API Define Spring Data MongoDB repositories Query the MongoDB using Spring Data Define a reactive repository using MongoDB Explore the Spring Data R2DBC API to perform reactive CRUD operations against a relational database Spring Data reative allow us to implement database operations relying on Reative Programming APIs. While the Spring R2DBC initiative aims to bring reactive programming to relational databaes, several NoSQL databases already provide this possibility. After an introduction to NoSQL and the MongoDB, this courses covers the APIs available to communicate with this NoSQL database using both blocking and reactive APIs.Introdcution to Reactive Spring is a comprehensive Java training workshop geared for experienced developers who wish to explore concurrent, asynchronous and reactive programming APIs and techniques using Spring. After an introduction to reactive programming, Reactive Streams and the Project Reactor APIs, this course will show how this APIs are integrated into Spring. Spring 5 includes Spring WebFlux, providing a reactive programming model for web applications, including support for Reactive REST APIs. Spring WebSocket assists in the creation of web applications which provide a full-duplex, two-way communication between client and server. Introduction to Reactive Programming Reactive Manifesto Introduce ReactiveX ReactiveX implementations The Observer, Iterator pattern and functional programming Discuss hot and cold publishers Reactive Streams API Introduce the Reactive Streams specification Publisher and Subscribers java.util.concurrent.Flow Transformation of Messages (Processor) Controlling messages Tutorial: Setup Eclipse for Using Maven Introduction Introduce the Reactor Building blocks Flux and Mono Creating observables Subscribing to a stream Testing Event Sources (introduction) Testing reactive implementations StepVerifier : test sequence of emitted items Defining expectations TestPublisher: produce test data to test downstream operators Reactive Operators Introduce Operators Show the use of marble diagrams Explain some commonly used operators Callback operators Schedulers (Multithreading) Thread usage of subscriber and consumer Using the subscribeOn method Introduce the Scheduler interface Using the observeOn method Backpressure Strategies for dealing with Backpressure ?reactive pull? backpressure Exception Handling Handling errors in onError Exception handling strategies Using onErrorReturn or onErrorNext operators Using the retry operators The Global Error Handler Spring Data Review Quick review of Spring Data repositories Query return types Defining Query methods Pagination and sorting R2DBC Reactive Relational Database Connectivity DatabaseClient Performing CRUD operations Reactive Query annotated methods Spring WebFlux: Introduction Annotated Controllers Functional Endpoints WebFlux configuration Creating a reactive REST endpoint Defining flows Defining the application flow Actions Defining decision Navigating flows RouterFunction View Technologies View technologies Using Thymeleaf to create the view View Configuration Spring WebClient: Introduction to WebClient Working with asynchronous and streaming APIs Making requests Handling the response Lab: WebClient WebTestClient Testing WebFlux server endpoints Testing controllers or functions Define integration tests Introduction to Spring Reactive WebSockets Be familiar with the basics of WebSockets Understand the HTTP handshake and upgrade Name some of the advantages of WebSockets Defining the WebSocket WebSocket Message Handling WebSocketSession Implementing the WebSockethandler Creating a Browser WebSocket Client WebSocket STOMP Streaming (or Simple) text-orientated messaging protocol Introduce SockJS Connecting to the STOMP endpoint Configuring the message broker STOMP destinations Reactive WebSocket Reactive WebSocket support Implement the reactive WebSocketHandler BigData Introduce Big Data Explain the need for enhanced data storage Introduction to MongoDB JavaScript Object Notation Overview Introduce Binary JSON (BSON) Starting the database Creating Collections and Documents Executing ?simple? database commands Introduce the ObjectID Searching for documents using query operators Updating and deleting documents MongoDB Compass Spring and MongoDB MongoDB Support in Spring Data MongoClient and MongoTemplate Spring Data MongoDB configuration @EnableMongoRepositories Adding documents to the database The @Document and @Field annotations Polymorphism and the _class property The Criteria object Spring Data MongoDB MongoRepository Field naming strategy Using JSON queries to find documents The @PersistenceConstructor annotation Reactive Repositories with MongoDB Using reactive repositories ReactiveMongoTemplate RxJava or Reactor Additional course details: Nexus Humans Introduction to Reactive Spring (TT3355 ) training program is a workshop that presents an invigorating mix of sessions, lessons, and masterclasses meticulously crafted to propel your learning expedition forward. This immersive bootcamp-style experience boasts interactive lectures, hands-on labs, and collaborative hackathons, all strategically designed to fortify fundamental concepts. Guided by seasoned coaches, each session offers priceless insights and practical skills crucial for honing your expertise. Whether you're stepping into the realm of professional skills or a seasoned professional, this comprehensive course ensures you're equipped with the knowledge and prowess necessary for success. While we feel this is the best course for the Introduction to Reactive Spring (TT3355 ) course and one of our Top 10 we encourage you to read the course outline to make sure it is the right content for you. Additionally, private sessions, closed classes or dedicated events are available both live online and at our training centres in Dublin and London, as well as at your offices anywhere in the UK, Ireland or across EMEA.

Duration 5 Days 30 CPD hours This course is intended for This course is primarily for Developers, Developer Consultants, Help Desk/COE Support, and Program/Project Managers. Overview Learn the fundamental concepts of the ABAP programming languageEfficiently use the ABAP Workbench toolsCreate simple application programs with user dialogs (list, selection screen, screens, Web Dynpro) and database dialogs (reading from the database) In this course, students gain knowledge of the fundamental concepts of ABAP and learn how to comfortably and efficiently work with the ABAP Workbench tools in order to undertake custom developments with confidence. Flow of an ABAP Program Describing the Processing of ABAP Programs ABAP Workbench Introduction Introducing the ABAP Development Environment Organizing ABAP Developments Developing Programs Finalizing Development Basic ABAP Language Elements Defining Elementary Data Objects Using Basic ABAP Statements Working with the ABAP Debugger Modularization Introducing Modularization Modularizing Using Subroutines Modularizing Using Function Modules Implementing Function Modules Modularizing Using BAPIs Modularizing Using Global Classes Implementing Simple Global Classes and Static Methods Modularizing Using Local Classes Complex Data Objects Working with Structures Working with Internal Tables Data Modeling and Data Retrieval Modeling Data Reading Single Database Records Reading Multiple Database Records Handling Other Aspects of Database Access Working with Authorization Checks Classic ABAP Report Implementing ABAP Lists Implementing Selection Screens Implementing Events of ABAP Reports Screen Creating Screens Creating Input/Output Fields Implementing Data Transport SAP List Viewer Using the SAP List Viewer Web Dynpro ABAP Describing Web Dynpro ABAP Implementing Navigation in Web Dynpro Implementing Data Transport in Web Dynpro Program Analysis Tools Using the Code Inspector ABAP Development Tools for SAP NetWeaver Describing ABAP Development Tools for SAP NetWeaver Creating an ABAP Project in Eclipse SAP Standard Software Adjustments Adjusting the SAP Standard Software Additional course details: Nexus Humans BC400 SAP ABAP Workbench Foundations training program is a workshop that presents an invigorating mix of sessions, lessons, and masterclasses meticulously crafted to propel your learning expedition forward. This immersive bootcamp-style experience boasts interactive lectures, hands-on labs, and collaborative hackathons, all strategically designed to fortify fundamental concepts. Guided by seasoned coaches, each session offers priceless insights and practical skills crucial for honing your expertise. Whether you're stepping into the realm of professional skills or a seasoned professional, this comprehensive course ensures you're equipped with the knowledge and prowess necessary for success. While we feel this is the best course for the BC400 SAP ABAP Workbench Foundations course and one of our Top 10 we encourage you to read the course outline to make sure it is the right content for you. Additionally, private sessions, closed classes or dedicated events are available both live online and at our training centres in Dublin and London, as well as at your offices anywhere in the UK, Ireland or across EMEA.

This course shows you how to apply various approaches and algorithms to solve business problems through AI and ML, follow a methodical workflow to develop sound solutions, use open-source, off-the-shelf tools to develop, test, and deploy those solutions, and ensure that they protect the privacy of users. This course includes hands-on activities for each topic area.

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