4679 Courses

Duration 2 Days 12 CPD hours This course is intended for Data Protection Officers IT Managers and Administrators Records Managers System Developers IT Security specialist Anyone who builds and develops IT systems Overview Critical data protection concepts and practices that impact IT Consumer data protection expectations and responsibility How to bake privacy into early stages of IT products and services for cost control, accuracy and speed-to-market How to establish data protection practices for data collection and transfer How to preempt data protection issues in the Internet of Things How to factor data protection into data classification and emerging tech such as cloud computing, facial recognition and surveillance How to communicate data protection issues with partners such as management, development, marketing and legal The Principles of Privacy in Technology training is the how to course on privacy and data protection practices in the development, engineering, deployment and auditing of IT products and services. Those taking the course will develop an understanding of privacy-related issues and practices in the context of the design and implementation of information and communication technologies and systems. The training is based on the body of knowledge for the IAPP?s ANSI accredited Certified Information Privacy Technologist (CIPT) certification program. Fundamentals of information privacy Reviewing the modern history of privacy Foundational privacy concepts Data protection roles and fair information practices Exploring the impacts of privacy and data protection regulations on information management Privacy in the IT environment Compliance requirements IT risks Stakeholder privacy expectations Differentiating between privacy and security Core privacy concepts Foundational elements for embedding privacy in IT Common privacy principles Data protection by design and default Privacy considerations in the information life cycle Privacy considerations throughout the stages of the information life cycle Privacy in systems and applications Examining the risks inherent in the IT environment and options for addressing them Identity and access management Credit card information and processing Remote access BYOD and telecommuting Data encryption Additional privacy-enhancing technologies in the enterprise environment Privacy techniques Strengths and weaknesses of authentication techniques Using identifiers Privacy by design Online privacy issues Unique challenges that come from online privacy issues Laws and regulations Online threats Social media E-commerce Tracking technologies Web security protocols Technologies with privacy considerations Privacy considerations associated with a variety of technologies Cloud computing Wireless IDs Location-based services ?Smart? technologies Video/data/audio surveillance Biometric recognition

Duration 2 Days 12 CPD hours This course is intended for This course is designed primarily for customer engineers and systems engineers in the following job roles: Automation architect Automation engineer Consulting systems engineer DevOps engineer Network administrator Network architect Network consulting engineer Network design engineer Network engineer Network operator Network reliability engineer Sales engineer Site reliability engineer Systems engineer Technical solutions architect Overview After taking this course, you should be able to: Articulate the role network automation and programmability play in the context of end-to-end network management and operations Define and differentiate between waterfall and agile software development methodologies Interpret and troubleshoot Python scripts with fundamental programming constructs built for network automation use cases Describe how DevOps principles, tools, and pipelines can be applied to network operations Understand the role of network automation development environments and associated technologies such as Python virtual environments, Vagrant, and Docker Understand and construct HTTP-based API calls to network devices Articulate the differences among and common use cases for XML, JSON, YAML, and protobuf Construct and interpret Python scripts using the Python requests module to automate devices that have HTTP-based APIs Understand the role YANG plays in network automation Understand that a number of tools exist to simplify working with YANG models Describe the functionality of RESTCONF and NETCONF and the differences between them Construct Ansible playbooks to configure network devices and retrieve operational state data from them Build Jinja2 templates and YAML data structures to generate desired state configurations The Introducing Automation for Cisco Solutions (CSAU) v1.1 course gives you a broad overview of network automation skills. Through a combination of lecture and hands-on labs, you will learn the fundamentals of automation such as working on model-driven programmability solutions with Representational State Transfer Configuration Protocol (RESTCONF) and Network Configuration Protocol (NETCONF) protocols. The course also covers data formats and types, including Extensible Markup Language (XML), JavaScript Object Notation (JSON), Yaml Ain?t Markup Language (YAML), and Yet Another Next Generation (YANG), and their value in network automation, along with DevOps tools such as Ansible and Git. Course Outline Examining Network Management and Operations Exploring Software Development Methodologies Using Python for Network Automation Describing NetDevOps: DevOps for Networking Managing Automation Development Environments Introducing HTTP Network APIs Reviewing Data Formats and Data Encoding Using Python Requests to Automate HTTP-Based APIs Exploring YANG Using YANG Tools Automating Model-Driven APIs with Python Introducing Ansible for Network Automation Templating Configurations with Jinja2

Duration 0.5 Days 3 CPD hours This course is intended for This course is designed for business leaders and decision makers, including C-level executives, project managers, HR leaders, Marketing and Sales leaders, and technical sales consultants, who want to increase their knowledge of and familiarity with concepts surrounding data science. Other individuals who want to know more about basic data science concepts are also candidates for this course. This course is also designed to assist learners in preparing for the CertNexus DSBIZ™ (Exam DSZ-110) credential. Overview In this course, you will identify how data science supports business decisions. You will: Explain the fundamentals of data science Describe common implementations of data science. Identify the impact data science can have on a business The ability to identify and respond to changing trends is a hallmark of a successful business. Whether those trends are related to customers and sales or to regulatory and industry standards, businesses are wise to keep track of the variables that can affect the bottom line. In today's business landscape, data comes from numerous sources and in diverse forms. By leveraging data science concepts and technologies, businesses can mold all of that raw data into information that facilitates decisions to improve and expand the success of the business. Data Science Fundamentals What is Data Science? Types of Data Data Science Roles Data Science Implementation The Data Science Lifecycle Data Acquisition and Preparation Data Modeling and Visualization The Impact of Data Science Benefits of Data Science Challenges of Data Science Business Use Cases for Data Science Additional course details: Nexus Humans CertNexus Data Science for Business Professionals (DSBIZ) 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 CertNexus Data Science for Business Professionals (DSBIZ) 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 intended for: Solutions architects Developers Cost-optimization leads System administrators Overview In this course, you will learn to: Explain the cost of core AWS services Determine and predict costs associated with current and future cloud workloads Use strategies and best practices to reduce AWS costs Use AWS tools to manage, monitor, alert, and optimize your AWS spend Apply strategies to monitor service costs and usage Implement governance standards, including resource tagging, account structure, provisioning,permissions, and access This course is for individuals who seek an understanding of how to manage, optimize, and predict costs as you run workloads on AWS. You learn how to implement architectural best practices, explore cost optimization strategies, and design patterns to help you architect cost-efficient solutions on AWS. Module 0: Couse Overview Course introduction Module 1: Introduction to Cloud Financial Management Introduction to Cloud Financial Management Four pillars of Cloud Financial Management Module 2: Resource Tagging Tagging resources Hands-On Lab: Cost optimization: Control Resource Consumption Using Tagging and AWS Config Module 3: Pricing and Cost Fundamentals of pricing AWS Free Tier Volume discounts Savings plans and Reserved Instances Demonstration: AWS Pricing Calculator Module 4: AWS Billing, Reporting, and Monitoring Understanding AWS invoices Reporting and planning AWS Cost Explorer AWS Budgets Demonstration: AWS Billing Console Demonstration: AWS Cost Explorer Demonstration: Trusted Advisor Hands-On Lab: Cost optimization: Deploy Ephemeral Environments Using Amazon EC2 Auto Scaling Module 5: Architecting for Cost: Compute Evolution of compute efficiency Amazon EC2 right-sizing Purchasing options Architect for Amazon EC2 Spot Instance Impact of software licensing Demonstration: Compute Optimizer Demonstration: Spot Instance Advisor Hands-On Lab: Cost optimization: Right Size Amazon EC2 Instances Using Amazon CloudWatch Metrics Module 6: Architecting for Cost: Networking Data transfer costs Understand data costs for different services How to triage network costs Hands-On Lab: Cost optimization: Reduce Data Transfer Costs Using Amazon CloudFront and Endpoints Module 7: Architecting for Cost: Storage Amazon EBS cost, pricing, and best practices Amazon S3 cost, pricing, and best practices Amazon EFS cost, pricing, and best practices Hands-On Lab: Cost optimization: Reduce Storage Costs Using Amazon S3 Lifecycle Management Module 8: Architecting for Cost: Databases Amazon RDS cost, pricing, and best practices Amazon Aurora cost, pricing, and best practices Amazon DynamoDB cost, pricing, and best practices Amazon ElastiCache cost, pricing, and best practices Amazon Redshift cost, pricing, and best practices Module 9: Cost Governance Setting up AWS Organizations AWS Systems Manager Hands-On Lab: Cost optimization: Reduce Compute Costs Using AWS Instance Scheduler Module 10: Course Summary Course review

Duration 2 Days 12 CPD hours This course is intended for This course is intended for Sales Representatives (SR), Sales Managers and End-users who have an interest in the Sales components of Dynamics 365. Students should have an existing working knowledge of either Microsoft Dynamics 365 or Microsoft Dynamics CRM. As a minimum, students should attend the prerequisite course Introduction to Microsoft Dynamics 365 Overview Understand the features and tools that exist in Microsoft Dynamics 365 for SR?s and Sales Managers. Be familiar with the stages of the Sales Order. Process in Microsoft Dynamics 365. Understand the fundamentals of Lead and Opportunity Management. Be able to track, manage, qualify Leads and convert to Opportunities and related customer records in Microsoft Dynamics 365. Know how to disqualify and cancel Leads, and convert Activity records to Leads and Opportunities. Understand how to collaborate on Opportunities with other SR?s and close Opportunity records as Won and Lost. Be able to track Competitors and Stakeholders. Understand how to view Resolution Activities. Add Products and Write-In Products to Opportunities. Build and maintain a repository of Products, Product Bundles and Product Families in the Product Catalog. Configure Unit Groups, Price Lists and Discount Lists. Work with Product Properties and view a Product Hierarchy. Create Quotes and add Products. Work with the Sales Order Process to convert Quotes to Orders and Invoices. Fulfill Orders and manage Invoice payments. Explore the Sales Reports and create a custom Sales Report using the Reporting Wizard in Microsoft Dynamics 365. Understand the significance of Sales Goal Management and Metrics in Microsoft Dynamics 365. Explore the Sales Charts and Dashboards and create a custom Sales Dashboard in Microsoft Dynamics 365. This course provides students with a detailed hands-on experience of the Salesfeatures and components of Microsoft Dynamics 365. Introduction Sales Order Process Scenarios An Introduction to Sales in Dynamics 365 The Dynamics 365 Platform Dynamics 365 Sales Fundamentals Security Considerations Where to get Help Further Reading and Resources Lead Management The Lead Management Process Working with Lead Records Working with the Lead Form Lead Assignment Leads and Activities Qualifying a Lead Disqualifying a Lead Opportunities Management Introduction to Opportunities The Opportunity Views The Opportunity Form Opportunity Sales Process Closing an Opportunity Resolution Activities Products Introduction to the Product Catalog Adding Products Configuring Unit Groups Price Lists and Price List Items Quotes, Orders and Invoices Introduction to Order Processing Adding Products to an Opportunity Working with Quotes Working with Orders Working with Invoices Sales Analysis Introduction to Sales Analysis in Dynamics 365 The Sales Reports The Reporting Wizard Working with Sales Charts Working with Sales Dashboards Working with Sales Goals and Metrics

Duration 5 Days 30 CPD hours This course is intended for Linux Professional Institute Certification (LPIC-1) 102 training is suitable for individuals with roles of: System administrator Network administrator Technician DevOps Overview Upon successful completion of this course, students will be able to: customize shell environments to meet users' needs customize existing scripts or write simple new Bash scripts install and configure X11 add, remove, suspend and change user accounts use cron and systemd timers to run jobs at regular intervals and to use at to run jobs at a specific time localize a system in a different language than English properly maintain the system time and synchronize the clock via NTP manage print queues and user print jobs using CUPS and the LPD compatibility interface manage the persistent network configuration of a Linux host configure DNS on a client host review system configuration to ensure host security in accordance with local security policies know how to set up a basic level of host security use public key techniques to secure data and communication. This course prepares students to take the 102 exam of the LPI level 1 certification. Shells and Shell Scripting Customize and use the shell environment Customize or write simple scripts User Interfaces and Desktops Install and configure X11 Graphical Desktops Accessibility Administrative Tasks Manage user and group accounts and related system files Automate system administration tasks by scheduling jobs Localisation and internationalisation Essential System Services Maintain system time System logging Mail Transfer Agent (MTA) basics Manage printers and printing Networking Fundamentals Fundamentals of internet protocols Persistent network configuration Basic network troubleshooting Configure client side DNS Security Perform security administration tasks Setup host security Securing data with encryption Additional course details: Nexus Humans Linux Professional Institute Certification (LPIC-1) 102 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 Linux Professional Institute Certification (LPIC-1) 102 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 System Administrator System Architect Technology Consultant Overview This course will prepare you to: start and stop SAP systems perform system configuration tasks describe the architecture of database systems explain fundamental user administration concepts create RFC destinations implement SAP notes and SAP Support Packages configure printers in SAP systems schedule and monitor background jobs In this five-day training, you will learn how to perform various administrative tasks to keep the SAP system running. This course provides you with fundamental knowledge on how to ensure a smooth operation of SAP systems running on Application Server ABAP (AS ABAP). AS ABAP is the technological foundation of SAP Business Suite as well as SAP S/4HANA systems. You will also learn the theoretical administration concepts within AS ABAP and work practically in an SAP system and on the operating system level. Course Content AS ABAP Fundamentals Starting and Stopping SAP Systems Technical System Configuration Setting profile parameters Setting up and working with operation modes Working with task lists Architecture of database systems Understanding basic database administration Fundamentals of User Administration Understanding the user administration concept Understanding the AS ABAP authorization concept RFC Communication Setting up RFC connections Software Maintenance Implementing SAP Notes and SAP Support Packages Preparing a software maintenance process Working with the Support Package Manager (SPAM) Understanding the Software Update Manager (SUM) Output Management Configuring printers Background Processing Scheduling background jobs System Monitoring and Troubleshooting Monitoring architecture Monitoring with SAP Solution Manager Additional course details: Nexus Humans ADM100 System Administration I of SAP S/4HANA and SAP Business Suite 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 ADM100 System Administration I of SAP S/4HANA and SAP Business Suite 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 4 Days 24 CPD hours This course is intended for This course is designed for data analysts, business intelligence specialists, developers, system architects, and database administrators. Overview Skills gained in this training include:The features that Pig, Hive, and Impala offer for data acquisition, storage, and analysisThe fundamentals of Apache Hadoop and data ETL (extract, transform, load), ingestion, and processing with HadoopHow Pig, Hive, and Impala improve productivity for typical analysis tasksJoining diverse datasets to gain valuable business insightPerforming real-time, complex queries on datasets Cloudera University?s four-day data analyst training course focusing on Apache Pig and Hive and Cloudera Impala will teach you to apply traditional data analytics and business intelligence skills to big data. Hadoop Fundamentals The Motivation for Hadoop Hadoop Overview Data Storage: HDFS Distributed Data Processing: YARN, MapReduce, and Spark Data Processing and Analysis: Pig, Hive, and Impala Data Integration: Sqoop Other Hadoop Data Tools Exercise Scenarios Explanation Introduction to Pig What Is Pig? Pig?s Features Pig Use Cases Interacting with Pig Basic Data Analysis with Pig Pig Latin Syntax Loading Data Simple Data Types Field Definitions Data Output Viewing the Schema Filtering and Sorting Data Commonly-Used Functions Processing Complex Data with Pig Storage Formats Complex/Nested Data Types Grouping Built-In Functions for Complex Data Iterating Grouped Data Multi-Dataset Operations with Pig Techniques for Combining Data Sets Joining Data Sets in Pig Set Operations Splitting Data Sets Pig Troubleshoot & Optimization Troubleshooting Pig Logging Using Hadoop?s Web UI Data Sampling and Debugging Performance Overview Understanding the Execution Plan Tips for Improving the Performance of Your Pig Jobs Introduction to Hive & Impala What Is Hive? What Is Impala? Schema and Data Storage Comparing Hive to Traditional Databases Hive Use Cases Querying with Hive & Impala Databases and Tables Basic Hive and Impala Query Language Syntax Data Types Differences Between Hive and Impala Query Syntax Using Hue to Execute Queries Using the Impala Shell Data Management Data Storage Creating Databases and Tables Loading Data Altering Databases and Tables Simplifying Queries with Views Storing Query Results Data Storage & Performance Partitioning Tables Choosing a File Format Managing Metadata Controlling Access to Data Relational Data Analysis with Hive & Impala Joining Datasets Common Built-In Functions Aggregation and Windowing Working with Impala How Impala Executes Queries Extending Impala with User-Defined Functions Improving Impala Performance Analyzing Text and Complex Data with Hive Complex Values in Hive Using Regular Expressions in Hive Sentiment Analysis and N-Grams Conclusion Hive Optimization Understanding Query Performance Controlling Job Execution Plan Bucketing Indexing Data Extending Hive SerDes Data Transformation with Custom Scripts User-Defined Functions Parameterized Queries Choosing the Best Tool for the Job Comparing MapReduce, Pig, Hive, Impala, and Relational Databases Which to Choose?

Duration 5 Days 30 CPD hours This course is intended for This course is intended for: Solutions architects and cloud architects seeking their AWS Certified Solutions Architect - Associate certification Customers and APN Partners who have 6 to 12 months of experience with AWS including a strong architecture background and experience Individuals who prefer an instructor led course for training and exam readiness Individuals who have not taken the Architecting on AWS course in the last ~6 months Overview In this course, you will learn to: Make architectural decisions based on AWS architectural principles and best practices Leverage AWS services to make your infrastructure scalable, reliable, and highly available Leverage AWS Managed Services to enable greater flexibility and resiliency in an infrastructure Make an AWS-based infrastructure more efficient to increase performance and reduce costs Use the Well-Architected Framework to improve architectures with AWS solutions Navigate the logistics of the examination process, exam structure, and question types Identify how questions relate to AWS architectural concepts Interpret the concepts being tested by an exam question This five-day, instructor-led course helps busy architects get away from the day-to-day to get focused and ready for their AWS Certified Solutions Architect ? Associate exam. Attendees learn the fundamentals of building IT infrastructure on AWS, so they can build scalable and resilient solutions in the cloud, by spending the first 3 days on the Architecting on AWS course. They?ll start getting in the exam readiness mindset with bonus end of module quizzes. Next, they?ll learn strategies to answer exam questions and avoid common mistakes with the Exam Readiness: AWS Certified Solutions Architect ? Associate half-day course. The course broadens attendees? knowledge of AWS services with deep dives into Amazon Redshift, Amazon Kinesis, and AWS Key Management Service, and then concludes with two quizzes and an instructor guided review of the AWS Certified Solutions Architect ? Associate practice exam. Architecting on AWS Module 1: Introduction Module 2: The Simplest Architectures Hands-On Lab 1: Hosting a Static Website Module 3: Adding a Compute Layer Module 4: Adding a Database Layer Hands-On Lab 2: Deploying a Web Application on AWS Module 5: Networking in AWS Part 1 Hands-On Lab 3: Creating a Virtual Private Cloud Architecting on AWS (continued) Module 6: Networking in AWS Part 2 Module 7: AWS Identity and Access Management (IAM) Module 8: Elasticity, High Availability, and Monitoring Hands-On Lab 4: Creating a Highly Available Environment Module 9: Automation Hands-On Lab 5: Automating Infrastructure Deployment with AWS CloudFormation Module 10: Caching Architecting on AWS (continued) Module 11: Building Decoupled Architectures Module 12: Microservices and Serverless Architectures Hands-On Lab 6: Implementing a Serverless Architecture with AWS Managed Services Module 13: RTP/RPO and Backup Recovery Setup Module 14: Optimizations and Review Exam Readiness: AWS Certified Solutions Architect -- Associate Module 0: The Exam Module 1: Design Resilient Architectures Module 2: Design Performant Architectures Module 3: Specify Secure Applications and Architectures Module 4: Design Cost-Optimized Architectures Module 5: Define Operationally Excellent Architectures Exam Readiness Additional deep dive of AWS services Quiz #1 Practice exam: AWS Certified Solutions Architect ? Associate Quiz #2 Wrap-up

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