666 Courses

Duration 1 Days 6 CPD hours This course is intended for This course is intended for data warehouse engineers, data platform engineers, and architects and operators who build and manage data analytics pipelines. Completed either AWS Technical Essentials or Architecting on AWS Completed Building Data Lakes on AWS Overview In this course, you will learn to: Compare the features and benefits of data warehouses, data lakes, and modern data architectures Design and implement a data warehouse analytics solution Identify and apply appropriate techniques, including compression, to optimize data storage Select and deploy appropriate options to ingest, transform, and store data Choose the appropriate instance and node types, clusters, auto scaling, and network topology for a particular business use case Understand how data storage and processing affect the analysis and visualization mechanisms needed to gain actionable business insights Secure data at rest and in transit Monitor analytics workloads to identify and remediate problems Apply cost management best practices In this course, you will build a data analytics solution using Amazon Redshift, a cloud data warehouse service. The course focuses on the data collection, ingestion, cataloging, storage, and processing components of the analytics pipeline. You will learn to integrate Amazon Redshift with a data lake to support both analytics and machine learning workloads. You will also learn to apply security, performance, and cost management best practices to the operation of Amazon Redshift. Module A: Overview of Data Analytics and the Data Pipeline Data analytics use cases Using the data pipeline for analytics Module 1: Using Amazon Redshift in the Data Analytics Pipeline Why Amazon Redshift for data warehousing? Overview of Amazon Redshift Module 2: Introduction to Amazon Redshift Amazon Redshift architecture Interactive Demo 1: Touring the Amazon Redshift console Amazon Redshift features Practice Lab 1: Load and query data in an Amazon Redshift cluster Module 3: Ingestion and Storage Ingestion Interactive Demo 2: Connecting your Amazon Redshift cluster using a Jupyter notebook with Data API Data distribution and storage Interactive Demo 3: Analyzing semi-structured data using the SUPER data type Querying data in Amazon Redshift Practice Lab 2: Data analytics using Amazon Redshift Spectrum Module 4: Processing and Optimizing Data Data transformation Advanced querying Practice Lab 3: Data transformation and querying in Amazon Redshift Resource management Interactive Demo 4: Applying mixed workload management on Amazon Redshift Automation and optimization Interactive demo 5: Amazon Redshift cluster resizing from the dc2.large to ra3.xlplus cluster Module 5: Security and Monitoring of Amazon Redshift Clusters Securing the Amazon Redshift cluster Monitoring and troubleshooting Amazon Redshift clusters Module 6: Designing Data Warehouse Analytics Solutions Data warehouse use case review Activity: Designing a data warehouse analytics workflow Module B: Developing Modern Data Architectures on AWS Modern data architectures

Duration 3 Days 18 CPD hours This course is intended for The Foundation course is designed for individuals who want to gain an overview of Business Analysis (Business Analysts, Requirements Engineers, Product manager, Product Owner, Chief Product Owner, Service Manager, Service Owner, Project manager, Consultants) Overview Students should be able to demonstrate knowledge and understanding of business analysis principles and techniques. Key areas are: the role and competencies of a business analyst strategy analysis business system and business process modelling stakeholder analysis investigation and modelling techniques requirements engineering business case development The business analyst role analyzes, understands and manages the requirements in a customer-supplier relationship and ensures that the right products are delivered. The Foundation Seminar gives a good introduction to the spectrum of this responsibility. Course Introduction Let?s Get to Know Each Other Course Overview Course Learning Objectives Course Structure Course Agenda Introduction to Business Analysis Structure and Benefits of Business Analysis Foundation Exam Details Business Analysis Certification Scheme What is Business Analysis? Intent and Context Origins of business analysis The development of business analysis The scope of business analysis work Taking a holistic approach The role and responsibilities of the business analyst The competencies of a Business Analyst Personal qualities Business knowledge Professional techniques The development of competencies Strategy Analysis The context for strategy The defiition of strategy Strategy development External environmental analysis Internal invironmental analysis SWOT analysis Executing strategy Business Analysis Process Model An approach to problem solving Stages of the business analysis process model Objectives of the process model stages Procedures for each process model stage Techniques used within each process model stage Investigation Techniques Interviews Observation Workshops Scenarios Prototyping Quantitative approaches Documenting the current situation Stakeholder Analysis and Management Stakeholder categories and identification Analysing stakeholders Stakeholder management strategies Managing stakeholders Understanding stakeholder perspectives Business activity models Modelling Business Processes Organizational context An altrnative view of an organization The organizational view of business processes Value propositions Process models Analysing the as-is process model Improving business processes (to-be business process) Defining the Solution Gab analysis Introduction to Business Architecture Definition to Business Architecture Business Architecture techniques Business and Financial Case The business case in the project lifecycle Identifying options Assessing project feasibility Structure of a business case Investment appraisal Establishing the Requirements A framework for requirements engineering Actors in requirements engineering Requirements elicitation Requirements analysis Requirements validation Documenting and Managing the Requirements The requirements document The requirements catalogue Managing requirements Modelling the Requirements Modelling system functions Modelling system data Delivering the Requirements Delivering the solution Context Lifecycles Delivering the Business Solution BA role in the business change lifecycle Design stage Implementation stage Realization stage

Duration 1 Days 6 CPD hours This course is intended for This course is intended for business users and knowledge workers in a variety of roles and fields who have competence in a desktop-based installation of the Microsoft Office 2010 or 2013 edition of the Microsoft Office productivity suite, and who are now extending Microsoft Office to a collaborative cloud-based Office 365 environment. Overview In this course, you will build upon your knowledge of the Microsoft Office desktop application suite to work productively in the cloud-based Microsoft Office 365 environment.You will:- Sign in, navigate, and identify components of the Office 365 environment.- Create, edit, and share documents with team members using Word Online, Excel Online, PowerPoint Online, and Microsoft SharePoint.- Collaborate and work with colleagues using the Team, Planner, and Yammer apps.- Use email and manage contacts with Outlook on the web.- Use instant messaging with Skype for Business.- Conduct online meetings with Skype for Business. This course is an introduction to Microsoft© Office 365© with Skype© for Business in a cloud-based environment. It can be used as an orientation to the full suite of Office 365 cloud-based tools, or the Skype for Business lessons can be presented separately in a seminar-length presentation with the remaining material available for later student reference. Getting Started Sign In to Office 365 Navigate the Office 365 Environment Collaborating with Shared Files Work with Shared Documents in SharePoint Edit Documents in Office Online Collaborate on the SharePoint Site Work with OneDrive for Business and Delve Using Productivity Apps Work with Productivity Apps in Combination Broadcast Messages with Yammer Collaborate with the Teams App Manage Tasks with the Planner App Using Outlook on the Web Send and Receive Email Manage Contacts Schedule Appointments Personalize Outlook on the Web Communicating with Skype for Business Overview of Skype for Business Use Instant Messaging Make Voice and Video Calls Using Skype for Business Meetings Initiate Meetings Use Meeting Controls and Options Customize Skype for Business Additional course details: Nexus Humans Office 365 Web Apps (with Skype for Business) 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 Office 365 Web Apps (with Skype for Business) 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 2 Days 12 CPD hours This course is intended for This Introductory-level course is targeted for aspiring web developers who have software development experience or background. The course can also be adjusted for non-developers upon request. Overview This 'skills-focused' course is approximately 50% hands-on, combining expert lecture, real-world demonstrations and group discussions with machine-based practical labs and exercises. Our instructors are highly experienced practitioners who bring years of current 'on-the-job' experience into every classroom. Introduction to HTML5/ CSS3 and Responsive Design Basics is a hands-on basic web development course geared for developers who need to understand what the latest in web technologies and responsive design practices that are central to targeting the entire spectrum of user platforms and browsers. This comprehensive course provides a balanced mixture of theory and practical labs designed to take students through HTML5 and CSS3. Students who attend this course will leave this course armed with the new skills to design, implement, and deploy robust, flexible, and safe web applications. HTML Define HTML and review its history Look at XHTML and its relationship to HTML Identify HTML limitations and improvements HTML5 HTML5 Overview HTML5 Semantic Structure HTML5 Forms HTML5 Media Delivery CSS Learn the basics of CSS Meaning of cascading in CSS Declaring CSS within your HTML page Creating styles in an external CSS file Control how to display and position HTML elements Overriding standard tag behavior Adding new classes Using custom classes in your page CSS3 Overview What is new in CSS3 The Advantages of CSS3 Browser Support for CSS3 CSS3 Advanced Selectors Selecting Using Attributes Selecting Using DOM Structure Complex Selecting using Pseudo-Classes Selecting Using UI Components and State CSS3 Visual Effects Font Options, Opacity, and Color Distributing Content Across Columns Working with Borders and Boxes Working with Vendor Prefixes Functional Techniques HTML5 JavaScript API Cross-Domain Messaging Working with Web Storage Offline with Application Cache Geolocation: What, Why, and How Responsive Web Design (RWD) Adapting to Varying Screen Sizes Scaling Page and Text Content Scaling and Adapting for Media Options for Adjusting Media Additional course details: Nexus Humans Web Essentials | Introduction to HTML5, CSS3 and Responsive Design (TT4002) 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 Web Essentials | Introduction to HTML5, CSS3 and Responsive Design (TT4002) 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 2 Days 12 CPD hours This course is intended for Participants who have actual experience in the data centre and/or IT infrastructures are best suited. Attendance of the CDCP© course is recommended but not a requirement. Overview After completion of the course the participant will be able to: 1. Develop and review their data centre strategy 2. Use different risk assessment methodologies together with practical tips specifically for data centre migrations to reduce the risk during a data centre migration 3. Understand different migration strategies 4. Understand the legal aspects when migrating a data centre 5. Understand the importance of Business Service Reviews and Service Level Objectives 6. Size and design the target data centre 7. Understand the importance of detailed discovery and how dependencies influence migration waves 8. Understand the safety requirements during migration 19. Get lots of practical tips when moving to another data centre This course is designed to expose participants to a step-by-step methodology which will enable them to reduce the risks involved when undertaking a data centre migration. It will also give participants a lot of valuable practical hints and tips by trainers having extensive experience in moving and consolidating mission critical data centre. Data Centre Strategy Data centre lifecycle Reasons to migrate a data centre Alternatives to data centre migration Consolidation Outsourcing Cloud computing Upgrade existing data centre or build new Project Management Project management and methods Scope statement Statement Of Work (SOW) Work Breakdown Structure (WBS) Allocate time to the project Cost and estimation methodology Project communication Risk Management Risk management and methods Risk identification Risk assessment methodologies Qualitative approach Semi-quantitative approach Quantitative approach Risk evaluation Risk treatment Risk in data centre migrations Migration Strategies Different data centre migration strategies Heterogeneous migration Homogeneous migration Physical migration Different IT transformations Pre-migration transformation Migration transformation Post-migration transformation Legal Aspects Regulatory requirements Contractual considerations Legal aspects when decommissioning High Level Discovery & Planning The importance of Business Service Reviews The concept of Availability The concept of Recoverability The importance of Service Level Objectives Requirements on designing the target IT architecture Information needed for high level planning Design Target Data Centre Requirements for the target data centre Sizing the data centre Architectural requirements Cooling requirements Power requirements Security Detailed Discovery and Planning The importance of discovery Automated discovery tools Asset management Network and system dependencies Detailed migration planning Migration waves Staffing Warranties and insurance Safety Safety precautions Technical safety review Electrical safety Lifting Personal safety during migration Fire safety during migration Security Controversy between access and security Access control Managing security during migration Security during migration Key management Practical hints and tips Continuous improvement Implementation Rehearsal Route investigation Resourcing Logistics team Packing Transport Installing the equipment Post migration support End of Project Why project closure Lessons learned Phased completion of project Criteria for project closure The outcome of the project End of project Exam: Certified Data Centre Migration Specialist Actual course outline may vary depending on offering center. Contact your sales representative for more information.

Duration 2 Days 12 CPD hours This course is intended for This is an intermediate level training course, designed for experienced Java developers and architects who need to identify, design, and implement web services. We will explore and apply the terminology, the specification, the processes and technologies specific to web services. Students should have at least a year of practical development experience with Java and servlets, and should be familiar with XML and JSON. Overview This 'skills-centric' course is about 50% hands-on lab and 50% lecture, designed to train attendees in core RESTful development skills, coupling the most current, effective techniques with the soundest industry practices. Working within in a hands-on learning environment, guided by our expert team, attendees will learn to: Understand and apply the basic concepts of REST Understand and intelligently discuss the similarities and differences between RESTful services and SOAP-based services Appreciate the security concerns associated with RESTful services Design, develop, and deploy real-world RESTful Services Effectively define and design endpoints Work with query parameters Determine the best format to use for exchanging data Understand the principles associated with HTTP methods and how to stay congruent to them Extend the semantics of the RESTful service beyond the HTTP methods Implement RESTful services using JAX-RS to Handle various HTTP methods Use different approaches for parameters Deal with content negotiation Work with different data formats including XML and JSON Handle exceptions Implement RESTful Java clients Develop JAX-RS Java clients using the JAX-RS 2.0 Client API Manage different Web targets Deal with content negotiation on the client Work with different data formats including XML and JSON Properly process server responses Implement JAX-RS Filters and Interceptors Intercept and manipulate service requests and responses Dynamically register interceptor to resources Understand the concept of NameBinding Discover asynchronous JAX-RS processing Implement an asynchronous JAX-RS service endpoint Register response listeners Geared for experienced Java developers, Java REST Essentials is a two day, lab-intensive services training course that introduces developers to the core concepts, principles, and Java implementations for RESTful services. Today's development environments are increasingly dominated by sophisticated tooling that makes the implementation of RESTful services less arduous. The proper design of these services is far more complex and demanding. Java RESTful Service Essentials focuses on providing an understanding of the fundamental principles and technologies that are used in building these services. This understanding is critical to being able to diagnose, troubleshoot, tune, and perform other lifecycle activities. Session: Working with REST Overview of REST Designing RESTful Services JAX-RS Lesson: Introduction to JAX-RS @Path: URI Matching JAX-RS Content Negotiation JAX-RS Request and Response JAX-RS Client API JAX-RS Filters and Interceptors Asynchronous JAX-RS Additional course details: Nexus Humans Java REST Essentials (TT7305) 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 Java REST Essentials (TT7305) 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 geared for attendees with Intermediate IT skills who wish to learn Computer Vision with tensor flow 2 Overview This 'skills-centric' course is about 50% hands-on lab and 50% lecture, with extensive practical exercises designed to reinforce fundamental skills, concepts and best practices taught throughout the course. Working in a hands-on learning environment, led by our Computer Vision expert instructor, students will learn about and explore how to Build, train, and serve your own deep neural networks with TensorFlow 2 and Keras Apply modern solutions to a wide range of applications such as object detection and video analysis Run your models on mobile devices and web pages and improve their performance. Create your own neural networks from scratch Classify images with modern architectures including Inception and ResNet Detect and segment objects in images with YOLO, Mask R-CNN, and U-Net Tackle problems faced when developing self-driving cars and facial emotion recognition systems Boost your application's performance with transfer learning, GANs, and domain adaptation Use recurrent neural networks (RNNs) for video analysis Optimize and deploy your networks on mobile devices and in the browser Computer vision solutions are becoming increasingly common, making their way into fields such as health, automobile, social media, and robotics. Hands-On Computervision with TensorFlow 2 is a hands-on course that thoroughly explores TensorFlow 2, the brandnew version of Google's open source framework for machine learning. You will understand how to benefit from using convolutional neural networks (CNNs) for visual tasks. This course begins with the fundamentals of computer vision and deep learning, teaching you how to build a neural network from scratch. You will discover the features that have made TensorFlow the most widely used AI library, along with its intuitive Keras interface. You'll then move on to building, training, and deploying CNNs efficiently. Complete with concrete code examples, the course demonstrates how to classify images with modern solutions, such as Inception and ResNet, and extract specific content using You Only Look Once (YOLO), Mask R-CNN, and U-Net. You will also build generative dversarial networks (GANs) and variational autoencoders (VAEs) to create and edit images, and long short-term memory networks (LSTMs) to analyze videos. In the process, you will acquire advanced insights into transfer learning, data augmentation, domain adaptation, and mobile and web deployment, among other key concepts Computer Vision and Neural Networks Computer Vision and Neural Networks Technical requirements Computer vision in the wild A brief history of computer vision Getting started with neural networks TensorFlow Basics and Training a Model TensorFlow Basics and Training a Model Technical requirements Getting started with TensorFlow 2 and Keras TensorFlow 2 and Keras in detail The TensorFlow ecosystem Modern Neural Networks Modern Neural Networks Technical requirements Discovering convolutional neural networks Refining the training process Influential Classification Tools Influential Classification Tools Technical requirements Understanding advanced CNN architectures Leveraging transfer learning Object Detection Models Object Detection Models Technical requirements Introducing object detection A fast object detection algorithm YOLO Faster R-CNN ? a powerful object detection model Enhancing and Segmenting Images Enhancing and Segmenting Images Technical requirements Transforming images with encoders-decoders Understanding semantic segmentation Training on Complex and Scarce Datasets Training on Complex and Scarce Datasets Technical requirements Efficient data serving How to deal with data scarcity Video and Recurrent Neural Networks Video and Recurrent Neural Networks Technical requirements Introducing RNNs Classifying videos Optimizing Models and Deploying on Mobile Devices Optimizing Models and Deploying on Mobile Devices Technical requirements Optimizing computational and disk footprints On-device machine learning Example app ? recognizing facial expressions

Duration 4 Days 24 CPD hours This course is intended for This course is geared for attendees with Intermediate IT skills who wish to learn Computer Vision with tensor flow 2 Overview This 'skills-centric' course is about 50% hands-on lab and 50% lecture, with extensive practical exercises designed to reinforce fundamental skills, concepts and best practices taught throughout the course. Working in a hands-on learning environment, led by our Computer Vision expert instructor, students will learn about and explore how to Build, train, and serve your own deep neural networks with TensorFlow 2 and Keras Apply modern solutions to a wide range of applications such as object detection and video analysis Run your models on mobile devices and web pages and improve their performance. Create your own neural networks from scratch Classify images with modern architectures including Inception and ResNet Detect and segment objects in images with YOLO, Mask R-CNN, and U-Net Tackle problems faced when developing self-driving cars and facial emotion recognition systems Boost your application's performance with transfer learning, GANs, and domain adaptation Use recurrent neural networks (RNNs) for video analysis Optimize and deploy your networks on mobile devices and in the browser Computer vision solutions are becoming increasingly common, making their way into fields such as health, automobile, social media, and robotics. Hands-On Computervision with TensorFlow 2 is a hands-on course that thoroughly explores TensorFlow 2, the brand-new version of Google's open source framework for machine learning. You will understand how to benefit from using convolutional neural networks (CNNs) for visual tasks. This course begins with the fundamentals of computer vision and deep learning, teaching you how to build a neural network from scratch. You will discover the features that have made TensorFlow the most widely used AI library, along with its intuitive Keras interface. You'll then move on to building, training, and deploying CNNs efficiently. Complete with concrete code examples, the course demonstrates how to classify images with modern solutions, such as Inception and ResNet, and extract specific content using You Only Look Once (YOLO), Mask R-CNN, and U-Net. You will also build generative adversarial networks (GANs) and variational autoencoders (VAEs) to create and edit images, and long short-term memory networks (LSTMs) to analyze videos. In the process, you will acquire advanced insights into transfer learning, data augmentation, domain adaptation, and mobile and web deployment, among other key concepts. Computer Vision and Neural Networks Computer Vision and Neural Networks Technical requirements Computer vision in the wild A brief history of computer vision Getting started with neural networks TensorFlow Basics and Training a Model TensorFlow Basics and Training a Model Technical requirements Getting started with TensorFlow 2 and Keras TensorFlow 2 and Keras in detail The TensorFlow ecosystem Modern Neural Networks Modern Neural Networks Technical requirements Discovering convolutional neural networks Refining the training process Influential Classification Tools Influential Classification Tools Technical requirements Understanding advanced CNN architectures Leveraging transfer learning Object Detection Models Object Detection Models Technical requirements Introducing object detection A fast object detection algorithm ? YOLO Faster R-CNN ? a powerful object detection model Enhancing and Segmenting Images Enhancing and Segmenting Images Technical requirements Transforming images with encoders-decoders Understanding semantic segmentation Training on Complex and Scarce Datasets Training on Complex and Scarce Datasets Technical requirements Efficient data serving How to deal with data scarcity Video and Recurrent Neural Networks Video and Recurrent Neural Networks Technical requirements Introducing RNNs Classifying videos Optimizing Models and Deploying on Mobile Devices Optimizing Models and Deploying on Mobile Devices Technical requirements Optimizing computational and disk footprints On-device machine learning Example app ? recognizing facial expressions

Duration 5 Days 30 CPD hours This course is intended for This intermediate-level course requires students have incoming experience working with Oracle Database 18 or higher. Overview Working in a hands-on learning environment led by our expert facilitator, you'll explore: The Oracle Database Architecture Query Optimizer Tuning Container Databases and Pluggable Databases Oracle 19c Tuning features Evaluating Execution Plans Oracle Tuning Tools Using Automatic Workload Repository Join Types AWR Using Baselines Additional AWR performance tools Optimizer Statistics Monitoring a Service Bind Variables and database parameters Oracle's Real Application Testing (RAT) SQL Tuning Advisor Automatic Sql Tuning Sql Plan Management Shared Pool Tuning Tuning the database buffer cache Tuning the PGA (Program Global Area) Automatic Memory Management (AMM) Tuning Segment Space Utilization (ASSM) Automatic Storage Management Oracle 19C Database Tuning is an intermediate level course for Oracle database experienced attendees that explores core tuning skills such as Database parameters, SQL Tuning Advisor, SQL Access Advisor, Adaptive SQL plans and more. Overview Oracle Database Architecture Instance Definition Define SGA Define Background Processes Datafile Definition Query Optimizer SQL Parsing Optimizing Terms Optimizing Methods Query Plan Generation Query Plan Control Tuning Container Databases and Pluggable Databases Pluggable tuning parameters Define Container tuning structure Using PDB$SEED Create a new PDB Plug and unplug a PDB Oracle 12c Tuning features Identifying and Using Oracle's Heat Map 12c Compression Levels and Types Evaluating Execution Plans Defining SQL execution plans Automatic Workload Repository Reading execution plans Oracle Tuning Tools Monitoring tools overview Enterprise Manager Dynamic Performance Views Automatic Workload Repository Automatic Database Diagnostic Monitor Sql Tuning Advisor SQL Access Advisor Sql Access Advisor DB operation Tuning DB operation Active Reporting Using Automatic Workload Repository Defining AWR AWR Settings Creating AWR Baselines Metrics, Alerts, and Thresholds Defining Metrics Setting Alerts Setting Corrective Actions User Defined Metrics Metric Dynamic Views Join Types Nested Loops Join Sort Merge join Hash Join and Cartesian Join Equijoins and Nonequijoins Outer Joins Semijoins AWR Using Baselines Creating AWR baselines Creating AWR Repeating baselines Moving Window Baseline Additional AWR performance tools Automatic Maintenance Tasks Segment Advisor Statistics Gathering Automatic Tuning Optimizer Automatic Database Diagnostic Monitor Active Session History (ASH) Optimizer Statistics Optimizer Statistics Overview Table and Index Statistics Statistic Preferences Statistics Gathering e) Locking Statistics, Export/Import Statistics Pending and published statistics Optimizer Hints Optimizer Paths Cost Base Optimization Monitoring a Service Overview of what is an Oracle Service Creating an Oracle Service for Single instance and RAC Monitoring a Service Resource Management and a Service Enterprise Manager and a Service Bind Variables and database parameters Bind variable definition Cursor_sharing parameter Adaptive Cursor Sharing Oracle's Real Application Testing (RAT) Sql Performance Analyzer overview Sql Performance Analyzer Options Database Parameter changes Database version changes Creating SQL Tuning Sets Database Replay Overview Database Replay Configuration Database Replay Options SQL Tuning Advisor SQL Tuning Advisor: Overview SQL Tuning Advisor Limited Mode Sql Tuning Advisor Comprehensive mode Sql Tuning Profiles SQL Access Advisor SQL Access Advisor: Overview Sql Access Advisor options SQL Access Advisor and Sql Tuning Sets Sql Access Advisor and AWR Results and Implementation Automatic Sql Tuning Automatic Sql Tuning Maintenance Task Automatic Tuning Optimization implementation(ATO) Automatic Tuning Optimization Results Enable/Disable Automatic Tuning Optimization Sql Plan Management Sql plan Management and baseline overview Enable sql plan management Loading Sql Plan baselines into the SGA Adaptive plan management Shared Pool Tuning Shared pool architecture Shared pool parameters Library Cache Dictionary cache Large pool considerations and contents Tuning the database buffer cache Database buffer cache overview Database buffer cache parameters Oracle and Dirty reads and writes Automatic Shared Memory Management (ASMM) Buffer Cache goals and responsibility Buffer Cache pools Tuning the PGA (Program Global Area) PGA Overview PGA Database Parameters Temporary Segments Temporary Tablespace Sizing the PGA Automatic Memory Management (AMM) Oracle's Automatic Memory Management Overview Database Auto-tuned Parameters Database Non Auto-tuned Parameters Automatic Memory Management Hints and Sizing suggestions AMM versus ASMM Tuning Segment Space Utilization (ASSM) Overview of Automatic Segment Space Management Defining the DB_BLOCK_SIZE Defining DB_nk_CACHE_SIZE parameter The DB_BLOCK_SIZE Parameter Overview of table compression, block chaining, and block migration Automatic Storage Management Overview of ASM Definition of Grid Infrastructure ASM Instance ASM Diskgroups ASM Diskgroup parameters and templates ASMCMD

Duration 5 Days 30 CPD hours This course is intended for This intermediate and beyond level course is geared for experienced technical professionals in various roles, such as developers, data analysts, data engineers, software engineers, and machine learning engineers who want to leverage Scala and Spark to tackle complex data challenges and develop scalable, high-performance applications across diverse domains. Practical programming experience is required to participate in the hands-on labs. Overview Working in a hands-on learning environment led by our expert instructor you'll: Develop a basic understanding of Scala and Apache Spark fundamentals, enabling you to confidently create scalable and high-performance applications. Learn how to process large datasets efficiently, helping you handle complex data challenges and make data-driven decisions. Gain hands-on experience with real-time data streaming, allowing you to manage and analyze data as it flows into your applications. Acquire practical knowledge of machine learning algorithms using Spark MLlib, empowering you to create intelligent applications and uncover hidden insights. Master graph processing with GraphX, enabling you to analyze and visualize complex relationships in your data. Discover generative AI technologies using GPT with Spark and Scala, opening up new possibilities for automating content generation and enhancing data analysis. Embark on a journey to master the world of big data with our immersive course on Scala and Spark! Mastering Scala with Apache Spark for the Modern Data Enterprise is a five day hands on course designed to provide you with the essential skills and tools to tackle complex data projects using Scala programming language and Apache Spark, a high-performance data processing engine. Mastering these technologies will enable you to perform a wide range of tasks, from data wrangling and analytics to machine learning and artificial intelligence, across various industries and applications.Guided by our expert instructor, you?ll explore the fundamentals of Scala programming and Apache Spark while gaining valuable hands-on experience with Spark programming, RDDs, DataFrames, Spark SQL, and data sources. You?ll also explore Spark Streaming, performance optimization techniques, and the integration of popular external libraries, tools, and cloud platforms like AWS, Azure, and GCP. Machine learning enthusiasts will delve into Spark MLlib, covering basics of machine learning algorithms, data preparation, feature extraction, and various techniques such as regression, classification, clustering, and recommendation systems. Introduction to Scala Brief history and motivation Differences between Scala and Java Basic Scala syntax and constructs Scala's functional programming features Introduction to Apache Spark Overview and history Spark components and architecture Spark ecosystem Comparing Spark with other big data frameworks Basics of Spark Programming SparkContext and SparkSession Resilient Distributed Datasets (RDDs) Transformations and Actions Working with DataFrames Spark SQL and Data Sources Spark SQL library and its advantages Structured and semi-structured data sources Reading and writing data in various formats (CSV, JSON, Parquet, Avro, etc.) Data manipulation using SQL queries Basic RDD Operations Creating and manipulating RDDs Common transformations and actions on RDDs Working with key-value data Basic DataFrame and Dataset Operations Creating and manipulating DataFrames and Datasets Column operations and functions Filtering, sorting, and aggregating data Introduction to Spark Streaming Overview of Spark Streaming Discretized Stream (DStream) operations Windowed operations and stateful processing Performance Optimization Basics Best practices for efficient Spark code Broadcast variables and accumulators Monitoring Spark applications Integrating External Libraries and Tools, Spark Streaming Using popular external libraries, such as Hadoop and HBase Integrating with cloud platforms: AWS, Azure, GCP Connecting to data storage systems: HDFS, S3, Cassandra, etc. Introduction to Machine Learning Basics Overview of machine learning Supervised and unsupervised learning Common algorithms and use cases Introduction to Spark MLlib Overview of Spark MLlib MLlib's algorithms and utilities Data preparation and feature extraction Linear Regression and Classification Linear regression algorithm Logistic regression for classification Model evaluation and performance metrics Clustering Algorithms Overview of clustering algorithms K-means clustering Model evaluation and performance metrics Collaborative Filtering and Recommendation Systems Overview of recommendation systems Collaborative filtering techniques Implementing recommendations with Spark MLlib Introduction to Graph Processing Overview of graph processing Use cases and applications of graph processing Graph representations and operations Introduction to Spark GraphX Overview of GraphX Creating and transforming graphs Graph algorithms in GraphX Big Data Innovation! Using GPT and Generative AI Technologies with Spark and Scala Overview of generative AI technologies Integrating GPT with Spark and Scala Practical applications and use cases Bonus Topics / Time Permitting Introduction to Spark NLP Overview of Spark NLP Preprocessing text data Text classification and sentiment analysis Putting It All Together Work on a capstone project that integrates multiple aspects of the course, including data processing, machine learning, graph processing, and generative AI technologies.