3996 Analyst courses

Duration 3 Days 18 CPD hours This course is intended for This is an introductory- level course appropriate for those who are developing applications using relational databases, or who are using SQL to extract and analyze data from databases and need to use the full power of SQL queries. Overview This course combines expert lecture, real-world demonstrations and group discussions with machine-based practical labs and exercises. Working in a hands-on learning environment led by our expert practitioner, attendees will learn to: Maximize the potential of SQL to build powerful, complex and robust SQL queries Query multiple tables with inner joins, outer joins and self joins Construct recursive common table expressions Summarize data using aggregation and grouping Execute analytic functions to calculate ranks Build simple and correlated subqueries Thoroughly test SQL queries to avoid common errors Select the most efficient solution to complex SQL problems A company?s success hinges on responsible, accurate database management. Organizations rely on highly available data to complete all sorts of tasks, from creating marketing reports and invoicing customers to setting financial goals. Data professionals like analysts, developers and architects are tasked with creating, optimizing, managing and analyzing data from databases ? with little room for error. When databases aren?t built or maintained correctly, it?s easy to mishandle or lose valuable data. Our SQL Programming and Database Training Series provides students with the skills they require to develop, analyze and maintain data and in correctly structured, modern and secure databases. SQL is the cornerstone of all relational database operations. In this hands-on course, you learn to exploit the full potential of the SELECT statement to write robust queries using the best query method for your application, test your queries, and avoid common errors and pitfalls. It also teaches alternative solutions to given problems, enabling you to choose the most efficient solution in each situation. Introduction: Quick Tools Review Introduction to SQL and its development environments Using SQL*PLUS Using SQL Developer Using the SQL SELECT Statement Capabilities of the SELECT statement Arithmetic expressions and NULL values in the SELECT statement Column aliases Use of concatenation operator, literal character strings, alternative quote operator, and the DISTINCT keyword Use of the DESCRIBE command Restricting and Sorting Data Limiting the Rows Rules of precedence for operators in an expression Substitution Variables Using the DEFINE and VERIFY command Single-Row Functions Describe the differences between single row and multiple row functions Manipulate strings with character function in the SELECT and WHERE clauses Manipulate numbers with the ROUND, TRUNC and MOD functions Perform arithmetic with date data Manipulate dates with the date functions Conversion Functions and Expressions Describe implicit and explicit data type conversion Use the TO_CHAR, TO_NUMBER, and TO_DATE conversion functions Nest multiple functions Apply the NVL, NULLIF, and COALESCE functions to data Decode/Case Statements Using the Group Functions and Aggregated Data Group Functions Creating Groups of Data Having Clause Cube/Rollup Clause SQL Joins and Join Types Introduction to JOINS Types of Joins Natural join Self-join Non equijoins OUTER join Using Subqueries Introduction to Subqueries Single Row Subqueries Multiple Row Subqueries Using the SET Operators Set Operators UNION and UNION ALL operator INTERSECT operator MINUS operator Matching the SELECT statements Using Data Manipulation Language (DML) statements Data Manipulation Language Database Transactions Insert Update Delete Merge Using Data Definition Language (DDL) Data Definition Language Create Alter Drop Data Dictionary Views Introduction to Data Dictionary Describe the Data Dictionary Structure Using the Data Dictionary views Querying the Data Dictionary Views Dynamic Performance Views Creating Sequences, Synonyms, Indexes Creating sequences Creating synonyms Creating indexes Index Types Creating Views Creating Views Altering Views Replacing Views Managing Schema Objects Managing constraints Creating and using temporary tables Creating and using external tables Retrieving Data Using Subqueries Retrieving Data by Using a Subquery as Source Working with Multiple-Column subqueries Correlated Subqueries Non-Correlated Subqueries Using Subqueries to Manipulate Data Using the Check Option Subqueries in Updates and Deletes In-line Views Data Control Language (DCL) System privileges Creating a role Object privileges Revoking object privileges Manipulating Data Overview of the Explicit Default Feature Using multitable INSERTs Using the MERGE statement Tracking Changes in Data

Duration 3 Days 18 CPD hours This course is intended for The target audience for this course includes: Software testers (both technical and user acceptance testers), Test analysts, Test engineers, Test consultants, Software developers, Managers including test managers, project managers, quality managers. Overview By the end of this course, an attendee should be able to: perform effective testing of software, be aware of techniques and standards, have an awareness of what testing tools can achieve, where to find more information about testing, and establish the basic steps of the testing process. This is an ISTQB certification in software testing for the US. In this course you will study all of the basic aspects of software testing and QA, including a comprehensive overview of tasks, methods, and techniques for effectively testing software. This course prepares you for the ISTQB Foundation Level exam. Passing the exam will grant you an ISTQB CTFL certification. Fundamentals of Testing What is Testing? Typical Objectives of Testing Testing and Debugging Why is Testing Necessary? Testing?s Contributions to Success Quality Assurance and Testing Errors, Defects, and Failures Defects, Root Causes and Effects Seven Testing Principles Test Process Test Process in Context Test Activities and Tasks Test Work Products Traceability between the Test Basis and Test Work Products The Psychology of Testing Human Psychology and Testing Tester?s and Developer?s Mindsets Testing Throughout the Software Development Lifecycle Software Development Lifecycle Models Software Development and Software Testing Software Development Lifecycle Models in Context Test Levels Component Testing Integration Testing System Testing Acceptance Testing Test Types Functional Testing Non-functional Testing White-box Testing Change-related Testing Test Types and Test Levels Maintenance Testing Triggers for Maintenance Impact Analysis for Maintenance Static Testing Static Testing Basics Work Products that Can Be Examined by Static Testing Benefits of Static Testing Differences between Static and Dynamic Testing Review Process Work Product Review Process Roles and responsibilities in a formal review Review Types Applying Review Techniques Success Factors for Reviews Test Techniques Categories of Test Techniques Choosing Test Techniques Categories of Test Techniques and Their Characteristics Black-box Test Techniques Equivalence Partitioning Boundary Value Analysis Decision Table Testing State Transition Testing Use Case Testing White-box Test Techniques Statement Testing and Coverage Decision Testing and Coverage The Value of Statement and Decision Testing Experience-based Test Techniques Error Guessing Exploratory Testing Checklist-based Testing Test Management Test Organization Independent Testing Tasks of a Test Manager and Tester Test Planning and Estimation Purpose and Content of a Test Plan Test Strategy and Test Approach Entry Criteria and Exit Criteria (Definition of Ready and Definition of Done) Test Execution Schedule Factors Influencing the Test Effort Test Estimation Techniques Test Monitoring and Control Metrics Used in Testing Purposes, Contents, and Audiences for Test Reports Configuration Management Risks and Testing Definition of Risk Product and Project Risks Risk-based Testing and Product Quality Defect Management Tool Support for Testing Test Tool Considerations Test Tool Classification Benefits and Risks of Test Automation Special Considerations for Test Execution and Test Management Tools Effective Use of Tools Main Principles for Tool Selection Pilot Projects for Introducing a Tool into an Organization Success Factors for Tools Additional course details: Nexus Humans ISTQB Software Testing Certification Training - Foundation Level (CTFL) 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 ISTQB Software Testing Certification Training - Foundation Level (CTFL) 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 intermediate-level hands-on course is geared for experienced Administrators, Analysts, Architects, Data Scientists, Database Administrators and Implementers Overview This course is approximately 50% hands-on, combining expert lecture, real-world demonstrations and group discussions with machine-based practical labs and exercises. Working in a hands-on learning environment led by our Oracle Certified expert facilitator, students will learn how to: Administer ODI resources and setup security with ODI Apply ODI Topology concepts for data integration Describe ODI Model concepts Describe architecture of Oracle Data Integrator Design ODI Mappings, Procedures, Packages, and Load Plans to perform ELT data transformations Explore, audit data, and enforce data quality with ODI Implement Changed Data Capture with ODI Oracle Data Integrator is a comprehensive data integration platform that covers all data integration requirements from high-volume, high-performance batch loads, to event-driven integration processes and SOA-enabled data services. Oracle Data Integrator's Extract, Load, Transform (E-LT) architecture leverages disparate RDBMS engines to process and transform the data - the approach that optimizes performance, scalability and lowers overall solution costs. Throughout this course participants will explore how to centralize data across databases, performing integration, designing ODI Mappings, and setting up ODI security. In addition, Oracle Data Integrator can interact with the various tools of the Hadoop ecosystem, allowing administrators and data scientists to farm out map-reduce operations from established relational databases to Hadoop. They can also read back into the relational world the results of complex Big Data analysis for further processing. Working in a hands-on learning environment led by our Oracle Certified expert facilitator, students will learn how to: Administer ODI resources and setup security with ODI Apply ODI Topology concepts for data integration Describe ODI Model concepts Describe architecture of Oracle Data Integrator Design ODI Mappings, Procedures, Packages, and Load Plans to perform ELT data transformations Explore, audit data, and enforce data quality with ODI Implement Changed Data Capture with ODI Introduction to Integration and Administration Oracle Data Integrator: Introduction Oracle Data Integrator Repositories Administering ODI Repositories Create and connect to the Master Repository Export and import the Master Repository Create, connect, and set a password to the Work Repository ODI Topology Concepts ODI Topology: Overview Data Servers and Physical Schemas Defining Topology Agents in Topology Planning a Topology Describing the Physical and Logical Architecture Topology Navigator Creating Physical Architecture Creating Logical Architecture Setting Up a New ODI Project ODI Projects Using Folders Understanding Knowledge Modules Exporting and Importing Objects Using Markers Oracle Data Integrator Model Concepts Understanding the Relational Model Understanding Reverse-Engineering Creating Models Organizing ODI Models and Creating ODI Datastores Organizing Models Creating Datastores Constraints in ODI Creating Keys and References Creating Conditions Exploring Your Data Constructing Business Rules ODI Mapping Concepts ODI Mappings Expressions, Join, Filter, Lookup, Sets, and Others Behind the Rules Staging Area and Execution Location Understanding Knowledge Modules Mappings: Overview Designing Mappings Multiple Sources and Joins Filtering Data Overview of the Flow in ODI Mapping Selecting a Staging Area Configuring Expressions Execution Location Selecting a Knowledge Module Mappings: Monitoring and Troubleshooting Monitoring Mappings Working with Errors Designing Mappings: Advanced Topics 1 Working with Business Rules Using Variables Datasets and Sets Using Sequences Designing Mappings: Advanced Topics 2 Partitioning Configuring Reusable Mappings Using User Functions Substitution Methods Modifying Knowledge Modules Using ODI Procedures Procedures: Overview Creating a Blank Procedure Adding Commands Adding Options Running a Procedure Using ODI Packages Packages: Overview Executing a Package Review of Package Steps Model, Submodel, and Datastore Steps Variable Steps Controlling the Execution Path Step-by-Step Debugger Starting a Debug Session New Functions Menu Bar Icons Managing ODI Scenarios Scenarios Managing Scenarios Preparing for Deployment Using Load Plans What are load plans? Load plan editor Load plan step sequence Defining restart behavior Enforcing Data Quality with ODI Data Quality Business Rules for Data Quality Enforcing Data Quality with ODI Working with Changed Data Capture CDC with ODI CDC implementations with ODI CDC implementation techniques Journalizing Results of CDC Advanced ODI Administration Setting Up ODI Security Managing ODI Reports ODI Integration with Java

Duration 2 Days 12 CPD hours This course is intended for Experienced security administrators and security analysts who are already familiar with VMware Carbon Black Cloud Overview By the end of the course, you should be able to meet the following objectives: Describe and determine use cases for integrating with VMware Carbon Black Cloud Configure, automate, and troubleshoot the VMware Carbon Black Cloud Syslog Integration Use VMware Carbon Black Cloud APIs to pull data with Postman Install and use the VMware Carbon Black Cloud Python SDK Automate operations using the VMware Carbon Black Cloud SDK and APIs Identify and troubleshoot VMware Carbon Black Cloud sensor installations Gather troubleshooting data within the browser to remediate or escalate problems Identify and resolve sensor usage, networking, and performance problems with the VMware Carbon Black Cloud sensor This two-day, hands-on training course provides you with the advanced knowledge, skills, and tools to achieve competency in performing advanced operations and troubleshooting of VMware Carbon Black Cloud. This course will go into integrating VMware Carbon Black Cloud with other third-party components and utilizing the API and the SDK to automate operations within the product and your security stack. This course will also enable you to troubleshoot common problems during sensor installation, operations, and within the VMware Carbon Black Cloud console with hands-on lab problems. Course Introduction Introductions and course logistics Course objectives VMware Carbon Black Cloud Integrations Describe the integration capabilities with VMware Carbon Black Cloud Determine integration use cases for VMware Carbon Black Cloud Identify required components for integrating VMware Carbon Black Cloud Differentiate VMware Carbon Black Cloud integration vendors VMware Carbon Black Cloud Syslog Integration Describe the function of the Syslog Connector Generate API and SIEM keys from the Cloud console Validate a successful Syslog integration Describe how to automate the Syslog Connector Troubleshoot problems with the Syslog integration Using Postman Explain the concept and purpose of an API Interpret common REST API Status codes Recognize the difference between platform and product APIs Using the Postman Client to initiate API calls Create a custom access level and respective API key Create a valid API request Using the VMware Carbon Black Cloud Python SDK Install the VMware Carbon Black Cloud Python SDK Describe the different authentication methods Evaluate the best authentication method for a given task Automating Operations Automate basic Incident Response tasks using the VMware Carbon Black Cloud SDK and API Automate basic watchlist interactions using the VMware carbon Black Cloud SDK and API Sensor Installation Troubleshooting Describe sensor install log collection process Identify sensor install log parameters Create a detailed sensor install log Locate sensor install logs on an endpoint Interpret sensor install success from an install log Determine likely cause for install failure using sensor logs Propose resolution steps for a given sensor install failure VMware Carbon Black Cloud Console Troubleshooting Identify sensor bypass status reasons Simplify console data exports using search Describe differences in Audit Log detail levels Locate built-in browser tools Gather console diagnostics logs from a browser Review console diagnostics logs Sensor Operations Troubleshooting Identify available types of diagnostic logs Gather appropriate diagnostic logs for a given issue Identify steps for resolving software interoperability problems Identify steps for resolving resource problems Identify steps for resolving network problems Additional course details:Notes Delivery by TDSynex, Exit Certified and New Horizons an VMware Authorised Training Centre (VATC) Nexus Humans VMware Carbon Black Cloud:Advanced Operations and Troubleshooting 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 VMware Carbon Black Cloud:Advanced Operations and Troubleshooting 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 class is intended for the following job roles: [Cloud] information security analysts, architects, and engineers Information security/cybersecurity specialists Cloud infrastructure architects Additionally, the course is intended for Google and partner field personnel who work with customers in those job roles. The course should also be useful to developers of cloud applications Overview This course teaches participants the following skills: Understanding the Google approach to security Managing administrative identities using Cloud Identity. Implementing least privilege administrative access using Google Cloud Resource Manager, Cloud IAM. Implementing IP traffic controls using VPC firewalls and Cloud Armor Implementing Identity Aware Proxy Analyzing changes to the configuration or metadata of resources with GCP audit logs Scanning for and redact sensitive data with the Data Loss Prevention API Scanning a GCP deployment with Forseti Remediating important types of vulnerabilities, especially in public access to data and VMs This course gives participants broad study of security controls and techniques on Google Cloud Platform. Through lectures, demonstrations, and hands-on labs, participants explore and deploy the components of a secure Google Cloud solution. Participants also learn mitigation techniques for attacks at many points in a Google Cloud-based infrastructure, including Distributed Denial-of-Service attacks, phishing attacks, and threats involving content classification and use. Foundations of GCP Security Google Cloud's approach to security The shared security responsibility model Threats mitigated by Google and by GCP Access Transparency Cloud Identity Cloud Identity Syncing with Microsoft Active Directory Choosing between Google authentication and SAML-based SSO GCP best practices Identity and Access Management GCP Resource Manager: projects, folders, and organizations GCP IAM roles, including custom roles GCP IAM policies, including organization policies GCP IAM best practices Configuring Google Virtual Private Cloud for Isolation and Security Configuring VPC firewalls (both ingress and egress rules) Load balancing and SSL policies Private Google API access SSL proxy use Best practices for structuring VPC networks Best security practices for VPNs Security considerations for interconnect and peering options Available security products from partners Monitoring, Logging, Auditing, and Scanning Stackdriver monitoring and logging VPC flow logs Cloud audit logging Deploying and Using Forseti Securing Compute Engine: techniques and best practices Compute Engine service accounts, default and customer-defined IAM roles for VMs API scopes for VMs Managing SSH keys for Linux VMs Managing RDP logins for Windows VMs Organization policy controls: trusted images, public IP address, disabling serial port Encrypting VM images with customer-managed encryption keys and with customer-supplied encryption keys Finding and remediating public access to VMs VM best practices Encrypting VM disks with customer-supplied encryption keys Securing cloud data: techniques and best practices Cloud Storage and IAM permissions Cloud Storage and ACLs Auditing cloud data, including finding and remediating publicly accessible data Signed Cloud Storage URLs Signed policy documents Encrypting Cloud Storage objects with customer-managed encryption keys and with customer-supplied encryption keys Best practices, including deleting archived versions of objects after key rotation BigQuery authorized views BigQuery IAM roles Best practices, including preferring IAM permissions over ACLs Protecting against Distributed Denial of Service Attacks: techniques and best practices How DDoS attacks work Mitigations: GCLB, Cloud CDN, autoscaling, VPC ingress and egress firewalls, Cloud Armor Types of complementary partner products Application Security: techniques and best practices Types of application security vulnerabilities DoS protections in App Engine and Cloud Functions Cloud Security Scanner Threat: Identity and Oauth phishing Identity Aware Proxy Content-related vulnerabilities: techniques and best practices Threat: Ransomware Mitigations: Backups, IAM, Data Loss Prevention API Threats: Data misuse, privacy violations, sensitive/restricted/unacceptable content Mitigations: Classifying content using Cloud ML APIs; scanning and redacting data using Data Loss Prevention API Additional course details: Nexus Humans Security in Google Cloud 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 Security in Google Cloud 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 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.

Duration 3 Days 18 CPD hours This course is intended for This course is geared for anyone needing to interface with an Oracle database such as end users, business analysts, application developers and database administrators / DBAs. Overview Working within in a hands-on learning environment, guided by our expert team, attendees will develop a practical approach to Oracle Database Technology. Throughout the course participants will explore: Using PL/SQL programming language for database applications and development incorporating PL/SQL modules within the application architecture from the initial design and planning phase The essentials of building executable PL/SQL program units Each of the major segments of a working program and how these interact with each other during program execution Important error or exception handling capabilities of the language. How database-resident program units can be used as part of the overall database application architecture Applying these new skills to the development of PL/SQL packages. Advanced database programming capabilities and benefits How database triggers can be used as part of an advanced database application design Oracle 19c PL/SQL Fundamentals is a three-day, hands-on course that introduces Oracle database programming using the PL/SQL programming language. Throughout the course students will explore the core syntax, structure and features of the language. This course will also lay the foundation for the entire Oracle PL/SQL programming series, allowing one to progress from introductory topics to advanced application design and programming and finally onto writing complex high-performance applications. The course also explores applying the newly learned skills to the development of database applications. Participants will learn how to use database-resident stored program units such as procedures, functions, packages and database triggers. Students will also learn about the latest features in Oracle 19c. Selection & Setup of the Database Interface Considering Available Tools Selecting the Appropriate Tool Oracle Net Database Connections Oracle PAAS Database Connections Setup SQL Developer Setup SQL *Plus Setup JDeveloper About BIND and Substitution Variables Using SQL Developer Using SQL *Plus Choosing a Database Programming Language What is Database Programming PL/SQL Programming PL/SQL Performance Advantages Integration with Other Languages PL/SQL Language Essentials PL/SQL Program Structure Language Syntax Rules Embedding SQL Writing Readable Code Generating Readable Code Generating Database Output SQL * Plus Input of Program Block DECLARE Section About the Declare Section Declare Primitive Types Declaration Options Not Null Constant Data Dictionary Integration % Type Declare Simple User-Defined Types Type ? Table Type ? Record Extended User Defined Types BEGIN Section About the Begin Section Manipulating Program Data Logic Control & Braching GOTO LOOP IF-THEN-ELSE CASE EXCEPTION Section About the Exception Section Isolating the Specific Exception Pragma Exception_INIT SQLCODE &SQLERRM Example SQL%ROWCOUNT & Select ? Into Beyond the Basics : Explicit Cursors About Explicit Cursors Extend Cursor Techniques For Update of Clause Where Current of Clause Using for ? Loop Cursors Introduction Database Resident Programming Units About Database ? Resident Programs Physical Storage & Execution Types of Stored Program Units Stored Program Unit Advantages Modular Design Principles Creating Stored Procedures and Functions Stored Procedures & Functions Create Procedure / Create Function Creating Procedures & Functions Raise_Salary() Procedure Salary_Valid() function The Parameter Specification Default Clause System & Object Privileges Using the Development Tools Executing Stored Procedures and Functions Calling Procedures & Functions Unit Testing with Execute Anonymous Block Unit Testing Specifying a Parameter Notation SQL Worksheet Unit Testing Calling Functions from SQL Maintaining Stored Programming Units Recompiling Programs Mass Recompilation Using UTL_RECOMP() Dropping Procedures & Functions Drop Procedures & Functions Drop Procedure / Function Data Dictionary Metadata Using USER_OBJECTS Using USER_SOURCE Using USER_ERRORS Using USER_OBJECT_SIZE Using USER_DEPENDENCIES Managing Dependencies Dependency Internals Tracking Dependencies The Dependency Tracking Utility SQL Developer Dependency Info Dependency Strategy Checklists Creating & Maintaining About Packages Creating Packages Maintaining Packages Performance Considerations Advanced Package Capabilities Definer & Invoker Rights White Lists & Accessible By Persistent Global Objects Defining Initilization Logic Object Orientation Support Advanced Cursor Techniques Using Cursor Variables Using SYS_REFCURSOR Using Cursor Expressions Using System Supplied Packages DBMS_OUTPUT() UTL_FILE() FOPEN() Example Database Trigger Concepts About Database Triggers DML Event Trigger Sub-Types Database Trigger Scenario Trigger Exhaustion Mechanisms Trigger within SQL Worksheet Creating Database Triggers Statement Level Triggers Using Raise Application_Error() Row-Level Triggers Examples of Triggers Employee_Salary_Check Example Employee_Journal Example Budget_Event Example Instead of Triggers Triggers within and Application Maintaining Database Triggers Call Syntax Trigger Maintenance Tasks Show Errors Trigger Drop Trigger Alter Trigger Multiple Triggers for a Table Handling Mutating Table Issues Implementing System Event Triggers What are System Event Triggers Defining the Scope Available System Events System Event Attributes

Duration 3 Days 18 CPD hours This course is intended for The ideal audience for the RPA and UiPath Boot Camp is beginners in the field of RPA and individuals in roles such as developers, project managers, operation analysts, and tech enthusiasts looking to familiarize themselves with automation technologies. It's also perfectly suited for business professionals keen on understanding and implementing automated solutions within their organizations to optimize processes. 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 Automation Learning expert instructor, students will explore: Gain a thorough understanding of Robotic Process Automation (RPA) and its applications using UiPath, setting a solid foundation for future learning and application. Learn to record and play in UiPath Studio, a key skill that enables automating complex tasks in a user-friendly environment. Master the art of designing and controlling workflows using Sequencing, Flowcharting, and Control Flow, helping to streamline and manage automation processes effectively. Acquire practical skills in data manipulation, from variable management to CSV/Excel and data table conversions, empowering you to handle data-rich tasks with confidence. Develop competence in managing controls and exploring various plugins and extensions, providing a broader toolkit for handling diverse automation projects. Get hands-on experience with exception handling, debugging, logging, code management, and bot deployment, fundamental skills that ensure your automated processes are reliable and efficient. How to deploy and control Bots with UiPath Orchestrator The Hands-on Natural Language Processing (NLP) Boot Camp is an immersive, three-day course that serves as your guide to building machines that can read and interpret human language. NLP is a unique interdisciplinary field, blending computational linguistics with artificial intelligence to help machines understand, interpret, and generate human language. In an increasingly data-driven world, NLP skills provide a competitive edge, enabling the development of sophisticated projects such as voice assistants, text analyzers, chatbots, and so much more. Our comprehensive curriculum covers a broad spectrum of NLP topics. Beginning with an introduction to NLP and feature extraction, the course moves to the hands-on development of text classifiers, exploration of web scraping and APIs, before delving into topic modeling, vector representations, text manipulation, and sentiment analysis. Half of your time is dedicated to hands-on labs, where you'll experience the practical application of your knowledge, from creating pipelines and text classifiers to web scraping and analyzing sentiment. These labs serve as a microcosm of real-world scenarios, equipping you with the skills to efficiently process and analyze text data. Time permitting, you?ll also explore modern tools like Python libraries, the OpenAI GPT-3 API, and TensorFlow, using them in a series of engaging exercises. By the end of the course, you'll have a well-rounded understanding of NLP, and will leave equipped with the practical skills and insights that you can immediately put to use, helping your organization gain valuable insights from text data, streamline business processes, and improve user interactions with automated text-based systems. You?ll be able to process and analyze text data effectively, implement advanced text representations, apply machine learning algorithms for text data, and build simple chatbots. What is Robotic Process Automation? Scope and techniques of automation Robotic process automation About UiPath The future of automation Record and Play UiPath stack Downloading and installing UiPath Studio Learning UiPath Studio Task recorder Step-by-step examples using the recorder Sequence, Flowchart, and Control Flow Sequencing the workflow Activities Control flow, various types of loops, and decision making Step-by-step example using Sequence and Flowchart Step-by-step example using Sequence and Control flow Data Manipulation Variables and scope Collections Arguments ? Purpose and use Data table usage with examples Clipboard management File operation with step-by-step example CSV/Excel to data table and vice versa (with a step-by-step example) Taking Control of the Controls Finding and attaching windows Finding the control Techniques for waiting for a control Act on controls ? mouse and keyboard activities Working with UiExplorer Handling events Revisit recorder Screen Scraping When to use OCR Types of OCR available How to use OCR Avoiding typical failure points Tame that Application with Plugins and Extensions Terminal plugin SAP automation Java plugin Citrix automation Mail plugin PDF plugin Web integration Excel and Word plugins Credential management Extensions ? Java, Chrome, Firefox, and Silverlight Handling User Events and Assistant Bots What are assistant bots? Monitoring system event triggers Monitoring image and element triggers Launching an assistant bot on a keyboard event Exception Handling, Debugging, and Logging Exception handling Common exceptions and ways to handle them Logging and taking screenshots Debugging techniques Collecting crash dumps Error reporting Managing and Maintaining the Code Project organization Nesting workflows Reusability of workflows Commenting techniques State Machine When to use Flowcharts, State Machines, or Sequences Using config files and examples of a config file Integrating a TFS server Deploying and Maintaining the Bot Publishing using publish utility Overview of Orchestration Server Using Orchestration Server to control bots Using Orchestration Server to deploy bots License management Publishing and managing updates

Duration 3 Days 18 CPD hours This course is intended for This in an intermediate and beyond-level course is geared for experienced Python developers looking to delve into the exciting field of Natural Language Processing. It is ideally suited for roles such as data analysts, data scientists, machine learning engineers, or anyone working with text data and seeking to extract valuable insights from it. If you're in a role where you're tasked with analyzing customer sentiment, building chatbots, or dealing with large volumes of text data, this course will provide you with practical, hands on skills that you can apply right away. Overview This course combines engaging instructor-led presentations and useful demonstrations with valuable hands-on labs and engaging group activities. Throughout the course you'll: Master the fundamentals of Natural Language Processing (NLP) and understand how it can help in making sense of text data for valuable insights. Develop the ability to transform raw text into a structured format that machines can understand and analyze. Discover how to collect data from the web and navigate through semi-structured data, opening up a wealth of data sources for your projects. Learn how to implement sentiment analysis and topic modeling to extract meaning from text data and identify trends. Gain proficiency in applying machine learning and deep learning techniques to text data for tasks such as classification and prediction. Learn to analyze text sentiment, train emotion detectors, and interpret the results, providing a way to gauge public opinion or understand customer feedback. The Hands-on Natural Language Processing (NLP) Boot Camp is an immersive, three-day course that serves as your guide to building machines that can read and interpret human language. NLP is a unique interdisciplinary field, blending computational linguistics with artificial intelligence to help machines understand, interpret, and generate human language. In an increasingly data-driven world, NLP skills provide a competitive edge, enabling the development of sophisticated projects such as voice assistants, text analyzers, chatbots, and so much more. Our comprehensive curriculum covers a broad spectrum of NLP topics. Beginning with an introduction to NLP and feature extraction, the course moves to the hands-on development of text classifiers, exploration of web scraping and APIs, before delving into topic modeling, vector representations, text manipulation, and sentiment analysis. Half of your time is dedicated to hands-on labs, where you'll experience the practical application of your knowledge, from creating pipelines and text classifiers to web scraping and analyzing sentiment. These labs serve as a microcosm of real-world scenarios, equipping you with the skills to efficiently process and analyze text data. Time permitting, you?ll also explore modern tools like Python libraries, the OpenAI GPT-3 API, and TensorFlow, using them in a series of engaging exercises. By the end of the course, you'll have a well-rounded understanding of NLP, and will leave equipped with the practical skills and insights that you can immediately put to use, helping your organization gain valuable insights from text data, streamline business processes, and improve user interactions with automated text-based systems. You?ll be able to process and analyze text data effectively, implement advanced text representations, apply machine learning algorithms for text data, and build simple chatbots. Launch into the Universe of Natural Language Processing The journey begins: Unravel the layers of NLP Navigating through the history of NLP Merging paths: Text Analytics and NLP Decoding language: Word Sense Disambiguation and Sentence Boundary Detection First steps towards an NLP Project Unleashing the Power of Feature Extraction Dive into the vast ocean of Data Types Purification process: Cleaning Text Data Excavating knowledge: Extracting features from Texts Drawing connections: Finding Text Similarity through Feature Extraction Engineer Your Text Classifier The new era of Machine Learning and Supervised Learning Architecting a Text Classifier Constructing efficient workflows: Building Pipelines for NLP Projects Ensuring continuity: Saving and Loading Models Master the Art of Web Scraping and API Usage Stepping into the digital world: Introduction to Web Scraping and APIs The great heist: Collecting Data by Scraping Web Pages Navigating through the maze of Semi-Structured Data Unearth Hidden Themes with Topic Modeling Embark on the path of Topic Discovery Decoding algorithms: Understanding Topic-Modeling Algorithms Dialing the right numbers: Key Input Parameters for LSA Topic Modeling Tackling complexity with Hierarchical Dirichlet Process (HDP) Delving Deep into Vector Representations The Geometry of Language: Introduction to Vectors in NLP Text Manipulation: Generation and Summarization Playing the creator: Generating Text with Markov Chains Distilling knowledge: Understanding Text Summarization and Key Input Parameters for TextRank Peering into the future: Recent Developments in Text Generation and Summarization Solving real-world problems: Addressing Challenges in Extractive Summarization Riding the Wave of Sentiment Analysis Unveiling emotions: Introduction to Sentiment Analysis Tools Demystifying the Textblob library Preparing the canvas: Understanding Data for Sentiment Analysis Training your own emotion detectors: Building Sentiment Models Optional: Capstone Project Apply the skills learned throughout the course. Define the problem and gather the data. Conduct exploratory data analysis for text data. Carry out preprocessing and feature extraction. Select and train a model. ? Evaluate the model and interpret the results. Bonus Chapter: Generative AI and NLP Introduction to Generative AI and its role in NLP. Overview of Generative Pretrained Transformer (GPT) models. Using GPT models for text generation and completion. Applying GPT models for improving autocomplete features. Use cases of GPT in question answering systems and chatbots. Bonus Chapter: Advanced Applications of NLP with GPT Fine-tuning GPT models for specific NLP tasks. Using GPT for sentiment analysis and text classification. Role of GPT in Named Entity Recognition (NER). Application of GPT in developing advanced chatbots. Ethics and limitations of GPT and generative AI technologies.

Duration 1 Days 6 CPD hours This course is intended for This overview-level course is ideally suited for professionals seeking an introduction to microservices architecture and its application within a business context. Ideal attendee roles include software developers, system architects, technical managers, and IT professionals who are part of teams transitioning to a microservices approach. It's also an excellent starting point for non-technical roles such as product owners or business analysts who work closely with technical teams and want to better understand and become conversant in the language and principles of microservices. Overview This course combines engaging instructor-led presentations and useful demonstrations with engaging group activities. Throughout the course you'll explore: Understand the Basics of Microservices: Get to know the fundamental principles and characteristics of microservices and how they revolutionize traditional software development approaches. Explore the Design of Microservices: Gain an overview of how microservices are designed based on business requirements and what makes them unique in the software architecture world. Overview of Managing and Scaling Microservices: Get an introduction to how microservices are managed and scaled independently, and understand the significance of these features in your business operations. Familiarize with the Microservices Ecosystem: Learn about the typical patterns, best practices, and common pitfalls in the microservices world, setting a foundation for future learning and implementation. Introduction to Microservices in a Business Context: Acquire a basic understanding of how microservices can be aligned with specific business capabilities, and get a glimpse into how they can coexist with legacy systems in a business setting. Microservices have rapidly emerged as a popular architectural style, breaking down applications into small, independent services that can be developed, deployed, and scaled individually. Microservices offer a robust method to address a variety of projects, such as e-commerce platforms and content management systems, enhancing scalability and boosting productivity. This technology, when employed correctly, can greatly increase software delivery speed and system resilience, making it a crucial skill set for modern technology professionals.Understanding Microservices - A Technical Overview is a one-day course ideally suited for technical professionals seeking an introduction to microservices architecture and its application within a business context. Under the guidance of an industry expert, this engaging class combines lecture-style learning with lively demonstrations, case study review and group discussions.Throughout the course you?ll explore the principles and characteristics that define microservices, how to identify suitable projects for a microservices approach, the factors to consider when designing them, and the strategies to effectively manage and scale them within complex systems. You?ll also learn about the best practices, patterns, and anti-patterns, arming you with the knowledge to make the right architectural choices. This course also explores the real-world implementation of microservices in a business enterprise. We'll discuss how to align the application of microservices with your organization's specific business capabilities, and offer strategies for smoothly integrating this technology within existing legacy systems. Introduction to Microservices Understand what microservices are and their role in modern software development. Introduction to Microservices: what they are and why they matter. Monolithic vs Microservices: highlighting the shift and benefits. Key principles and characteristics of microservices. Identifying suitable applications for microservices transformation. Demo: Analyzing a sample application and identifying potential microservices Architecting and Managing Microservices Learn the basic strategies for scaling and managing microservices. Scaling Microservices: from a single service to hundreds. Key components of a microservices architecture. Introduction to resilience patterns: Circuit-Breakers and Bulkheads. Load management and provisioning in a microservices setup. Understanding the role of cloud services in microservices. Optional Demo: Illustrating how a microservice-based application scales in real-time Designing Microservices Learn the key aspects to consider when designing microservices. Defining microservice boundaries: Deciding the scope of a microservice. Communication patterns in microservices. Understanding Microservice endpoints. Exploring data stores and transaction boundaries in microservices. Overcoming challenges in Microservices design. Demo: Designing microservices for a hypothetical business requirement Implementing Microservices in a Business Enterprise Understand the process and considerations for implementing microservices in an enterprise context. Assessing enterprise readiness for microservices. Building the business case for microservices: strategic advantages and potential challenges. Aligning microservices with business capabilities. Organizational changes: Team structures and processes for microservices. Dealing with Legacy Systems: Strategies for microservices integration. Demo: Exploring a case study of successful microservices implementation in a business enterprise The Microservices Ecosystem Understand the key tools and best practices in the Microservices ecosystem. Understanding the typical Microservices Stack. Monitoring and Logging in Microservices. Introduction to Docker: Containerization of Microservices. Deployment strategies in a Microservices setup. Introduction to Orchestration in Microservices Demo: Containerizing and deploying a simple microservice Microservices Deployment Strategies Understand various ways to safely introduce changes in a microservices environment. The concept of Blue-Green Deployment: changing services without downtime. Canary Releases and Feature Toggles: slowly rolling out changes to users. Database changes in a microservices environment: keeping data consistent. Demo: Examining various deployment strategies Microservices Best Practices and DevOps Learn key strategies to ensure a smooth operation of your microservices setup. The DevOps culture in Microservices: collaboration for efficiency. Defining a Minimum Viable Product in a Microservices setup: building small, delivering fast. Dealing with data in a distributed setup: managing Data Islands. The importance of Continuous Integration/Continuous Delivery in a microservices setup. Governance: Keeping track of your services and their consumers. Demo: Visualizing a simple continuous delivery pipeline Microservices Patterns and Anti-Patterns Learn about common do's and don'ts when working with microservices. Understanding patterns that help with efficient microservices operation. Recognizing and avoiding anti-patterns that can hinder performance. Dealing with common challenges: dependencies between services, managing service boundaries. Demo: Examples of real-world patterns and anti-patterns Simple Overview of OAuth and OpenID for Microservices Introduction to OAuth and OpenID: What they are and why they matter in Microservices. The role of tokens in OAuth 2.0: How they help in securing communications. A simplified look at OpenID Connect: Linking identities across services. Demo