141 Courses delivered Live Online

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 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 This course is appropriate for anyone needing to interface with an Oracle database or those needing a general understanding of Oracle database functionality. That would include end users, business analysts, application developers and database administrators. Overview Working in a hands-on learning environment led by our expert pracitioner you'll learn how to: Add Data, Retrieve, Sort and Organize a SQL Database Combine Data, Set Operators and Subqueries Manipulate Data and Data Definition Languages in SQL Work with Data Dictionary Views and Create Sequences, Indexes and Views Use Database Objects and Subqueries Perform Data and access control Perform other Advanced Level Database operations. Oracle 19C SQL Programming Fundamentals Is a three-day, hands-on course designed to equip you with the fundamental skills needed to set up, run and manage SQL databases using Oracle Database Technology. You will also be discovering all the tools and concepts required to organize data efficiently. Our engaging instructors and mentors are highly-experienced practitioners who bring years of current 'on-the-job' experience into every classroom. 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, you will learn the key elements of a database, and the way Oracle systems facilitate their induction in the system. You?ll also learn the tools and strategies you can implement to store, retrieve, compare and organize data according to your requirements. You?ll also explore the process of creating simple to complex reports from existing data. By the end of this course, you will also have hands-on knowledge of SQL systems that are required to proceed to other advanced to professional programs. Adding Data, Retrieving, Sorting and Organizing a SQL Database The building blocks of a database. How to add data to the database. The process of retrieving data using SQL functions. Multiple methods of sorting and organizing data. Using SQL functions to get the required simple to complex output. Various strategies for using functions and conditions to organize data. Combining Data, Set Operators And Subqueries Consolidating data using multiple functions and group operators. Fetching intelligent data reports using simple functions. Fetching data from multiple sources in the tables. Using Subqueries to compile data as required. Using Set operators to create smart data reports. Data Manipulation and Data Definition Languages in SQL Describing and managing data transaction using Data Definition Language. Categorize and review data tables using Data Definition Language. Data Dictionary Views and Creating Sequences, Indexes and Views How to manage and query Data Dictionary Views. The process of creating and using Sequences. How to create various types of Synonyms and Indexes. Creating simple and complex views and retrieving data. Understanding and using Database Objects and Subqueries Core concept and application of Schema Objects. Fetching required data with Subqueries. Using Subqueries to organize Data in SQL. Data and access control Assigning and revoking data access. Managing data access control according to user levels. Performing Advanced Level Database operations. Using advanced functions and performing data queries. Creating and managing time zone-based databases.

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 5 Days 30 CPD hours This course is intended for This is an introductory-level systems administration course geared for Systems Administrators and users who wish to learn how to how to install, configure and maintain an Enterprise Linux system in a networked environment. Overview This course is about 50% lab to lecture ratio, combining expert instructor-led discussions with practical hands-on skills that emphasize current techniques, best practices and standards. Working in this hands-on lab environment, guided by our expert practitioner, attendees will explore Installing the Linux operating system and configuring peripherals Performing and modifying startup and shutdown processes Configuring and maintaining basic networking services Creating and maintaining system users and groups Understanding and administering file permissions on directories and regular files Planning and creating disk partitions and file systems Performing maintenance on file systems Identifying and managing Linux processes Automating tasks with cron Performing backups and restoration of files Working with system log files Troubleshooting system problems Analyzing and taking measures to increase system performance Configuring file sharing with NFS Configuring Samba for file sharing with the Windows clients Setting up a basic Web server Understanding the components for setting up a LAMP server Implementing basic security measures Linux System Administration is a comprehensive hands-on course that teaches students how to install, configure and maintain an Enterprise Linux system in a networked environment. This lab-intensive class explores core administrative tasks such as: creating and managing users, creating and maintaining file systems, determining and implementing security measures and performing software installation and package management. Linux networking topics include installing and supporting SSH, NFS, Samba and the Apache Web server. Students will explore common security issues, as well as several tools, such as the PAM modules that help secure the operating system and network environment. Upon successful completion of this course, students will be prepared to maintain Linux systems in a networked business environment. Although the course includes installing and configuring a CentOS 7 / RHEL 7 Linux system, much of the course content also applies to Oracle, Ubuntu, Scientific and other current versions of mainstream Linux distributions. Labs include user and group maintenance, system backups and restoration, software management, administration tasks automation, file system creation and maintenance, managing remote access, working with cron, and configuring basic file sharing and Web services, as well as working with system logging utilities such as rsyslog and much more. System Administration Overview UNIX, Linux and Open Source Duties of the System Administrator Superusers and the Root Login Sharing Superuser Privileges with Others (su and sudo Commands) TCP/IP Networking Fundamentals Online Help Installation and Configuration Planning: Hardware and Software Considerations Site Planning Installation Methods and Types Installation Classes Partitions Logical Volume Manager - LVM File System Overview Swap Partition Considerations Other Partition Considerations The Linux Boot Loader: grub Software Package Selection Adding and Configuring Peripherals Printers Graphics Controllers Basic Networking Configuration Booting to Recovery Mode Booting and Shutting Down Linux Boot Sequence The systemd Daemon The systemctl Command Targets vs. Run Levels Modifying a Target Service Unit Scripts Changing System States Booting into Rescue Mode Shutdown Commands Managing Software and Devices Identifying Software Packages Using rpm to Manage Software Using yum to Manage Software Installing and Removing Software Identifying Devices Displaying Device and System Information (PCI, USB) Plug and Play Devices Device Configuration Tools Managing Users and Groups Setting Policies User File Management The /etc/passwd file The /etc/shadow file The /etc/group file The /etc/gshadow file Adding Users Modifying User Accounts Deleting User Accounts Working with Groups Setting User Environments Login Configuration Files The Linux File System Filesystem Types Conventional Directory Structure Mounting a File System The /etc/fstab File Special Files (Device Files) Inodes Hard File Links Soft File Links Creating New File Systems with mkfs The lost+found Directory Repairing File Systems with fsck The Journaling Attribute File and Disk Management Tools Linux File Security File Permissions Directory Permissions Octal Representation Changing Permissions Setting Default Permissions Access Control Lists (ACLs) The getfacl and setfacl commands SUID Bit SGID Bit The Sticky Bit Controlling Processes Characteristics of Processes Parent-Child Relationship Examining Running Processes Background Processes Controlling Processes Signaling Processes Killing Processes Automating Processes cron and crontab at and batch System Processes (Daemons) Working with the Linux Kernel Linux Kernel Components Types of Kernels Kernel Configuration Options Recompiling the Kernel Shell Scripting Overview Shell Script Fundamentals Bash Shell Syntax Overview Shell Script Examples System Backups Backup Concepts and Strategies User Backups with the tar Command System Backup Options The xfsdump and xfsrestore Commands Troubleshooting the System Common Problems and Symptoms Troubleshooting Steps Repairing General Boot Problems Repairing the GRUB 2 Boot Loader Hard Drive Problems Restoring Shared Libraries System Logs and rsyslogd Basic Networking Networking Services Overview NetworkManager Introduction Network Configuration Files Locations and Formats Enabling and Restarting Network Services with systemtcl Configuring Basic Networking Manually Configuring Basic Networking with NetworkManager LAMP Server Basics LAMP Overview Configuring the Apache Web Server Common Directives Apache Virtual Hosting Configuring an Open Source Database MySQL MariaDB PHP Basics Perl CGI Scripting Introduction to System Security Security Overview Maintaining System Security Server Access Physical Security Network Security Security Tools Port Probing with nmap Intrusion Detection and Prevention PAM Security Modules Scanning the System Maintaining File Integrity Using Firewalls Introduction to firewalld The Samba File Sharing Facility Configure Samba for Linux to Linux/UNIX File Sharing Configure Samba for Linux to Windows File Sharing Use the smbclient Utility to Transfer Files Mount/Connect Samba Shares to Linux and Windows Clients Networked File Systems (NFS) Using NFS to Access Remote File Systems Configuring the NFS Server Configuring the NFS Client Exporting File Systems from the NFS Server to the NFS Client

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 2 Days 12 CPD hours This course is intended for This in an Introductory and beyond level course is geared for experienced Java developers seeking to be proficient in Apache Kafka. Attendees should be experienced developers who are comfortable with Java, and have reasonable experience working with databases. Overview Working in a hands-on learning environment, students will explore Overview of Streaming technologies Kafka concepts and architecture Programming using Kafka API Kafka Streams Monitoring Kafka Tuning / Troubleshooting Kafka Apache Kafka is a real-time data pipeline processor. It high-scalability, fault tolerance, execution speed, and fluid integrations are some of the key hallmarks that make it an integral part of many Enterprise Data architectures. In this lab intensive two day course, students will learn how to use Kafka to build streaming solutions. Introduction to Streaming Systems Fast data Streaming architecture Lambda architecture Message queues Streaming processors Introduction to Kafka Architecture Comparing Kafka with other queue systems (JMS / MQ) Kaka concepts : Messages, Topics, Partitions, Brokers, Producers, commit logs Kafka & Zookeeper Producing messages Consuming messages (Consumers, Consumer Groups) Message retention Scaling Kafka Programming With Kafka Configuration parameters Producer API (Sending messages to Kafka) Consumer API (consuming messages from Kafka) Commits , Offsets, Seeking Schema with Avro Kafka Streams Streams overview and architecture Streams use cases and comparison with other platforms Learning Kafka Streaming concepts (KStream, KTable, KStore) KStreaming operations (transformations, filters, joins, aggregations) Administering Kafka Hardware / Software requirements Deploying Kafka Configuration of brokers / topics / partitions / producers / consumers Security: How secure Kafka cluster, and secure client communications (SASL, Kerberos) Monitoring : monitoring tools Capacity Planning : estimating usage and demand Trouble shooting : failure scenarios and recovery Monitoring and Instrumenting Kafka Monitoring Kafka Instrumenting with Metrics library Instrument Kafka applications and monitor their performance

Duration 3 Days 18 CPD hours This course is intended for This course is geared for Python-experienced attendees who wish to be equipped with the skills you need to use pandas to ensure the veracity of your data, visualize it for effective decision-making, and reliably reproduce analyses across multiple datasets. Overview Working in a hands-on learning environment, guided by our expert team, attendees will learn to: Understand how data analysts and scientists gather and analyze data Perform data analysis and data wrangling using Python Combine, group, and aggregate data from multiple sources Create data visualizations with pandas, matplotlib, and seaborn Apply machine learning (ML) algorithms to identify patterns and make predictions Use Python data science libraries to analyze real-world datasets Use pandas to solve common data representation and analysis problems Build Python scripts, modules, and packages for reusable analysis code Perform efficient data analysis and manipulation tasks using pandas Apply pandas to different real-world domains with the help of step-by-step demonstrations Get accustomed to using pandas as an effective data exploration tool. Data analysis has become a necessary skill in a variety of domains where knowing how to work with data and extract insights can generate significant value. Geared for data team members with incoming Python scripting experience, Hands-On Data Analysis with Pandas will show you how to analyze your data, get started with machine learning, and work effectively with Python libraries often used for data science, such as pandas, NumPy, matplotlib, seaborn, and scikit-learn. Using real-world datasets, you will learn how to use the powerful pandas library to perform data wrangling to reshape, clean, and aggregate your data. Then, you will be able to conduct exploratory data analysis by calculating summary statistics and visualizing the data to find patterns. In the concluding lessons, you will explore some applications of anomaly detection, regression, clustering, and classification using scikit-learn to make predictions based on past data. Students will leave the course armed with the skills required to use pandas to ensure the veracity of their data, visualize it for effective decision-making, and reliably reproduce analyses across multiple datasets. Introduction to Data Analysis Fundamentals of data analysis Statistical foundations Setting up a virtual environment Working with Pandas DataFrames Pandas data structures Bringing data into a pandas DataFrame Inspecting a DataFrame object Grabbing subsets of the data Adding and removing data Data Wrangling with Pandas What is data wrangling? Collecting temperature data Cleaning up the data Restructuring the data Handling duplicate, missing, or invalid data Aggregating Pandas DataFrames Database-style operations on DataFrames DataFrame operations Aggregations with pandas and numpy Time series Visualizing Data with Pandas and Matplotlib An introduction to matplotlib Plotting with pandas The pandas.plotting subpackage Plotting with Seaborn and Customization Techniques Utilizing seaborn for advanced plotting Formatting Customizing visualizations Financial Analysis - Bitcoin and the Stock Market Building a Python package Data extraction with pandas Exploratory data analysis Technical analysis of financial instruments Modeling performance Rule-Based Anomaly Detection Simulating login attempts Exploratory data analysis Rule-based anomaly detection Getting Started with Machine Learning in Python Learning the lingo Exploratory data analysis Preprocessing data Clustering Regression Classification Making Better Predictions - Optimizing Models Hyperparameter tuning with grid search Feature engineering Ensemble methods Inspecting classification prediction confidence Addressing class imbalance Regularization Machine Learning Anomaly Detection Exploring the data Unsupervised methods Supervised methods Online learning The Road Ahead Data resources Practicing working with data Python practice

Duration 2 Days 12 CPD hours This course is intended for This is an Intermediate PowerBI course geared for experienced users who wish to leverage the tool's more advanced capabilities Overview This course is about 50% hands-on lab and 50% lecture, designed to train attendees in essential PowerBI data handling functions and reporting skills, coupling the most current, effective techniques with the soundest practices. Attendees of this course will gain practical examples from the experienced instructor who has deployed and configured Power BI reporting in a wide variety of businesses. Working in a hands-on learning environment led by our expert facilitator, students will learn how to: Create Advanced Power BI Reports Advanced understanding of the data schemas and extracting data Perform advanced transformations of data or any data schema Utilize time-phased data in the creation of complex analyses Create new measures using DAX Filter data using row-level security Create and deploy content packs Use Power BI to integrate with line-of-business applications Next Level Power BI for Experienced Users is a two day, course that provides attendees already experienced with Microsoft Power BI basics with a hands-on exploration of intermediate and beyond level features. This course is geared for attendees ready to learn the advanced techniques that you, your business analysts, and your stakeholders need to create complex information from projects, program, and portfolio reporting to utilizing time-phased data and, potentially, data from your enterprise?s other line-of-business tools. Get Project Online Data Select and mine relevant tables with ODATA Advanced ODATA data mining Importing other data formats Advanced Editing of data queries Advanced Data Transformations Managing table relationships Creating & using data hierarchies Creating custom columns and measures and metrics for filtering and reporting Creating Power BI Reports Using advanced visualizations Configuring drill-down Modifying visual interactions Importing and creating custom visuals Configure Power BI Security Creating Dashboard and row-level security Utilizing Filtering using row-level security Publishing Reports and Dashboards Building Mobile Reporting Creating and deploying content packs Configuring natural language query

Duration 5 Days 30 CPD hours This course is intended for This hands-on course is geared for experienced DBAs new to Oracle 19c, who can work in Linux and have basic experience with SQL scripting. 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 Oracle Certified expert facilitator, students will learn how to: How to use tools to access an Oracle Database Generate database creation scripts by using DBCA How to create a container database (CDB) by using the CREATE DATABASE command Learn about Startup and shut down Oracle databases Initialization parameter files and initialization parameters Tools that are used to administer Oracle Net Services How to use the Oracle Connection Manager Control utility to administer Oracle Connection Manager How to create a new PDB from the PDB seed. Logical and physical storage structures in an Oracle database Usage of Oracle Database features that save space Explanation of DML and undo data generation Learn about general architecture of Oracle Data Pump and SQL*Loader How to use SQL*Loader to load data from a non-Oracle database (or user files) Bonus Content / Time Permitting: Explanation of maintenance windows Bonus Content / Time Permitting: Employ basic monitoring procedures and manage performance Oracle 19C Database Administration I (Oracle DBA I) is a comprehensive, hands-on course provides concrete information on the design of an Oracle Database instance and database, allowing you to manage your database investment. In this class, you will learn how to create database storage structures that align with your requirements and business models. You will also learn how to create users and administer databases as well as harden the databases to meet your business requirements. This is the foundational course for learning about Oracle Database and it does not assume prior knowledge or Oracle technologies, however you should have incoming experience working with SQL, and be comfortable with Linux and working from the command line. This training is NOT Official Oracle University training. This is independent, adjustable content that aligns with current topics, skills and tools that participants need to excel in these areas. Introduction to Oracle Database Oracle Multitenant Container Database Oracle Database Instance Configurations Database Sharding Oracle Database Server Accessing an Oracle Database Oracle Database Tools Database Tool Choices SQL Developer Enterprise Manager Database Express Creating an Oracle Database by Using DBCA Planning the Database Choosing a Database Template Configuration Assistant Creating an Oracle Database by Using a SQL Command Creating a Container Database Enable Pluggable Database Starting Up and Shutting Down a Database Instance Starting the Oracle Database Instance Shutting Down an Oracle Database Instance Opening and Closing PDBs Managing Database Instances Investigating Initialization Parameter Files Viewing Initialization Parameters by Using SQL*Plus Modifying Initialization Parameters by Using SQL*Plus Viewing Diagnostic Information Oracle Net Services Overview Oracle Net Services Components Oracle Net Listener Configuring Naming Methods Configuring the Oracle Network to Access a Database Creating a Net Service Name for a PDB Configuring and Administering the Listener Exploring the Default Listener Creating a Second Listener Connecting to a Database Service Using the New Listener Configuring a Shared Server Architecture Configuring Shared Server Mode Configuring Clients to Use a Shared Server Configuring Oracle Connection Manager for Multiplexing and Access Control Oracle Connection Manager Processes Filtering Rules Session Multiplexing Creating PDBs Creating a New PDB from the PDB Seed Cloning Remote PDBs in Hot Mode Relocating PDBs Managing PDBs Renaming a PDB Setting Parameter Values for PDBs Database Storage Overview Logical and Physical Database Structures Tablespaces and Data Files Types of Segments Monitoring Tablespace Space Usage Creating and Managing Tablespaces Viewing Tablespace Information Creating a Tablespace Managing Temporary and Permanent Tablespaces Improving Space Usage Managing Space in Tablespaces Using Compression Enabling the Resumable Space Allocation Feature Creating and Managing User Accounts Creating Common and Local Users Creating a Local User for an Application Exploring OS and Password File Authentication Configuring Privilege and Role Authorization Granting a Local Role (DBA) to PDBADMIN Using SQL*Developer to Create Local Roles Configuring User Resource Limits Using SQL*Developer to Create a Local Profile & Users Configuring a Default Role for a User Implementing Oracle Database Auditing Enabling Unified Auditing Creating Audit Users Creating an Audit Policy Introduction to Loading and Transporting Data General Architecture Oracle Data Pump SQL Loader Loading Data into a PDB from an External File Moving Data from One PDB to Another PDB Transporting a Tablespace Using External Tables to Load and Transport Data Querying External Tables Unloading External Tables Automated Maintenance Tasks Overview Automated Maintenance Tasks Maintenance Windows Predefined Maintenance Windows Bonus: Managing Tasks and Windows Enabling and Disabling Automated Maintenance Tasks Modifying the Duration of a Maintenance Window Bonus: Database Monitoring and Performance Tuning Overview Performance Planning Considerations Automatic Workload Repository (AWR) Advisory Framework Bonus: Monitoring Database Performance & Processes Server-Generated Alerts Setting Metric Thresholds Performance Monitoring Examining the Database Background Processes Bonus: Tuning Database Memory Viewing Memory Configurations Bonus: Analyzing SQL and Optimizing Access Paths Using the Optimizer Statistics Advisor