2563 Courses delivered Live Online

Duration 3 Days 18 CPD hours This course is intended for This course is geared for experienced Scala developers who are new to the world of machine learning and are eager to expand their skillset. Professionals such as data engineers, data scientists, and software engineers who want to harness the power of machine learning in their Scala-based projects will greatly benefit from attending. Additionally, team leads and technical managers who oversee Scala development projects and want to integrate machine learning capabilities into their workflows can gain valuable insights from this course Overview Working in a hands-on learning environment led by our expert instructor you'll: Grasp the fundamentals of machine learning and its various categories, empowering you to make informed decisions about which techniques to apply in different situations. Master the use of Scala-specific tools and libraries, such as Breeze, Saddle, and DeepLearning.scala, allowing you to efficiently process, analyze, and visualize data for machine learning projects. Develop a strong understanding of supervised and unsupervised learning algorithms, enabling you to confidently choose the right approach for your data and effectively build predictive models Gain hands-on experience with neural networks and deep learning, equipping you with the know-how to create advanced applications in areas like natural language processing and image recognition. Explore the world of generative AI and learn how to utilize GPT-Scala for creative text generation tasks, broadening your skill set and making you a more versatile developer. Conquer the realm of scalable machine learning with Scala, learning the secrets to tackling large-scale data processing and analysis challenges with ease. Sharpen your skills in model evaluation, validation, and optimization, ensuring that your machine learning models perform reliably and effectively in any situation. Machine Learning Essentials for Scala Developers is a three-day course designed to provide a solid introduction to the world of machine learning using the Scala language. Throughout the hands-on course, you?ll explore a range of machine learning algorithms and techniques, from supervised and unsupervised learning to neural networks and deep learning, all specifically crafted for Scala developers. Our expert trainer will guide you through real-world, focused hands-on labs designed to help you apply the knowledge you gain in real-world scenarios, giving you the confidence to tackle machine learning challenges in your own projects. You'll dive into innovative tools and libraries such as Breeze, Saddle, DeepLearning.scala, GPT-Scala (and Generative AI with Scala), and TensorFlow-Scala. These cutting-edge resources will enable you to build and deploy machine learning models for a wide range of projects, including data analysis, natural language processing, image recognition and more. Upon completing this course, you'll have the skills required to tackle complex projects and confidently develop intelligent applications. You?ll be able to drive business outcomes, optimize processes, and contribute to innovative projects that leverage the power of data-driven insights and predictions. Introduction to Machine Learning and Scala Learning Outcome: Understand the fundamentals of machine learning and Scala's role in this domain. What is Machine Learning? Machine Learning with Scala: Advantages and Use Cases Supervised Learning in Scala Learn the basics of supervised learning and how to apply it using Scala. Supervised Learning: Regression and Classification Linear Regression in Scala Logistic Regression in Scala Unsupervised Learning in Scala Understand unsupervised learning and how to apply it using Scala. Unsupervised Learning:Clustering and Dimensionality Reduction K-means Clustering in Scala Principal Component Analysis in Scala Neural Networks and Deep Learning in Scala Learning Outcome: Learn the basics of neural networks and deep learning with a focus on implementing them in Scala. Introduction to Neural Networks Feedforward Neural Networks in Scala Deep Learning and Convolutional Neural Networks Introduction to Generative AI and GPT in Scala Gain a basic understanding of generative AI and GPT, and how to utilize GPT-Scala for natural language tasks. Generative AI: Overview and Use Cases Introduction to GPT (Generative Pre-trained Transformer) GPT-Scala: A Library for GPT in Scala Reinforcement Learning in Scala Understand the basics of reinforcement learning and its implementation in Scala. Introduction to Reinforcement Learning Q-learning and Value Iteration Reinforcement Learning with Scala Time Series Analysis using Scala Learn time series analysis techniques and how to apply them in Scala. Introduction to Time Series Analysis Autoregressive Integrated Moving Average (ARIMA) Models Time Series Analysis in Scala Natural Language Processing (NLP) with Scala Gain an understanding of natural language processing techniques and their application in Scala. Introduction to NLP: Techniques and Applications Text Processing and Feature Extraction NLP Libraries and Tools for Scala Image Processing and Computer Vision with Scala Learn image processing techniques and computer vision concepts with a focus on implementing them in Scala. Introduction to Image Processing and Computer Vision Feature Extraction and Image Classification Image Processing Libraries for Scala Model Evaluation and Validation Understand the importance of model evaluation and validation, and how to apply these concepts using Scala. Model Evaluation Metrics Cross-Validation Techniques Model Selection and Tuning in Scala Scalable Machine Learning with Scala Learn how to handle large-scale machine learning problems using Scala. Challenges of Large-Scale Machine Learning Data Partitioning and Parallelization Distributed Machine Learning with Scala Machine Learning Deployment and Production Understand the process of deploying machine learning models into production using Scala. Deployment Challenges and Best Practices Model Serialization and Deserialization Monitoring and Updating Models in Production Ensemble Learning Techniques in Scala Discover ensemble learning techniques and their implementation in Scala. Introduction to Ensemble Learning Bagging and Boosting Techniques Implementing Ensemble Models in Scala Feature Engineering for Machine Learning in Scala Learn advanced feature engineering techniques to improve machine learning model performance in Scala. Importance of Feature Engineering in Machine Learning Feature Scaling and Normalization Techniques Handling Missing Data and Categorical Features Advanced Optimization Techniques for Machine Learning Understand advanced optimization techniques for machine learning models and their application in Scala. Gradient Descent and Variants Regularization Techniques (L1 and L2) Hyperparameter Tuning Strategies

Join me on Wednesday 18th May to discuss Staff Retention: We will share ideas and hopefully learn new ideas. We will explore the most effective ways to connect your team. Lets look at how leading in an emotionally Intelligent way can help retain staff.

We share the secrets of how to make one of the most challenging areas of managing people into one of the simplest and most rewarding. Build motivated and effective teams through managers who are skilled in setting challenging but achievable goals, measuring performance and giving great feedback.

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 2.5 Days 15 CPD hours

Duration 2 Days 12 CPD hours This course is intended for This is an Intermediate and beyond-level Tableau course geared for experienced Tableau users who wish to leverage Tableau's more advanced capabilities. Overview This skills-focused 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 facilitator, students will learn how to: Understand what data works best with Tableau Desktop and how to shape and clean it appropriately to get Learn how to maximize flexibility from Tableau Desktop. Learn how Tableau Prep folds into the analytic cycle, and when to prep data in Tableau Prep vs. Tableau Desktop. Understand the terminology used in Tableau Prep. Know how Tableau Prep approaches data sampling. Create and understand data prep flows that address common scenarios encountered in data preparation, as applied to common data use cases Know how to view data prepared in Tableau Prep using Tableau Desktop. Understand data exploration and validation in Tableau Prep and Tableau Desktop. Geared for experienced Tableau Users, Tableau Prep Building (Tableau Data Prep) for Experienced Users is a two-day hands-on course designed to provide you with the tools and knowledge of how to prepare and shape data in Tableau Prep. It?s best suited for people who have 3-6 months experience in Tableau Desktop and are somewhat familiar with writing calculations. Throughout the course, our instructors will take you from conceptual data preparation material to creating useful Tableau Prep flows that can be output to Tableau Desktop for analysisNOTE: The Tableau Training Series is independent-format training that can be tuned and adjusted to best meet your needs. Our materials are flexible, comprehensive, and are always instructed by a senior instructor with a deep understanding of Tableau and its most current features, benefits and functionality in a wide array of uses. This is not Official Tableau Training. Course Outline Introduction to the workspace Introduction to the workflow Data literacy concepts Connecting to and configuring data Exploring data Cleaning data Preferred data structures in Tableau Shaping data Combining data Opening a data sample and creating an output file Best practices for data preparation Complex flows Starting with a question Hands-on data preparation Additional course details: Nexus Humans Tableau Prep Building (Tableau Data Prep) for Experienced Users (TTDTAB010) 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 Tableau Prep Building (Tableau Data Prep) for Experienced Users (TTDTAB010) 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.

"Learn video marketing essentials for the financial sector—discover what content to create, how to make it on a budget, and where to use it for maximum impact."

On this webinar, we will discuss how market forces impact funds, Real estate investment trusts and private equity firms in Real Estate.

Learn how to use Microsoft Project to create and resource robust project plans and how to maintain and track throughout the project lifecycle. Course overview Duration: 1 day (6.5 hours) Our Project Planning and Control course gives you the essential skills to use Microsoft Project to build, resource and monitor project schedules. It looks at initial setup, building plans, using a work breakdown structure and managing resources through to baselining and progressing your schedule. This course is designed for new or existing users of Microsoft Project, and no previous experience of Project is required. Knowledge of planning techniques would be an advantage. Objectives  By the end of the course you will be able to: Create project schedules Build a Work Breakdown Structure Create relationships Set baselines Manage resources Set deadlines and task properties Print and report on your project Update and track project schedules Content Creating a new project Project defaults Project start date Setting default hours per day/week Setting daily working times Project timeline Building a project Creating a work breakdown structure Adding tasks and durations Estimated durations Setting milestones Recurring tasks Linking, Baselining and Resourcing Setting start dates and dependencies Task Inspector Resourcing Assigning resources Filtering available resources Baseline Setting a baseline Removing a baseline Managing resources Resource properties Dealing with over allocations Tasking information Constraint dates Setting deadline Assigning task specific calendars Task types Updating your project Completing work Completing work per resource Updating tasks Updating the project Rescheduling work Change highlighting Printing and reporting Setup and Printing Visual reports Using the Timeline Creating Dashboard reports

Learn how create and structure enterprise projects and programmes. Course overview Duration: 2 days (13 hours) Our P6 Project Planning and Controls Fundamentals course is an intensive two day course aimed at experienced planners and project controllers who need to use Primavera to create and manage detailed plans. It includes creating EPS levels, projects, WBS levels and detailed activity and resource planning. Experience of project planning and scheduling techniques is essential. Objectives  By the end of the course you will be able to: Create a programme structure Create projects and set project properties Create programme milestones Create a Work Breakdown Structure (WBS) Create detailed plans including activities, links and resources Progress the schedule Manage actuals Customise layouts Use the reporting tools in Primavera Content Programme Management Creating EPS elements Defining the programme structure Navigating the EPS structure Finding programmes Project Management and WBS Creating projects Setting project properties Validating projects Assigning project codes Building a work breakdown structure Creating a WBS structure Creating WBS elements Work package management Top Down budgets Allocating top down budgets Budget change Programming milestones and activity planning Creating programme milestones Setting constraints Linking milestones Scheduling Using the schedule function Detailed activity planning Creating activities Relationship types Creating relationships Adding milestones Assigning activity codes Resourcing, workloads and baselining Resource types Creating resources Resource attributes Assigning resources Switching resources Split load resource assignment Reduced hours resource assignment Checking workload Reviewing workload Dealing with resource conflicts Assignments view Baselining Creating baselines Assigning baselines Working with layouts Creating layouts Customising columns Setting filters Sorting and grouping Changing the timescale Customising the Gantt Creating activity code breakdown structures Progressing the schedules Updating task status and remaining duration Setting the data date Monitoring and reporting Exporting and importing information Primavera standard reports Creating custom reports Creating portfolios Printing Printing your schedule Printing to other packages