Duration 3 Days 18 CPD hours This course is intended for This course is geared for attendees with solid Python skills who wish to learn and use basic machine learning algorithms and concepts 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. Topics Covered: This is a high-level list of topics covered in this course. Please see the detailed Agenda below Getting Started & Optional Python Quick Refresher Statistics and Probability Refresher and Python Practice Probability Density Function; Probability Mass Function; Naive Bayes Predictive Models Machine Learning with Python Recommender Systems KNN and PCA Reinforcement Learning Dealing with Real-World Data Experimental Design / ML in the Real World Time Permitting: Deep Learning and Neural Networks Machine Learning Essentials with Python is a foundation-level, three-day hands-on course that teaches students core skills and concepts in modern machine learning practices. This course is geared for attendees experienced with Python, but new to machine learning, who need introductory level coverage of these topics, rather than a deep dive of the math and statistics behind Machine Learning. Students will learn basic algorithms from scratch. For each machine learning concept, students will first learn about and discuss the foundations, its applicability and limitations, and then explore the implementation and use, reviewing and working with specific use casesWorking in a hands-on learning environment, led by our Machine Learning expert instructor, students will learn about and explore:Popular machine learning algorithms, their applicability and limitationsPractical application of these methods in a machine learning environmentPractical use cases and limitations of algorithms Getting Started Installation: Getting Started and Overview LINUX jump start: Installing and Using Anaconda & Course Materials (or reference the default container) Python Refresher Introducing the Pandas, NumPy and Scikit-Learn Library Statistics and Probability Refresher and Python Practice Types of Data Mean, Median, Mode Using mean, median, and mode in Python Variation and Standard Deviation Probability Density Function; Probability Mass Function; Naive Bayes Common Data Distributions Percentiles and Moments A Crash Course in matplotlib Advanced Visualization with Seaborn Covariance and Correlation Conditional Probability Naive Bayes: Concepts Bayes? Theorem Naive Bayes Spam Classifier with Naive Bayes Predictive Models Linear Regression Polynomial Regression Multiple Regression, and Predicting Car Prices Logistic Regression Logistic Regression Machine Learning with Python Supervised vs. Unsupervised Learning, and Train/Test Using Train/Test to Prevent Overfitting Understanding a Confusion Matrix Measuring Classifiers (Precision, Recall, F1, AUC, ROC) K-Means Clustering K-Means: Clustering People Based on Age and Income Measuring Entropy LINUX: Installing GraphViz Decision Trees: Concepts Decision Trees: Predicting Hiring Decisions Ensemble Learning Support Vector Machines (SVM) Overview Using SVM to Cluster People using scikit-learn Recommender Systems User-Based Collaborative Filtering Item-Based Collaborative Filtering Finding Similar Movie Better Accuracy for Similar Movies Recommending movies to People Improving your recommendations KNN and PCA K-Nearest-Neighbors: Concepts Using KNN to Predict a Rating for a Movie Dimensionality Reduction; Principal Component Analysis (PCA) PCA with the Iris Data Set Reinforcement Learning Reinforcement Learning with Q-Learning and Gym Dealing with Real-World Data Bias / Variance Tradeoff K-Fold Cross-Validation Data Cleaning and Normalization Cleaning Web Log Data Normalizing Numerical Data Detecting Outliers Feature Engineering and the Curse of Dimensionality Imputation Techniques for Missing Data Handling Unbalanced Data: Oversampling, Undersampling, and SMOTE Binning, Transforming, Encoding, Scaling, and Shuffling Experimental Design / ML in the Real World Deploying Models to Real-Time Systems A/B Testing Concepts T-Tests and P-Values Hands-on With T-Tests Determining How Long to Run an Experiment A/B Test Gotchas Capstone Project Group Project & Presentation or Review Deep Learning and Neural Networks Deep Learning Prerequisites The History of Artificial Neural Networks Deep Learning in the TensorFlow Playground Deep Learning Details Introducing TensorFlow Using TensorFlow Introducing Keras Using Keras to Predict Political Affiliations Convolutional Neural Networks (CNN?s) Using CNN?s for Handwriting Recognition Recurrent Neural Networks (RNN?s) Using an RNN for Sentiment Analysis Transfer Learning Tuning Neural Networks: Learning Rate and Batch Size Hyperparameters Deep Learning Regularization with Dropout and Early Stopping The Ethics of Deep Learning Learning More about Deep Learning Additional course details: Nexus Humans Machine Learning Essentials with Python (TTML5506-P) 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 Machine Learning Essentials with Python (TTML5506-P) 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 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
Learn how to use this innovative tool to analyse and validate your schedule, to add and model uncertainty and risk and to work with updated plans to compare project progress. Course overview Duration: 1 day (6.5 hours) This course looks at the powerful features of Nodes and Links. It looks at analysing and validating your schedule, adding uncertainty and risk and working with updated plans to compare project progress. Hands on practice will be gained throughout the course to ensure you can confidentially put your new skills into practice back in the workplace. This course is designed for new users of Nodes and links, no previous experience is required. You should however be familiar with risk management processes and terminology. Objectives By the end of the course you will be able to: Import and validate plans Analyse and review plans Add and model uncertainty Add and model risk Load updated schedules Re run analysis on updated schedules Content Validating your plan Importing a baseline plan Running a health check Analysing the results Reviewing the plan Analysing critical paths Reviewing activities Reviewing resources Adding Uncertainty Setting uncertainty templates Distributions Adding uncertainty Using Inherit Using AI Reviewing activity distributions Modelling Uncertainty Running the Analysis Reviewing the results Reviewing activity results Risk Drivers Filtering for activities Setting up the Risk Register Setting Risk Templates Adding Risks to the Risk Register Independent vs Dependant Events Setting Probability and Impact Modelling Uncertainty and Risk Mapping risks to activities Running the Analysis Reviewing the results Updated Plans Importing a new plan version Comparing plans Tracking progress Trend analysis Analysing Updated Plans Using updated plans Synchronising uncertainly and risk Rerunning analysis
This course is very much a discussion, so be prepared to present and critically analyse your own and class mates work. You will also need to bring a few examples of work you have done in the past. Learning and applying best practice visualisation principles will improve effective discussions amongst decision makers throughout your organisation. As a result more end-users of your dashboards will be able to make better decisions, more quickly. This 2 Day training course is aimed at analysts with good working knowledge of BI tools (we use Tableau to present, but attendees can use their own software such as Power BI or Qlik Sense). It is a great preparation for taking advanced certifications, such as Tableau Certified Professional. Contact us to discuss the Visual Analytics Best Practice course Email us if you are interested in an on-site course, or would be interested in different dates and locations This Tableau Desktop training intermediate course is designed for the professional who has a solid foundation with Tableau and is looking to take it to the next level. Attendees should have a good understanding of the fundamental concepts of building Tableau worksheets and dashboards typically achieved from having attended our Tableau Desktop Foundation Course. At the end of this course you will be able to communicate insights more effectively, enabling your organisation to make better decisions, quickly. The Tableau Desktop Analyst training course is aimed at people who are used to working with MS Excel or other Business Intelligence tools and who have preferably been using Tableau already for basic reporting. The course includes the following topics: WHAT IS VISUAL ANALYSIS? Visual Analytics Visual Analytics Process Advantages of Visual Analysis Exercise: Interpreting Visualisations HOW DO WE PROCESS VISUAL INFORMATION? Memory and Processing Types Exercise: Identifying Types of Processing Cognitive Load Exercise: Analysing Cognitive Load Focus and Guide the Viewer Remove Visual Distractions Organise Information into Chunks Design for Proximity Exercise: Reducing Cognitive Load SENSORY MEMORY Pre-attentive Attributes Quantitatively-Perceived Attributes Categorically-Perceived Attributes Exercise: Analysing Pre-attentive Attributes Form & Attributes Exercise: Using Form Effectively Colour & Attributes Exercise: Using Colour Effectively Position & Attributes Exercise: Using Position Effectively ENSURING VISUAL INTEGRITY Informing without Misleading Gestalt Principles Visual Area Axis & Scale Colour Detail Exercise: Informing without Misleading CHOOSING THE RIGHT VISUALISATION Comparing and Ranking Categories Comparing Measures Comparing Parts to Whole Viewing Data Over Time Charts Types for Mapping Viewing Correlation Viewing Distributions Viewing Specific Values DASHBOARDS AND STORIES Exercise: Picking the Chart Type Exercise: Brainstorming Visual Best Practice Development Process for Dashboards and Stories Plan the Visualisation Create the Visualisation Test the Visualisation Exercise: Designing Dashboards and Stories This training course includes over 20 hands-on exercises to help participants “learn by doing” and to assist group discussions around real-life use cases. Each attendee receives an extensive training manual which covers the theory, practical applications and use cases, exercises and solutions together with a USB with all the materials required for the training. The course starts at 09:30 on the first day and ends at 17:00. On the second day the course starts at 09:00 and ends at 17:00. Students must bring their own laptop with an active version of Tableau Desktop 10.5 (or later) pre-installed. What People Are Saying About This Course "Steve was willing to address questions arising from his content in a full and understandable way"Lisa L. "Really enjoyed the course and feel the subject and the way it was taught was very close to my needs"James G. "The course tutor Steve was incredibly helpful and taught the information very well while making the two days very enjoyable."Bradd P. "The host and his courses will give you the tools and confidence that you need to be comfortable with Tableau."Jack S. "Steve was fantastic with his knowledge and knowhow about the product. Where possible he made sure you could put demonstrations in to working practice, to give the audience a clear understanding."Tim H. "This was a very interesting and helpful course, which will definitely help me produce smarter, cleaner visualisations that will deliver more data-driven insights within our business."Richard A. "Steve is very open to questions and will go out of his way to answer any query. Thank you"Wasif N. "Steve was willing to address questions arising from his content in a full and understandable way"Lisa L. "Really enjoyed the course and feel the subject and the way it was taught was very close to my needs"James G.
SAP Training London: Overview What is SAP? SAP is one of the largest ERP(Enterprise Resource Planning) software in the world. It provides end to end solution for Financials, Manufacturing, Logistics, Distributions etc. SAP applications, built around their latest R/3 system, provide the capability to manage financial, asset, and cost accounting, production operations and materials, personnel, plants, and archived documents. The R/3 system runs on a number of platforms including Windows and MAC and uses the client/server model. SAP Business Cases/ Live Project Our SAP training courses are designed in a way which gives the students maximum exposure of real-life scenario through no of business cases and guidance on implementation by professional SAP Consultants. Free SAP Access Free SAP Sandbox Access provided for 6 months so that you can practice even after your SAP training course. Certificate of Attendance- You receive a certificate once you finish the course from Osborne Training, You can also do an external exam to receive certification from SAP (Optional), for details on exam booking you may visit the SAP website. SAP Training Modules Available Financial & Controlling (FICO) High-Performance Analytic Appliance (HANA) Supply Relationship Management (SRM) Customer Relationship Management (CRM)
SAP Courses Overview SAP is one of the largest ERP(Enterprise Resource Planning) software in the world. It provides end to end solution for Financials, Manufacturing, Logistics, Distributions etc. SAP applications, built around their latest R/3 system, provide the capability to manage financial, asset, and cost accounting, production operations and materials, personnel, plants, and archived documents. The R/3 system runs on a number of platforms including Windows and MAC and uses the client/server model. SAP Business Cases/ Live Project Our SAP training courses are designed in a way which gives the students maximum exposure of real-life scenario through no of business cases and guidance on implementation by professional SAP Consultants. Certificate of Attendance- You receive a certificate once you finish the course from Osborne Training, SAP Certification During the training, you get access to the SAP sandbox which continues even after training finishes until the completion of the Internship. You can also do an external exam to receive certification from SAP (Optional), for details on exam booking you may visit the SAP website. SAP Training Modules Available Financial & Controlling (FICO) High-Performance Analytic Appliance (HANA) Supply Relationship Management (SRM) Customer Relationship Management (CRM) Free SAP Access Free SAP Sandbox Access provided for 6 months so that you can practice even after your SAP training course.
SAP Training: Overview What is SAP? SAP is one of the largest ERP(Enterprise Resource Planning) software in the world. It provides end to end solution for Financials, Manufacturing, Logistics, Distributions etc. SAP applications, built around their latest R/3 system, provide the capability to manage financial, asset, and cost accounting, production operations and materials, personnel, plants, and archived documents. The R/3 system runs on a number of platforms including Windows and MAC and uses the client/server model. SAP Business Cases/ Live Project Our SAP training courses are designed in a way which gives the students maximum exposure of real-life scenario through no of business cases and guidance on implementation by professional SAP Consultants. You receive a certificate once you finish the course from Osborne Training. SAP Certification During the training, you get access to Sap sandbox which continues even after training finishes until the completion of the Internship. You can also do an external exam to receive certification from SAP (Optional), for details on exam booking you may visit the SAP website. SAP Training Modules Available Financial & Controlling (FICO) High-Performance Analytic Appliance (HANA) Supply Relationship Management (SRM) Customer Relationship Management (CRM)
Overview This is a 2 day applied course on XVA for anyone interested in going beyond merely a conceptual understanding of XVA and wants practical examples of Monte Carlo simulation of market risk factors to create exposure distributions and profiles for derivatives used for XVA pricing Learn how to do Monte Carlo simulation of key market risk factors across major asset classes to create exposure distributions and profiles (with and without collateral) for derivatives used for XVA pricing. Learn how to calculate each XVA. Learn sensitivities of each XVA and how XVA desks manage these. Learn regulatory capital treatment of counterparty credit risk (both for CCR and CVA volatility) and how to stress test this within ICAAP or system-wide external, supervisor-led capital stress test. Who the course is for Anyone involved in OTC derivatives XVA traders XVA quants Derivatives traders and salespeople Risk management Treasury staff Internal audit and finance Course Content To learn more about the day by day course content please request a brochure To learn more about schedule, pricing & delivery options, book a meeting with a course specialist now
Duration 2 Days 12 CPD hours This course is intended for Application consultants, Business Analysts, Executives, Technology Consultants, Users Overview By the end of this course, students will be able to:Explain SAP LumiraCreate documents and acquire dataPrepare datasetsVisualize dataShare stories In this course, students will learn how to create stunning and interactive visualizations by choosing a rich library of visualization types, ranging from scatter plots, heat and geo maps to tag clouds, box plots and network charts. Course Outline Positioning and Overview of SAP Lumira Discovery Navigating the BI Launchpad Acquiring Data Enrich the Dataset Create Visualizations Create a Story Sharing Options Using the Lumira Discovery Formula Editor Additional Data Sources Data Mashups
Duration 2 Days 12 CPD hours This course is intended for This course is intended for Sales Representatives (SR), Sales Managers and End-users who have an interest in the Sales components of Dynamics 365. Students should have an existing working knowledge of either Microsoft Dynamics 365 or Microsoft Dynamics CRM. As a minimum, students should attend the prerequisite course Introduction to Microsoft Dynamics 365 Overview Understand the features and tools that exist in Microsoft Dynamics 365 for SR?s and Sales Managers. Be familiar with the stages of the Sales Order. Process in Microsoft Dynamics 365. Understand the fundamentals of Lead and Opportunity Management. Be able to track, manage, qualify Leads and convert to Opportunities and related customer records in Microsoft Dynamics 365. Know how to disqualify and cancel Leads, and convert Activity records to Leads and Opportunities. Understand how to collaborate on Opportunities with other SR?s and close Opportunity records as Won and Lost. Be able to track Competitors and Stakeholders. Understand how to view Resolution Activities. Add Products and Write-In Products to Opportunities. Build and maintain a repository of Products, Product Bundles and Product Families in the Product Catalog. Configure Unit Groups, Price Lists and Discount Lists. Work with Product Properties and view a Product Hierarchy. Create Quotes and add Products. Work with the Sales Order Process to convert Quotes to Orders and Invoices. Fulfill Orders and manage Invoice payments. Explore the Sales Reports and create a custom Sales Report using the Reporting Wizard in Microsoft Dynamics 365. Understand the significance of Sales Goal Management and Metrics in Microsoft Dynamics 365. Explore the Sales Charts and Dashboards and create a custom Sales Dashboard in Microsoft Dynamics 365. This course provides students with a detailed hands-on experience of the Salesfeatures and components of Microsoft Dynamics 365. Introduction Sales Order Process Scenarios An Introduction to Sales in Dynamics 365 The Dynamics 365 Platform Dynamics 365 Sales Fundamentals Security Considerations Where to get Help Further Reading and Resources Lead Management The Lead Management Process Working with Lead Records Working with the Lead Form Lead Assignment Leads and Activities Qualifying a Lead Disqualifying a Lead Opportunities Management Introduction to Opportunities The Opportunity Views The Opportunity Form Opportunity Sales Process Closing an Opportunity Resolution Activities Products Introduction to the Product Catalog Adding Products Configuring Unit Groups Price Lists and Price List Items Quotes, Orders and Invoices Introduction to Order Processing Adding Products to an Opportunity Working with Quotes Working with Orders Working with Invoices Sales Analysis Introduction to Sales Analysis in Dynamics 365 The Sales Reports The Reporting Wizard Working with Sales Charts Working with Sales Dashboards Working with Sales Goals and Metrics