Duration 5 Days 30 CPD hours This course is intended for Telco cloud system administrators and telco network operations engineers Professionals who work with telco or enterprise and data center networks Designers and operations engineers who manage telco workloads Overview By the end of the course, you should be able to meet the following objectives: List VMware Telco Cloud Automation deployment options and procedures Describe the VMware Telco Cloud Automation infrastructure settings Configure Containers as a Service (CaaS) functionality Describe partner integration options and procedures Define zero-touch provisioning and describe infrastructure deployment Instantiate network services and network functions Describe the authorization model of VMware Telco Cloud Automation Define platform life cycle management (LCM) for VMware Telco Cloud Automation Enumerate troubleshooting concepts and day-two operations for VMware Telco Cloud Automation Describe the use of APIs within VMware Telco Cloud Automation List examples of how VMware Telco Cloud Automation can be used in a CICD environment This five-day, hands-on training course provides you with the advanced knowledge, skills, and tools to achieve competency in operating and troubleshooting the VMware Telco Cloud AutomationTM environment. In this course, you are introduced to VMware Telco Cloud Automation infrastructure settings, deployment options, and procedures. You explore Containers as a Service and understand the workflow details of Partner Integration processes. You are introduced to zero-touch provisioning and its importance in VMware Telco Cloud Automation. You onboard and instantiate network functions and network services using hands-on lab exercises. Course Introduction Introductions and course logistics Course objectives VMware Telco Cloud Automation Installation Describe day-zero operations for VMware Telco Cloud Automation Describe the VMware Telco Cloud Automation architecture List the steps to perform VMware Telco Cloud Automation deployment List the steps to perform VMware Telco Cloud Automation control plane integration Describe VMware Telco Cloud Automation control plane scaling Describe the requirements on other applications such as VMware vRealize© Orchestrator? and Harbor Describe where, when, and how to use VMware Telco Cloud Automation tagging Day One Operations: Infrastructure Settings Describe the VMware Telco Cloud Automation infrastructure options Describe VMware Telco Cloud Automation infrastructure requirements Outline the role of virtual infrastructure and TCA Identify the benefits of public versus private infrastructure List the steps to integrate a VM-based virtual infrastructure List the steps to integrate a container-based virtual infrastructure Describe private infrastructure requirements Day One Operations: Containers as a Service Define Containers as a Service (CaaS) List the challenges of CNF deployment without automation Describe the Kubernetes and VMware Tanzu? Kubernetes Grid? architectures Describe supporting technologies like Cluster API List steps to create a Kubernetes cluster template Describe the process for deploying node pools and groups Describe cluster monitoring List CaaS scale options Day One Operations: Partner Integration Describe partner integration and the types of partners Describe Harbor and the various Harbor platforms List the steps to interface with a Harbor platform Compare and contrast specialized VNF managers (S-VNFMs) and generic VNF managers (G-VNFMs) Explain how to add an S-VNFM Define S-VNFM use cases Day One Operations: Zero Touch Provisioning and Infrastructure Deployment Describe zero-touch provisioning List the use cases of zero-touch provisioning List the benefits of zero-touch provisioning Describe the infrastructure requirements of zero-touch provisioning Describe the zero-touch provisioning domains List the steps to deploy an infrastructure using zero-touch provisioning Day One Operations: Network Functions ad Network Services Describe the roles of network services and network functions List the types of descriptors Describe the role of TOSCA Describe the role of onboarding List the steps to onboard network functions and network services Examine the results of the onboarding process List the steps to instantiate network functions and network services Examine the results of the instantiation process Day Two Operations: Authorization Model Explain the resources that can be accessed in vSphere Define the role of a VMware vCenter Server© system in credential management Describe the procedures to create, delete, and modify rules using vCenter Server Explain how to control and verify access to vSphere resources List roles in VMware Telco Cloud Automation Explain the tasks and list the levels of permissions needed in VMware Telco Cloud Automation List all the permissions and filters that can be implemented in VMware Telco Cloud Automation Summarize the role-based access control model of VMware Telco Cloud Automation Day Two Operations: Platform Life Cycle Management Explain the life cycle stages in VMware Telco Cloud Automation control plane Explain the life cycle stages in VMware Telco Cloud Automation Define an upgrade schedule Apply an upgrade schedule to manage life cycle management of the VMware Telco Cloud Automation control plane Apply an upgrade schedule to manage life cycle management of VMware Telco Cloud Automation Describe network function and network service life cycle management events Execute network function and network service healing Set up Network Function and Network Service monitoring Perform Network Function and Network Service termination Day Two Operations: Troubleshooting List the components of the VMware Telco Cloud Automation dashboard Explain the features of fault management in VMware Telco Cloud Automation Explain the features of performance management in VMware Telco Cloud Automation Describe the use of fault management of VMware Telco Cloud Automation for VNFs and CNFs Describe the use of performance management of VMware Telco Cloud Automation for VNFs and CNFs Troubleshoot using tcf_manager, app.log, and web.log Define the procedures to integrate VMware vRealize© Operations Manager? with VMware Telco Cloud Automation Usage of VMware vRealize© Operations? Day Two Operations: API Management Define the VMware Telco Cloud Automation API Explain the API architecture Describe VMware Telco Cloud Automation API use cases Explain how to configure an external REST API Describe how to request security tokens for implementation Explain how to implement commands through external systems using APIs Day Two Operations: Continuous Integration and Continuous Delivery Describe continuous integration and continuous delivery (CICD) List the benefits and challenges of CICD Describe how VMware Telco Cloud Automation can be used in a CICD environment Explore VMware Telco Cloud Automation CICD examples
Duration 1 Days 6 CPD hours This course is intended for New administrators, business analysts or report writers who are new to creating reports or dashboards within Salesforce. Overview A student in this class will learn the basic Salesforce object model, and how to create and secure reports and dashboards. The instructor will lead students through exercises to create tabular, summary, matrix and join reports. Students will learn advanced reporting functionality such as charting, report summary fields, bucket fields, conditional highlighting, advanced report filters and building custom report types. Finally, the student will learn how to create and run dashboards and schedule and email reports and dashboards. This course is specifically designed to teach administrators, business analysts or report writers how to utilize the basic and advanced analytic capabilities of Salesforce. Introductions / Login to Training OrgsOverview of Salesforce Object ModelTabular, Summary, Matrix, Join ReportsCharts, Bucket Fields, Report Summary Fields, Conditional HighlightingCustom Report TypesDashboardsReport & Dashboard Scheduling Additional course details: Nexus Humans Introduction to Salesforce.com Analytics - Building Reports and Dashboards 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 Introduction to Salesforce.com Analytics - Building Reports and Dashboards 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.
There is a lot to learn in Power BI, this course takes a comprehensive look at the fundamentals of analysing data and includes a balanced look at the four main components that make up Power BI Desktop: Report view, Data view, Model view, and the Power Query Editor. It also demonstrates how to utilise the online Power BI service. It looks at authoring tools that enable you to connect to and transform data from a variety of sources, allowing you to produce detailed reports through a range of visualisations, in an interactive and dynamic way. It also includes a detailed look at formulas by writing both M functions in Power Query, and DAX functions in Desktop view. This knowledge will allow you to take your reports to the next level. The aim of this course is to provide a complete introduction to understanding the Power BI analysis process, by working hands-on with examples that will equip you with the necessary skills to start applying your learning straight away. 1 Getting Started The Power BI ecosystem Opening Power BI Desktop Power BI's four views Introduction to Dashboards 2 Importing Files Importing data sources Importing an Excel file Importing a CSV file Importing a database Connect to an SQL Server Database Import vs. Direct Query Importing from the web Importing a folder of files Managing file connections 3 Shape Data in the Query Editor The process of shaping data Managing data types Keeping and removing rows Add a custom column Appending tables together Hiding queries in reports Fixing error issues Basic maths operations 4 The Data Model Table relationships Relationship properties 5 Merge Queries Table join kinds Merging tables 6 Inserting Dashboard Visuals Things to keep in mind Inserting maps Formatting Maps Inserting charts Formatting Charts Inserting a tree map Inserting a table, matrix, and card Controlling number formats About report themes Highlighting key points Filter reports with slicers Sync slicers across dashboards Custom web visuals 7 Publish and share Reports Publishing to Power BI service Editing online reports Pinning visuals to a dashboard What is Q&A? Sharing dashboards Exporting reports to PowerPoint Exporting reports as PDF files 8 The Power Query Editor Fill data up and down Split column by delimiter Add a conditional column More custom columns Merging columns 9 The M Functions Inserting text functions Insert an IF function Create a query group 10 Pivoting Tables Pivot a table Pivot and append tables Pivot but don't aggregate Unpivot tables Append mismatched headers 11 Data Modelling Expanded Understanding relationships Mark a date table 12 DAX New Columns New columns and measures New column calculations Insert a SWITCH function 13 Introduction to DAX Measures Common measure functions Insert a SUM function Insert a COUNTROWS function Insert a DISTINCTCOUNT function Insert a DIVIDE function DAX rules 14 The CALCULATE Measure The syntax of CALCULATE Insert a CALCULATE function Control field summarisation Things of note 15 The SUMX measure X iterator functions Anatomy of SUMX Insert a SUMX function When to use X functions 16 Time Intelligence Measures Importance of a calendar table Insert a TOTALYTD function Change financial year end date Comparing historical data Insert a DATEADD function 17 Hierarchies and Groups Mine data using hierarchies Compare data in groups
Duration 3 Days 18 CPD hours This course is intended for This course is designed for network and software engineers who hold the following job roles: Network engineer Systems engineer Wireless engineer Consulting systems engineer Technical solutions architect Network administrator Wireless design engineer Network manager Site reliability engineer Deployment engineer Sales engineer Account manager Overview After taking this course, you should be able to: Leverage the tools and APIs to automate Cisco ACI powered data centers. Demonstrate workflows (configuration, verification, healthchecking, monitoring) using Python, Ansible, and Postman. Leverage the various models and APIs of the Cisco Nexus OS platform to perform day 0 operations, improve troubleshooting methodologies with custom tools, augment the CLI using scripts, and integrate various workflows using Ansible and Python. Describe the paradigm shift of Model Driven Telemetry and understand the building blocks of a working solution. Describe how the Cisco Data Center compute solutions can be managed and automated using API centric tooling, by using the Python SDK, PowerTool, and Ansible modules to implement various workflows on Cisco UCS, Cisco IMC, Cisco UCS Manager, Cisco UCS Director, and Cisco Intersight. The Implementing Automation for Cisco Data Center Solutions (DCAUI) v1.1 course teaches you how to implement Cisco© Data Center automated solutions including programming concepts, orchestration, and automation tools. Through a combination of lessons and hands-on practice, you will manage the tools and learn the benefits of programmability and automation in the Cisco-powered Data Center. You will examine Cisco Application Centric Infrastructure (Cisco ACI©), Software-Defined Networking (SDN) for data center and cloud networks, Cisco Nexus© (Cisco NX-OS) platforms for device-centric automation, and Cisco Unified Computing System (Cisco UCS©) for Data Center compute. You will study their current ecosystem of Application Programming Interfaces (APIs), software development toolkits, and relevant workflows along with open industry standards, tools, and APIs, such as Python, Ansible, Git, JavaScript Object Notation (JSON), Yaml Ain't Markup Language (YAML), Network Configuration Protocol (NETCONF), Representational State Transfer Configuration Protocol (RESTCONF), and Yet Another Generation (YANG).This course prepares you for the 300-635 Automating Cisco Data Center Solutions (DCAUTO) certification exam. Introducing Automation for Cisco Solutions (CSAU) is required prior to enrolling in Implementing Automation for Cisco Data Center Solutions (DCAUI) because it provides crucial foundational knowledge essential to success. This course also earns you 24 Continuing Education (CE) credits towards recertification. Course Outline Describing the Cisco ACI Policy Model Describing the Cisco APIC REST API Using Python to Interact with the ACI REST API Using Ansible to Automate Cisco ACI Introducing Cisco NX-OS Programmability Describing Day-Zero Provisioning with Cisco NX-OS Implementing On-Box Programmability and Automation with Cisco NX-OS Implementing Off-Box Programmability and Automation with Cisco NX-OS Automating Cisco UCS Using Developer Tools Implementing Workflows Using Cisco UCS Director Describing Cisco DCNM Describing Cisco Intersight Additional course details: Nexus Humans Cisco Implementing Automation for Cisco Data Center Solutions (DCAUI) v1.1 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 Cisco Implementing Automation for Cisco Data Center Solutions (DCAUI) v1.1 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 1 Days 6 CPD hours This course is intended for This course is intended for the following participants:Cloud professionals interested in taking the Data Engineer certification exam.Data engineering professionals interested in taking the Data Engineer certification exam. Overview This course teaches participants the following skills: Position the Professional Data Engineer Certification Provide information, tips, and advice on taking the exam Review the sample case studies Review each section of the exam covering highest-level concepts sufficient to build confidence in what is known by the candidate and indicate skill gaps/areas of study if not known by the candidate Connect candidates to appropriate target learning This course will help prospective candidates plan their preparation for the Professional Data Engineer exam. The session will cover the structure and format of the examination, as well as its relationship to other Google Cloud certifications. Through lectures, quizzes, and discussions, candidates will familiarize themselves with the domain covered by the examination, to help them devise a preparation strategy. Rehearse useful skills including exam question reasoning and case comprehension. Tips and review of topics from the Data Engineering curriculum. Understanding the Professional Data Engineer Certification Position the Professional Data Engineer certification among the offerings Distinguish between Associate and Professional Provide guidance between Professional Data Engineer and Associate Cloud Engineer Describe how the exam is administered and the exam rules Provide general advice about taking the exam Sample Case Studies for the Professional Data Engineer Exam Flowlogistic MJTelco Designing and Building (Review and preparation tips) Designing data processing systems Designing flexible data representations Designing data pipelines Designing data processing infrastructure Build and maintain data structures and databases Building and maintaining flexible data representations Building and maintaining pipelines Building and maintaining processing infrastructure Analyzing and Modeling (Review and preparation tips) Analyze data and enable machine learning Analyzing data Machine learning Machine learning model deployment Model business processes for analysis and optimization Mapping business requirements to data representations Optimizing data representations, data infrastructure performance and cost Reliability, Policy, and Security (Review and preparation tips) Design for reliability Performing quality control Assessing, troubleshooting, and improving data representation and data processing infrastructure Recovering data Visualize data and advocate policy Building (or selecting) data visualization and reporting tools Advocating policies and publishing data and reports Design for security and compliance Designing secure data infrastructure and processes Designing for legal compliance Resources and next steps Resources for learning more about designing data processing systems, data structures, and databases Resources for learning more about data analysis, machine learning, business process analysis, and optimization Resources for learning more about data visualization and policy Resources for learning more about reliability design Resources for learning more about business process analysis and optimization Resources for learning more about reliability, policies, security, and compliance Additional course details: Nexus Humans Preparing for the Professional Data Engineer Examination 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 Preparing for the Professional Data Engineer Examination 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.
I’ll share a case of visual hallucinations, showing how an existential-phenomenological approach helps understand their meaning and purpose. We aim to explore the lived experiences on irregular perceptions of reality with an open mind. Each Saturday includes: a live dialogue between Prof. Ernesto Spinelli and an International Existential Therapist; a moment to share your thoughts and feelings with the teachers; and a final integration facilitated by Bárbara Godoy. This series of ten dialogues set out to explore the multifaceted dimentions and complexities associated with Existential Therapies. It attempts to engage with various interpretations of insanity through the lens of patients often painful, confounding, and deeply unsettling life experiences. Hallucination- between Prof. Ernesto Spinelli and Prof. Simon du Ploc “The phenomenon of hallucination has been a subject of debate for centuries. It has been suggested that its function was one of revelation or prophesy, and those who hallucinated were often considered to have a ‘sacred’ affliction. In recent times, their function, at least in the West since the Age of Reason, has been often been reduced to primary indicators of schizophrenia and other forms of psychosis. Lumped into the ‘core phenomena’ of schizophrenia, the concern is not so much what they are, or what they mean to the client, or even their content, but their treatment and control. I will present an excerpt from my own clinical practice with a client who presented with distressing visual hallucinations. This piece of work illustrates how approaching such irregular perceptions of reality from an existential-phenomenological perspective can provide a way of understanding their meaning and purpose within a client’s lived experience. I will suggest that such an approach also enables us to take a creative position regarding wider notions of sanity and madness, a position which enables us to navigate a path between, on the one hand, the medical model which typically focusses on reduction and management of hallucinations, and on the other hand, a Laingian view of hallucination as a route to ‘hyper-sanity’. Adopting such a path may enable us to work more confidently with clients when they present with unusual or disturbing perceptions.” Prof. Simon du Ploc. Prof. Simon du Plock is Senior Research Fellow at the Metanoia Institute, London. He was Head of the Faculty of Post-Qualification and Professional Doctorates at the Institute from 2007 to 2020, in which role he directed counselling psychology and psychotherapy research doctorates jointly with Middlesex University. He is a Fellow of the Royal Society for Medicine, a Foundation Member with Senior Practitioner Status of the BPS Register of Psychologists Specialising in Psychotherapy, and a Member of the BPS Register of Applied Psychology Practice Supervisors. He has been a BPS Chartered Counselling Psychologist and UKCP Registered Psychotherapist since 1994. He has authored nearly one hundred journal papers and book chapters on existential therapy, and he has co-edited Existential Analysis, the Journal of the British Society for Existential Analysis, since 1993. He was an editor of the 2019 Wiley World Handbook of Existential Therapy. He has lectured and trained internationally, and in 2006 he was made an Honorary Member of the East European Association for Existential Therapy in recognition of his contribution to cooperation between West and East Europe in the development of existential psychotherapy. His clinical and research interests include phenomenological research methodology, clinical and research supervision, existential pedagogy, and working with issues of addiction and dependency. Prof. Ernesto Spinelli was Chair of the Society for Existential Analysis between 1993 and 1999 and is a Life Member of the Society. His writings, lectures and seminars focus on the application of existential phenomenology to the arenas of therapy, supervision, psychology, and executive coaching. He is a Fellow of the British Psychological Society (BPS) as well as an APECS accredited executive coach and coaching supervisor. In 2000, he was the Recipient of BPS Division of Counselling Psychology Award for Outstanding Contribution to the Profession. And in 2019, Ernesto received the BPS Award for Distinguished Contribution to Practice. His most recent book, Practising Existential Therapy: The Relational World 2nd edition (Sage, 2015) has been widely praised as a major contribution to the advancement of existential theory and practice. Living up to the existential dictum that life is absurd, Ernesto is also the author of an on-going series of Private Eye novels. Date and Time: Saturday 15 November from 2 pm to 3 pm – (UK time) Individual Dialogue Fee: £70 Venue: Online Zoom FULL PROGRAMME 2025: 25 January “Knots” with Prof. Ernesto Spinelli and Bárbara Godoy 22 February “Healing” with Dr. Michael Guy Thompson and Prof. Ernesto Spinelli 22 March “Difference” with Prof. Tod DuBose and Prof. Ernesto Spinelli 12 April “Polarisation” with Prof. Kirk Schneider and Prof. Ernesto Spinelli 3 May “Character” with Prof. Robert Romanyshyn and Prof. Ernesto Spinelli 21 June “Opening” with Dr. Yaqui Martinez and Prof. Ernesto Spinelli 19 July “Meaning” with Dr. Jan Resnick and Prof. Ernesto Spinelli 25 October “Invention” with Dr. Betty Cannon and Prof. Ernesto Spinelli 15 November “Hallucination” with Prof. Simon du Plock and Prof. Ernesto Spinelli 13 December “Hysteria” with Bárbara Godoy and Prof. Ernesto Spinelli Read the full programme here > Course Organised by:
Duration 2 Days 12 CPD hours Overview Understand why Blockchain is needed and where Explore the major components of BlockchainLearn about Hyperledger Fabric and the structure of the Hyperledger ArchitectureLean the features of the Fabric model including chaincode, SDKs, Ledger, Security and Membership ServicesPerform comprehensive labs on writing chaincodeExplore the architecture of Hyperledger FabricUnderstand and perform in depth labs on Bootstrapping the NetworkPerform comprehensive labs to integrate/develop an application with Hyperledger Fabric running a smart contractBuild applications on Hyperledger FabricCourse Outline: This training course has been created to walk you through Chaincode Development, Testing, and Deployment for a Hyperledger Fabric Network catering specifically toward Golang written Chaincode (Fabric?s original Chaincode Language). Additionally as an Application Developer you will learn how to write, and prepare Client Applications using the most mature Standard Development Kit in Hyperledger Fabric, NodeJS. Blockchain Basics (Overview)Hyperledger Fabric Development EnvironmentKnowing the Difference: ComposerChaincode Use CasesChaincode BasicsGolang Shim DevelopmentDatabases for the DeveloperChaincode Dev. Deployment and InteractionsClients & SDK Development: Fabric-NetworkClients & SDK Development: Fabric-Client InteractionsLogging and Monitoring
Duration 3 Days 18 CPD hours This course is intended for This course is geared for Python experienced developers, analysts or others who are intending to learn the tools and techniques required in building various kinds of powerful recommendation systems (collaborative, knowledge and content based) and deploying them to the web. Overview Working in a hands-on lab environment led by our expert instructor, attendees will Understand the different kinds of recommender systems Master data-wrangling techniques using the pandas library Building an IMDB Top 250 Clone Build a content-based engine to recommend movies based on real movie metadata Employ data-mining techniques used in building recommenders Build industry-standard collaborative filters using powerful algorithms Building Hybrid Recommenders that incorporate content based and collaborative filtering Recommendation systems are at the heart of almost every internet business today; from Facebook to Net?ix to Amazon. Providing good recommendations, whether its friends, movies, or groceries, goes a long way in defining user experience and enticing your customers to use your platform.This course shows you how to do just that. You will learn about the different kinds of recommenders used in the industry and see how to build them from scratch using Python. No need to wade through tons of machine learning theory?you will get started with building and learning about recommenders as quickly as possible. In this course, you will build an IMDB Top 250 clone, a content-based engine that works on movie metadata. You will also use collaborative filters to make use of customer behavior data, and a Hybrid Recommender that incorporates content based and collaborative filtering techniques.Students will learn to build industry-standard recommender systems, leveraging basic Python syntax skills. This is an applied course, so machine learning theory is only used to highlight how to build recommenders in this course.This skills-focused ccombines engaging lecture, demos, group activities and discussions with machine-based student labs and exercises.. Our engaging instructors and mentors are highly-experienced practitioners who bring years of current, modern 'on-the-job' modern applied datascience, AI and machine learning experience into every classroom and hands-on project. Getting Started with Recommender Systems Technical requirements What is a recommender system? Types of recommender systems Manipulating Data with the Pandas Library Technical requirements Setting up the environment The Pandas library The Pandas DataFrame The Pandas Series Building an IMDB Top 250 Clone with Pandas Technical requirements The simple recommender The knowledge-based recommender Building Content-Based Recommenders Technical requirements Exporting the clean DataFrame Document vectors The cosine similarity score Plot description-based recommender Metadata-based recommender Suggestions for improvements Getting Started with Data Mining Techniques Problem statement Similarity measures Clustering Dimensionality reduction Supervised learning Evaluation metrics Building Collaborative Filters Technical requirements The framework User-based collaborative filtering Item-based collaborative filtering Model-based approaches Hybrid Recommenders Technical requirements Introduction Case study and final project ? Building a hybrid model Additional course details: Nexus Humans Applied AI: Building Recommendation Systems with Python (TTAI2360) 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 Applied AI: Building Recommendation Systems with Python (TTAI2360) course and one of our Top 10 we encourage you to read the course outline to make sure it is the right content for you. Additionally, private sessions, closed classes or dedicated events are available both live online and at our training centres in Dublin and London, as well as at your offices anywhere in the UK, Ireland or across EMEA.
Duration 3 Days 18 CPD hours This course is intended for This course is geared for Python experienced developers, analysts or others who are intending to learn the tools and techniques required in building various kinds of powerful recommendation systems (collaborative, knowledge and content based) and deploying them to the web. Overview This skills-focused combines engaging lecture, demos, group activities and discussions with machine-based student labs and exercises.. Our engaging instructors and mentors are highly-experienced practitioners who bring years of current, modern 'on-the-job' modern applied datascience, AI and machine learning experience into every classroom and hands-on project. Working in a hands-on lab environment led by our expert instructor, attendees will Understand the different kinds of recommender systems Master data-wrangling techniques using the pandas library Building an IMDB Top 250 Clone Build a content-based engine to recommend movies based on real movie metadata Employ data-mining techniques used in building recommenders Build industry-standard collaborative filters using powerful algorithms Building Hybrid Recommenders that incorporate content based and collaborative filtering Recommendation systems are at the heart of almost every internet business today; from Facebook to Net?ix to Amazon. Providing good recommendations, whether its friends, movies, or groceries, goes a long way in defining user experience and enticing your customers to use your platform.This course shows you how to do just that. You will learn about the different kinds of recommenders used in the industry and see how to build them from scratch using Python. No need to wade through tons of machine learning theory?you will get started with building and learning about recommenders as quickly as possible. In this course, you will build an IMDB Top 250 clone, a content-based engine that works on movie metadata. You will also use collaborative filters to make use of customer behavior data, and a Hybrid Recommender that incorporates content based and collaborative filtering techniques. Students will learn to build industry-standard recommender systems, leveraging basic Python syntax skills. This is an applied course, so machine learning theory is only used to highlight how to build recommenders in this course. Getting Started with Recommender Systems Technical requirements What is a recommender system? Types of recommender systems Manipulating Data with the Pandas Library Technical requirements Setting up the environment The Pandas library The Pandas DataFrame The Pandas Series Building an IMDB Top 250 Clone with Pandas Technical requirements The simple recommender The knowledge-based recommender Building Content-Based Recommenders Technical requirements Exporting the clean DataFrame Document vectors The cosine similarity score Plot description-based recommender Metadata-based recommender Suggestions for improvements Getting Started with Data Mining Techniques Problem statement Similarity measures Clustering Dimensionality reduction Supervised learning Evaluation metrics Building Collaborative Filters Technical requirements The framework User-based collaborative filtering Item-based collaborative filtering Model-based approaches Hybrid Recommenders Technical requirements Introduction Case study and final project ? Building a hybrid model Additional course details: Nexus Humans Building Recommendation Systems with Python (TTAI2360) 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 Building Recommendation Systems with Python (TTAI2360) 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.