2839 Learning courses in London delivered Live Online

Duration 1 Days 6 CPD hours This course is intended for This course is intended for: A technical audience at an intermediate level Overview Using Amazon SageMaker, this course teaches you how to: Prepare a dataset for training. Train and evaluate a machine learning model. Automatically tune a machine learning model. Prepare a machine learning model for production. Think critically about machine learning model results In this course, learn how to solve a real-world use case with machine learning and produce actionable results using Amazon SageMaker. This course teaches you how to use Amazon SageMaker to cover the different stages of the typical data science process, from analyzing and visualizing a data set, to preparing the data and feature engineering, down to the practical aspects of model building, training, tuning and deployment. Day 1 Business problem: Churn prediction Load and display the dataset Assess features and determine which Amazon SageMaker algorithm to use Use Amazon Sagemaker to train, evaluate, and automatically tune the model Deploy the model Assess relative cost of errors Additional course details: Nexus Humans Practical Data Science with Amazon SageMaker 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 Practical Data Science with Amazon SageMaker course and one of our Top 10 we encourage you to read the course outline to make sure it is the right content for you. Additionally, private sessions, closed classes or dedicated events are available both live online and at our training centres in Dublin and London, as well as at your offices anywhere in the UK, Ireland or across EMEA.

Duration 5 Days 30 CPD hours This course is intended for This intermediate and beyond level course is geared for experienced technical professionals in various roles, such as developers, data analysts, data engineers, software engineers, and machine learning engineers who want to leverage Scala and Spark to tackle complex data challenges and develop scalable, high-performance applications across diverse domains. Practical programming experience is required to participate in the hands-on labs. Overview Working in a hands-on learning environment led by our expert instructor you'll: Develop a basic understanding of Scala and Apache Spark fundamentals, enabling you to confidently create scalable and high-performance applications. Learn how to process large datasets efficiently, helping you handle complex data challenges and make data-driven decisions. Gain hands-on experience with real-time data streaming, allowing you to manage and analyze data as it flows into your applications. Acquire practical knowledge of machine learning algorithms using Spark MLlib, empowering you to create intelligent applications and uncover hidden insights. Master graph processing with GraphX, enabling you to analyze and visualize complex relationships in your data. Discover generative AI technologies using GPT with Spark and Scala, opening up new possibilities for automating content generation and enhancing data analysis. Embark on a journey to master the world of big data with our immersive course on Scala and Spark! Mastering Scala with Apache Spark for the Modern Data Enterprise is a five day hands on course designed to provide you with the essential skills and tools to tackle complex data projects using Scala programming language and Apache Spark, a high-performance data processing engine. Mastering these technologies will enable you to perform a wide range of tasks, from data wrangling and analytics to machine learning and artificial intelligence, across various industries and applications.Guided by our expert instructor, you?ll explore the fundamentals of Scala programming and Apache Spark while gaining valuable hands-on experience with Spark programming, RDDs, DataFrames, Spark SQL, and data sources. You?ll also explore Spark Streaming, performance optimization techniques, and the integration of popular external libraries, tools, and cloud platforms like AWS, Azure, and GCP. Machine learning enthusiasts will delve into Spark MLlib, covering basics of machine learning algorithms, data preparation, feature extraction, and various techniques such as regression, classification, clustering, and recommendation systems. Introduction to Scala Brief history and motivation Differences between Scala and Java Basic Scala syntax and constructs Scala's functional programming features Introduction to Apache Spark Overview and history Spark components and architecture Spark ecosystem Comparing Spark with other big data frameworks Basics of Spark Programming SparkContext and SparkSession Resilient Distributed Datasets (RDDs) Transformations and Actions Working with DataFrames Spark SQL and Data Sources Spark SQL library and its advantages Structured and semi-structured data sources Reading and writing data in various formats (CSV, JSON, Parquet, Avro, etc.) Data manipulation using SQL queries Basic RDD Operations Creating and manipulating RDDs Common transformations and actions on RDDs Working with key-value data Basic DataFrame and Dataset Operations Creating and manipulating DataFrames and Datasets Column operations and functions Filtering, sorting, and aggregating data Introduction to Spark Streaming Overview of Spark Streaming Discretized Stream (DStream) operations Windowed operations and stateful processing Performance Optimization Basics Best practices for efficient Spark code Broadcast variables and accumulators Monitoring Spark applications Integrating External Libraries and Tools, Spark Streaming Using popular external libraries, such as Hadoop and HBase Integrating with cloud platforms: AWS, Azure, GCP Connecting to data storage systems: HDFS, S3, Cassandra, etc. Introduction to Machine Learning Basics Overview of machine learning Supervised and unsupervised learning Common algorithms and use cases Introduction to Spark MLlib Overview of Spark MLlib MLlib's algorithms and utilities Data preparation and feature extraction Linear Regression and Classification Linear regression algorithm Logistic regression for classification Model evaluation and performance metrics Clustering Algorithms Overview of clustering algorithms K-means clustering Model evaluation and performance metrics Collaborative Filtering and Recommendation Systems Overview of recommendation systems Collaborative filtering techniques Implementing recommendations with Spark MLlib Introduction to Graph Processing Overview of graph processing Use cases and applications of graph processing Graph representations and operations Introduction to Spark GraphX Overview of GraphX Creating and transforming graphs Graph algorithms in GraphX Big Data Innovation! Using GPT and Generative AI Technologies with Spark and Scala Overview of generative AI technologies Integrating GPT with Spark and Scala Practical applications and use cases Bonus Topics / Time Permitting Introduction to Spark NLP Overview of Spark NLP Preprocessing text data Text classification and sentiment analysis Putting It All Together Work on a capstone project that integrates multiple aspects of the course, including data processing, machine learning, graph processing, and generative AI technologies.

¡Hola, amigos!  On the 18th 19th and 20th of December (19:30 GMT) we will offer an online free conversation class. 18th December Levels A1 to A2.  We will meet other students, get to know each other and, of course, practice Spanish. Come and meet us! We will be learning some Navidad vocabulary, talks about Spanish and latino traditions and of course we will have lot of fun.  Book your place in our web!  Check the web to know the available days for each level. 

¡Hola, amigos!  On the 18th 19th and 20th of December (19:30 GMT) we will offer an online free conversation class.  20th December Levels C1 to C2.  We will meet other students, get to know each other and, of course, practice Spanish. Come and meet us! We will be learning some Navidad vocabulary, talks about Spanish and latino traditions and of course we will have lot of fun.  Book your place in our web!  Levels: A1 to C2. Check the web to know the available days for each level. 

¡Hola, amigos!  On the 18th 19th and 20th of December (19:30 GMT) we will offer an online free conversation class. We will meet other students, get to know each other and, of course, practice Spanish. 19th December Levels B1 to B2.  Come and meet us! We will be learning some Navidad vocabulary, talks about Spanish and latino traditions and of course we will have lot of fun.  Book your place in our web!  Levels: A1 to C2. Check the web to know the available days for each level. 

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 course benefits individuals responsible for configuring and monitoring devices running the Junos OS. Course Level : Junos Layer 2 VPNs (JL2V) is an advanced-level course. Overview Define the term virtual private network. Describe the business drivers for MPLS VPNs. Describe the differences between Layer 2 VPNs and Layer 3 VPNs. List advantages for the use of MPLS Layer 3 VPNs and Layer 2 VPNs. Describe the roles of a CE device, PE router, and P router in a BGP Layer 2 VPN. Explain the flow of control traffic and data traffic for a BGP Layer 2 VPN. Configure a BGP Layer 2 VPN and describe the benefits and requirements of over-provisioning. Monitor and troubleshoot a BGP Layer 2 VPN. Explain the BGP Layer 2 VPN scaling mechanisms and route reflection. Describe the Junos OS BGP Layer 2 VPN CoS support. Describe the flow of control and data traffic for an LDP Layer 2 circuit. Configure an LDP Layer 2 circuit. Monitor and troubleshoot an LDP Layer 2 circuit. Describe the operation of FEC 129 BGP autodiscovery for Layer 2 VPNs. Configure a FEC 129 BGP autodiscovery Layer 2 VPN. Monitor and troubleshoot a FEC 129 BGP autodiscovery for Layer 2 VPNs. Describe the difference between Layer 2 MPLS VPNs and VPLS. Explain the purpose of the PE device, the CE device, and the P device. Explain the provisioning of CE and PE routers. Describe the signaling process of VPLS. Describe the learning and forwarding process of VPLS. Describe the potential loops in a VPLS environment. Configure BGP, LDP, and FEC 129 BGP autodiscovery VPLS. Troubleshoot VPLS. Describe the purpose and features of Ethernet VPN. Configure Ethernet VPN. Monitor and troubleshoot Ethernet VPN. Describe the Junos OS support for hierarchical VPN models. Describe the Junos OS support for Carrier-of-Carriers VPN Option C. Configure the interprovider VPN Option C. Describe the Junos OS support for multisegment pseudowire for FEC 129. Describe and configure circuit cross-connect (CCC). This two-day course is designed to provide students with MPLS-based Layer 2 virtual private network (VPN) knowledge and configuration examples. Course IntroductionMPLS VPNs MPLS VPNs Provider-Provisioned VPNs BGP Layer 2 VPNs Overview of Layer 2 Provider-Provisioned VPNs BGP Layer 2 VPN Operational Model: Control Plane BGP Layer 2 VPN Operational Model: Data Plane Preliminary BGP Layer 2 VPN Configuration BGP Layer 2 Configuration Monitoring and Troubleshooting BGP Layer 2 VPNs Lab: BGP Layer 2 VPNs Layer 2 VPN Scaling and CoS Review of VPN Scaling Mechanisms Layer 2 VPNs and CoS LDP Layer 2 Circuits LDP Layer 2 Circuit Operation LDP Layer 2 Circuit Configuration LDP Layer 2 Circuit Monitoring and Troubleshooting FEC 129 BGP Autodiscovery Layer 2 Circuit Operation FEC 129 BGP Autodiscovery Layer 2 Circuit Configuration FEC 129 BGP Autodiscovery Monitoring and Troubleshooting Virtual Private LAN Services Layer 2 MPLS VPNs Versus VPLS BGP VPLS Control Plane BGP VPLS Data Plane Learning and Forwarding Process Loops VPLS Configuration VPLS Configuration VPLS Troubleshooting Ethernet VPN (EVPN) EVPN Overview EVPN Control Plane EVPN Operation EVPN Configuration EVPN Troubleshooting

Duration 2 Days 12 CPD hours This course is intended for This introductory-level course is ideal for project managers, team leaders, and collaboration-focused roles who are already familiar with Jira and are looking to integrate Confluence into their project workflows. Overview Throughout the course you will learn to: Master the fundamentals of Confluence, including understanding its history, navigation, and the distinction between pages and blogs. Gain proficiency in creating, editing, copying, moving, and deleting pages, along with managing file directories and executing advanced editing features. Develop the ability to use and create blueprints and templates, aiding in the standardization and productivity enhancement of your team's work. Understand the collaborative features of Confluence such as sharing links, commenting, mentioning, liking, and watching content to promote a culture of teamwork and collaboration in your organization. Learn how to effectively integrate Confluence with Jira, linking issues and filters, and using auto-links for smoother project management. OPTIONAL: Acquire skills in Confluence administration, including managing notifications and watchers, linking to other applications, customizing the look and feel of your workspace, and creating various types of spaces (public, private, team, etc.) Boost your project management and team collaboration skills with our hands-on, interactive course, Getting Started with Confluence (with Jira). Confluence, as a powerful project collaboration tool, seamlessly integrates with Jira, allowing you to create, share, and collaborate on projects in a more efficient and visually appealing way. This course will equip you with the skills to manage projects, improve workflow efficiency, and promote transparency in your organization. You will gain practical knowledge about Confluence's core features such as creating and editing pages, managing file directories, using tasks, macros, and gadgets, and differentiating between pages and blogs.Working in a hands-on learning environment guided by our expert instructor, you?ll gain experience with Confluence's unique features like using and creating blueprints and templates, enhancing standardization and productivity in your team. The program includes a deep dive into collaborative features of Confluence and its integration with Jira, which will enhance your ability to foster a collaborative environment. Administrative aspects like managing notifications, watchers, linking to other applications, and creating various types of spaces will also be covered.You?ll leave the course with the skills to apply Confluence within your existing Jira environment effectively, ready to use its collaborative tools and features to streamline workflows and boost project productivity. Introduction History Navigation Space Directory Shortcuts Pages VS Blogs Pages Creating Pages Editing Pages File Directory Advanced Editing (Markup, Undefined links, etc.) Copying and Moving Pages Deleting Pages Tasks Macros/Gadgets Macro overview and use Using JIRA Gadgets Editing Existing Macros Blueprints/Templates Working with Blueprints Creating/Using Templates Collaboration Sharing Links Commenting Mentioning 'Liking' Content 'Watching' Content JIRA Integration Linking your JIRA and Confluence Instances Linking Issues and Filters Auto Links Administration Page vs Space vs System Admin Notifications Watchers Linking to Other Applications Workbox Notifications Look and Feel Creating Spaces Public Space Private Space Team Space Technical Documentation Meeting Minutes Blog Additional course details: Nexus Humans Introduction to Confluence (TTDV7545) 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 Confluence (TTDV7545) 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 4 Days 24 CPD hours This course is intended for This course is geared for experienced skilled Java developers, software developers, data scientists, machine learning experts or others who wish to transtion their coding skills to Scala, learning how to code in Scala and apply it in a practical way. This is not a basic class. Overview Working in a hands-on learning environment led by our expert instructor you'll: Get comfortable with Scala's core principles and unique features, helping you navigate the language confidently and boosting your programming skills. Discover the power of functional programming and learn techniques that will make your code more efficient,maintainable, and enjoyable to write. Become proficient in creating dynamic web applications using the Play Framework, and easily connect to databases with the user-friendly Slick library. Master concurrency programming with Akka, empowering you to build scalable and fault-tolerant applications that excel in performance. Enhance your testing skills using ScalaTest and ScalaCheck, ensuring the reliability and quality of your Scala applications, while having fun in the process. Explore the fascinating world of generative AI and GPT technologies, and learn how to integrate them into your projects,adding a touch of innovation and intelligence to your Scala solutions. If your team requires different topics, additional skills or a custom approach, our team will collaborate with you to adjust the course to focus on your specific learning objectives and goals. Discover the power of Scala programming in our comprehensive, hands-on technical training course designed specifically for experienced object-oriented (OO) developers. Scala is a versatile programming language that combines the best of both OO and functional programming paradigms, making it ideal for a wide range of projects, from web applications to big data processing and machine learning. By mastering Scala, you'll be able to develop more efficient, scalable, and maintainable applications. Fast Track to Scala Programming for OO / Java Developers is a four day hands-on course covers the core principles of Scala, functional programming, web application development, database connectivity, concurrency programming, testing, and interoperability between Scala and Java. Additionally, you'll explore cutting-edge generative AI and GPT technologies, learning how to integrate them into your Scala applications for intelligent suggestions or automation. Throughout the course you?ll explore the latest tools and best practices in the Scala ecosystem, gaining valuable knowledge and experience that can be directly applied to your day-to-day work. With 50% of the course content dedicated to hands-on labs, you'll gain practical experience applying the concepts you've learned across various projects, such as building functional web applications, connecting to databases, designing modular components, and implementing concurrency. Upon completing the course, you'll have a solid understanding of the language and its features, empowering you to confidently apply your new skills in data science and machine learning projects. You'll exit well-prepared to create efficient, scalable, and maintainable Scala applications, regardless of the complexity of your projects. Introduction to Scala Scala features and benefits Comparing Scala with Java and other OO languages Installing Scala and setting up the development environment Object-Oriented Programming in Scala Classes and objects Traits, mixins, and inheritance Companion objects and factories Encapsulation and polymorphism Functional Programming Basics Pure functions and referential transparency Higher-order functions and currying Immutability and persistent data structures Pattern matching and recursion Having Fun with Functional Data Structures Lists, sets, and maps in Scala Folding and reducing operations Stream processing and lazy evaluation For-comprehensions Building Web Applications in Functional Style Introduction to Play Framework Functional web routing and request handling JSON handling with Play-JSON Middleware and functional composition Connecting to a Database Introduction to Slick library Database configuration and setup Querying and updating with Slick Transactions and error handling Building Scalable and Extensible Components Modular architecture and design patterns Dependency injection with MacWire Type classes and type-level programming Implicit parameters and conversions Concurrency Programming & Akka Introduction to Akka framework and Actor model Actor systems and message passing Futures and Promises Supervision and fault tolerance Building Confidence with Testing Introduction to ScalaTest and ScalaCheck Unit testing and property-based testing Test-driven development in Scala Mocking and integration testing Interoperability between Scala and Java Calling Java code from Scala Using Java libraries in Scala projects Converting Java collections to Scala collections Writing Scala code that can be called from Java Using Generative AI and GPT Technologies in Scala Programming Overview of GPT and generative AI Integrating GPT with Scala applications Use cases and practical examples

Duration 1 Days 6 CPD hours This course is intended for This course is designed for non-technical business executives who are tasked with making business decisions about emerging technologies in their businesses. Overview You will learn:Blockchain Cloud BasicsIoT OverviewMobility and Ambient ComputingMachine Learning and Deep LearningChatbots, Robotics, and More This course is designed for non-technical business executives looking to learn and understand emerging technologies. Blockchain Cloud BasicsIoT OverviewMobility and Ambient ComputingMachine Learning and Deep LearningChatbots, Robotics, and More