1542 Courses delivered Live Online

HP iMC for engineers training course description A hands on course focusing on network management using HP iMC on Microsoft Windows or UNIX. What will you learn Describe the network management architecture. Use HP NNMi. Diagnose faults using HP iMC. Recognise the MIB structure. HP iMC for engineers training course details Who will benefit: Network administrators. Network operators Those wishing to find out more about how their NMS works Anyone wishing to implement NFV using OpenStack. Prerequisites: Introduction to Virtualization Duration 2 day HP iMC for engineers training course content Network management What is network management? Benefits, issues. Getting started with HP iMC Starting HP iMC, IP discovery, IP monitoring, controlling IP discovery. Hands on Initial HP iMC configuration. Using HP iMC Viewing devices, Device view, IP view, network view, polling. Hands on Using HP iMC. Agents Configuring Cisco devices for SNMP support, communities, traps, syslog. Hands on Configuring network devices for HP iMC. Parts of SNMP SNMP architecture, MIBs, The protocol. HP iMC SNMP configuration. Hands on HP iMC SNMP configuration. MIBs The MIB2 groups, additional MIBs, MIB compilers, vendor MIBs. HP iMC MIB loader and browser. Hands on MIB browsing. Monitoring devices Polling, obtaining MIB information. Hands on HP iMC performance management. Configuration and change management Configuration templates, software library, configuration compare, configuration audit and reports. Hands on Using the configuration center. Reports Report templates, Real time reports, scheduling reports. Hands on Using real time reports. HP iMC fault management Alarms, polling, fault management, setting thresholds and configuring traps. Syslog. Hands on Working with alarms. Security alarms.

Total H.248 training course description A course focusing purely on the H.248 protocol. Anyone working through the ITU standards documents can testify to the need of a training course to explain how H.248 really works. This course already assumes knowledge of other VoIP protocols and starts by positioning H.248 in relation to the other protocols. The course then looks at H.248 architectures and concepts before analysing H.248 messages and call flows. What will you learn Describe what H.248 is Recognise where H.248 fits in relation to other VoIP protocols. Explain how H.248 works. Analyse H.248 packets Total H.248 training course details Who will benefit: Technical staff working with H.248 Prerequisites: Voice Over IP. Duration 2 days Total H.248 training course contents What is H.248? Review of VoIP protocols: RTP, RTCP, SIP, SDP, H.323. The PSTN and SS7. Where H.248 fits into the picture. H.248 history. MGCP. The IETF. Megaco. ITU standards. H.248v1, v2, v3. H.248 architectures Media Gateways, Media Gateway Controllers, Gateway Control functions, Signalling Gateways. Reference architectures: IMS/TISPAN: IBCF, IWF, I-BGF, SPDF. MSF: S-SBG-NC, D-SBG-NC. GSMA: IPX Proxy. Softswitches. H.248 concepts The connection model, terminations, streams, contexts. Termination properties: descriptors, context properties. Events, signals, packages. H.248 messages Protocol stack, UDP, TCP. Message structure. Transactions, actions, commands. Requests, replies, acknowledgements. Sample message flows. Binary encoding, ASN syntax, Text encoding. H.248 commands Termination manipulation: Add, Subtract, Move, Modify. Event reporting: Notify. Management: AuditCapability, AuditValue, ServiceChange. H.248 Descriptors What are descriptors? Relationship with messages and commands. Basic descriptors, Descriptors composed of other descriptors. The 19 descriptors. Defaults. H.248 Transactions Groups of commands, transaction Ids, relationship with actions and commands. Requests and replies. H.248 wrap up What is a package? Basic packages. H.248 security. H.248 - SIP interoperation. H.248 interoperation with other protocols.

Ansible training course description The course focusses on the use of ansible for network devices instead of its usual server use case. The course progresses from the basics of ansible and playbooks onto using network specific modules including NAPALM. The use Jinja2 templating with ansible is also studied. Hands on sessions with ansible configuring routers and switches follow all major sections. What will you learn Automate tasks with ansible. Write ansible playbooks. Configure network devices with ansible. Troubleshoot network devices with ansible. Use ansible network modules. Use jinja2 templates with ansible. Ansible training course details Who will benefit: Network engineers. Prerequisites: TCP/IP Foundation Duration 2 days Ansible training course contents What is ansible? The language, the engine, the framework. Uses of ansible, orchestration. Hands on Installing ansible, enabling SSH on network devices. Ansible architecture How ansible 'normally' works, Agentless, SSH, ansible and Python, modules, how ansible work on network devices, Configuration management, inventories, playbooks, modules, ansible.cfg. Hands on Getting started, running ad hoc commands. Playbooks ansible-playbook, users, YAML, plays, tasks, modules. ansible-vault. Hands on Running playbooks. More playbooks Handlers, variables, environmental variables, playbook variables, inventory variables, variable scope and precedence, accessing variables, facts, ansible vault. Conditionals, wait_for. Hands on Using variables and conditions in playbooks. Inventories /etc/ansible/hosts, inventory variables, static inventories, dynamic inventories. Hands on Inventories and variables. Ansible network modules Built in modules, custom modules, return values. ansible-doc -l. connection: local, Cisco modules, Juniper module, Hands on Using modules for your network devices. Ansible templatings The template module, the assemble module, jinja2 templates, for, if else. Hands on Configuring network devices from templates. Roles and includes Dynamic includes, Handler includes, playbook includes. Roles, role parts: handlers, files, templates, cross platform roles, ansible galaxy. Hands on includes example, building roles. Ansible and NAPALM Installation, napalm-ansible, NAPALM modules: napalm_diff-yang, napalm_get_facts, napalm_install_config, napalm_parse_yang, napalm_ping, napalm_translate_yang, napalm_validate. Hands on Using NAPALM modules in ansible.

IPsec training course description This hands on course focuses on IPsec VPNs. Rather than focusing on one implementation this course concentrates on the technologies and protocols of IPsec. Starting with an overview of the complete IPsec architecture the course then moves onto ESP packet analysis along with encryption and authentication provided. IKEv1 and IKEv2 are both covered in detail. Having covered IPsec with pre shared keys the course then moves onto IPsec with certificates followed by IPsec issues. The course is vendor neutral with hands on with both Cisco and Microsoft implementations. What will you learn Explain how IPsec works. Explain the role of AH, ESP and IKE. Configure IPsec. Troubleshoot IPsec. IPsec training course details Who will benefit: Technical staff working with IPsec. Prerequisites: Definitive IP VPNs for engineers. Duration 3 days IPsec training course contents What is IPsec? How to spell IPsec, IPsec is IP security, confidentiality, integrity, authenticity, replay protection, what is a VPN? Network layer security, IPsec and IPv4, IPsec and IPv6, the suite of protocols, the standard, IPsec RFCs, IPsec history. Hands on Analysis of 'normal' IP packets. IPsec architecture The IPsec protocols, AH vs ESP, Why two headers? transport mode, tunnel mode, Remote access VPNs, site to site VPNs, security associations, SA database, Security Parameters Index, implementations: Host tack, Bump in the Stack, Bump in the Wire. Hands on Configuring IPsec. AH What AH does, the stack, The AH header, What is authenticated? Device authentication. AH in transport mode, AH in tunnel mode. Hands on AH packet analysis. ESP What ESP does, the ESP header, ESP in transport mode, ESP in tunnel mode, ESP and SA, ESP and SPI. Hands on ESP packet analysis, policy configuration. IPsec encryption IPsec is a framework, standard algorithms, ESP keys, the role of IKE, key lifetimes, how IKE generates the keys, DES, 3DES, AES, cipher block chaining, counter mode, other encryption. Hands on Encryption configuration. IPsec authentication Authentication types, IPsec authentication, Authentication algorithms: MD5, keyed SHA-1, HMAC-MD5, HMAC-SHA-1, HMAC-RIPEMD, other authentication algorithms. Hands on Authentication configuration. IKE Internet Key Exchange, IKE and the SAD, the two phase negotiation, ISAKMP, ISAKMP header, pre shared keys, digital signatures, public key encryption, Diffie Hellman, proposals, counter proposals, nonces, identities, phase 1 negotiation: main mode, aggressive mode, base mode. Phase 2 negotiation: quick mode, new group mode. Hands on IKE packet analysis. More IKE PFS, IKE and dynamic addresses, XAUTH, hybrid authentication, CRACK, ULA, PIC. User level authentication. IKE renegotiation, heartbeats. Hands on Troubleshooting IPsec. IKEv2 The IKEv2 exchange, IKE_SA_INIT, IKE_AUTH, CREATE_CHILD_SA, IKEv2 packets, the informational exchange. Comparing IKev1 vs IKE v2. Hands on IKEv2 configuration and analysis. PKI What is PKI?, Digital certificates, Certificate authorities, CA servers, RA, VA, certificates, CA hierarchy, CRLs, certificate formats. Hands on installing and configuring certificate servers. IPsec issues NAT, IPsec overhead and fragmentation. Summary IPsec strengths and weaknesses. Where to get further information.

Duration 4 Days 24 CPD hours This course is intended for If you're a developer with a keen interest in providing automated solutions for your organization, this certification could be a great fit for you. You automate time-consuming and repetitive tasks by using Microsoft Power Automate. You review solution requirements, create process documentation, and design, develop, deploy, integrate, troubleshoot, and evaluate solutions. Working with business stakeholders, you help to improve and automate business workflows. Overview After completing this course, students will be able to: Design RPA solutions Develop RPA solutions Deploy and manage RPA solutions Candidates for this course automate time-consuming and repetitive tasks by using Microsoft Power Automate. They review solution requirements, create process documentation, and design, develop, troubleshoot, and evaluate solutions. Candidates work with business stakeholders to improve and automate business workflows. They collaborate with administrators to deploy solutions to production environments, and they support solutions. Module 1: Get started with Power Automate for desktop Get started with Power Automate for desktop by learning about flows, creating automated steps, and flow development essentials. Module 2: Automate processes with Robotic Process Automation and Power Automate for desktop Work with Power Automate for desktop to record Windows and Web applications, but also use out of box actions such as manipulating Excel documents as part of an end to end invoice processing solution. Module 3: Work with Power Automate for desktop Work with Power Automate for desktop options, flows, recording features, conditions, loops, variables, images, and error and exception handling. Module 4: Work with different technologies in Power Automate for desktop Learn how to automate email handling, Excel, user interface, and system services with Power Automate for desktop. Module 5: Implement advanced logic in Power Automate for desktop Learn how to work with system flows, control flows, mimic mouse actions, as well as operations used to manipulate text, date, and time in Power Automate for desktop. Module 6: Build expertise with Power Automate for desktop Learn how to use Power Automate for desktop to work with Power Automate, OCR technologies, and scripting. Module 7: Build custom connectors for Power Automate This Learning Path explores custom connectors and explains how to configure them and use them with Microsoft Power Automate Module 8: Use best practices to secure and govern Microsoft Power Platform environments This module focuses on introducing Microsoft Power Platform environments and their role in creating Data Loss Prevention (DLP) policies by using examples and use cases. A brief introduction and overview of tools will also be discussed, including Microsoft Power Platform and Power Automate Admin experiences and Microsoft Power Platform Center of Excellence (COE) toolkit. Additional course details: Nexus Humans PL-500T00 Microsoft Power Automate RPA Developer 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 PL-500T00 Microsoft Power Automate RPA Developer 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.

A webinar about the simple stuff and how it can help get you through when everything else feels too tough.

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

Duration 4 Days 24 CPD hours This course is intended for The information protection administrator translates an organization?s risk and compliance requirements into technical implementation. They are responsible for implementing and managing solutions for content classification, data loss prevention (DLP), information protection, data lifecycle management, records management, privacy, risk, and compliance. They also work with other roles that are responsible for governance, data, and security to evaluate and develop policies to address an organization's risk reduction and compliance goals. This role assists workload administrators, business application owners, human resources departments, and legal stakeholders to implement technology solutions that support the necessary policies and controls. Learn how to protect information in your Microsoft 365 deployment. This course focuses on data lifecycle management and information protection and compliance within your organization. The course covers implementation of data loss prevention policies, sensitive information types, sensitivity labels, data retention policies, Microsoft Purview Message Encryption, audit, eDiscovery, and insider risk among other related topics. The course helps learners prepare for the Microsoft Information Protection Administrator exam (SC-400). Prerequisites Foundational knowledge of Microsoft security and compliance technologies. Basic knowledge of information protection concepts. Understanding of cloud computing concepts. Understanding of Microsoft 365 products and services. 1 - Introduction to information protection and data lifecycle management in Microsoft Purview Know your data Protect your data Prevent data loss Govern your data 2 - Classify data for protection and governance Data classification overview Classify data using sensitive information types Classify data using trainable classifiers Review sensitive information and label usage Explore labeled and sensitive content Understand activities related to your data 3 - Create and manage sensitive information types Compare built-in versus custom sensitive information types Create and manage custom sensitive information types Describe custom sensitive information types with exact data match Implement document fingerprinting Create keyword dictionary 4 - Understand Microsoft 365 encryption Learn how Microsoft 365 data is encrypted at rest Understand service encryption in Microsoft Purview Explore customer key management using Customer Key Learn how data is encrypted in-transit 5 - Deploy Microsoft Purview Message Encryption Implement Microsoft Purview Message Encryption Implement Microsoft Purview Advanced Message Encryption Use Microsoft Purview Message Encryption templates in mail flow rules 6 - Protect information in Microsoft Purview Information protection overview Configure sensitivity labels Configure sensitivity label policies Configure auto-labeling policies Manage, monitor, and remediate information protection 7 - Apply and manage sensitivity labels Apply sensitivity labels to Microsoft Teams, Microsoft 365 groups, and SharePoint sites Plan on-premises labeling Configure on-premises labeling for the Unified Labeling Scanner Apply protections and restrictions to email and files Monitor label performance using label analytics 8 - Prevent data loss in Microsoft Purview Data loss prevention overview Identify content to protect Define policy settings for your DLP policy Test and create your DLP policy Prepare Endpoint DLP Manage DLP alerts in the Microsoft Purview compliance portal View data loss prevention reports Implement the Microsoft Purview Extension 9 - Configure DLP policies for Microsoft Defender for Cloud Apps and Power Platform Configure data loss prevention policies for Power Platform Integrate data loss prevention in Microsoft Defender for Cloud Apps Configure policies in Microsoft Defender for Cloud Apps Manage data loss prevention violations in Microsoft Defender for Cloud Apps 10 - Manage data loss prevention policies and reports in Microsoft 365 Configure data loss prevention for policy precedence Implement data loss prevention policies in test mode Explain data loss prevention reporting capabilities Manage permissions for data loss prevention reports Manage and respond to data loss prevention policy violations 11 - Manage the data lifecycle in Microsoft Purview Data Lifecycle Management overview Configure retention policies Configure retention labels Configure manual retention label policies Configure auto-apply retention label policies Import data for Data Lifecycle Management Manage, monitor, and remediate Data Lifecycle Management 12 - Manage data retention in Microsoft 365 workloads Explain retention in Exchange Online Explain retention in SharePoint Online and OneDrive Explain retention in Microsoft Yammer Activate archive mailboxes in Microsoft Exchange Apply mailbox holds in Microsoft Exchange Recover content in Microsoft Exchange 13 - Manage records in Microsoft Purview Records management overview Import a file plan Configure retention labels Configure event driven retention Manage, monitor, and remediate records 14 - Explore compliance in Microsoft 365 Plan for security and compliance in Microsoft 365 Plan your beginning compliance tasks in Microsoft Purview Manage your compliance requirements with Compliance Manager Examine the Compliance Manager dashboard Analyze the Microsoft Compliance score 15 - Search for content in the Microsoft Purview compliance portal Explore Microsoft Purview eDiscovery solutions Create a content search View the search results and statistics Export the search results and search report Configure search permissions filtering Search for and delete email messages 16 - Manage Microsoft Purview eDiscovery (Standard) Explore Microsoft Purview eDiscovery solutions Implement Microsoft Purview eDiscovery (Standard) Create eDiscovery holds Search for content in a case Export content from a case Close, reopen, and delete a case 17 - Manage Microsoft Purview eDiscovery (Premium) Explore Microsoft Purview eDiscovery (Premium) Implement Microsoft Purview eDiscovery (Premium) Create and manage an eDiscovery (Premium) case Manage custodians and non-custodial data sources Analyze case content 18 - Manage Microsoft Purview Audit (Standard) Explore Microsoft Purview Audit solutions Implement Microsoft Purview Audit (Standard) Search the audit log Export, configure, and view audit log records Use audit log searching to investigate common support issues 19 - Prepare Microsoft Purview Communication Compliance Plan for communication compliance Identify and resolve communication compliance workflow Case study--Configure an offensive language policy Investigate and remediate communication compliance alerts 20 - Manage insider risk in Microsoft Purview Insider risk management overview Create and manage insider risk policies Investigate insider risk alerts Take action on insider risk alerts through cases Manage insider risk management forensic evidence Create insider risk management notice templates 21 - Implement Microsoft Purview Information Barriers Explore Microsoft Purview Information Barriers Configure information barriers in Microsoft Purview Examine information barriers in Microsoft Teams Examine information barriers in OneDrive Examine information barriers in SharePoint 22 - Manage regulatory and privacy requirements with Microsoft Priva Create and manage risk management policies Investigate and remediate risk management alerts Create rights requests Manage data estimate and retrieval for rights requests Review data from rights requests Get reports from rights requests 23 - Implement privileged access management Case study--Implementing privileged access management 24 - Manage Customer Lockbox Manage Customer Lockbox requests

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Duration 4 Days 24 CPD hours This course is intended for The primary audience for this course is data professionals, data architects, and business intelligence professionals who want to learn about data engineering and building analytical solutions using data platform technologies that exist on Microsoft Azure. The secondary audience for this course includes data analysts and data scientists who work with analytical solutions built on Microsoft Azure. In this course, the student will learn how to implement and manage data engineering workloads on Microsoft Azure, using Azure services such as Azure Synapse Analytics, Azure Data Lake Storage Gen2, Azure Stream Analytics, Azure Databricks, and others. The course focuses on common data engineering tasks such as orchestrating data transfer and transformation pipelines, working with data files in a data lake, creating and loading relational data warehouses, capturing and aggregating streams of real-time data, and tracking data assets and lineage. Prerequisites Successful students start this course with knowledge of cloud computing and core data concepts and professional experience with data solutions. AZ-900T00 Microsoft Azure Fundamentals DP-900T00 Microsoft Azure Data Fundamentals 1 - Introduction to data engineering on Azure What is data engineering Important data engineering concepts Data engineering in Microsoft Azure 2 - Introduction to Azure Data Lake Storage Gen2 Understand Azure Data Lake Storage Gen2 Enable Azure Data Lake Storage Gen2 in Azure Storage Compare Azure Data Lake Store to Azure Blob storage Understand the stages for processing big data Use Azure Data Lake Storage Gen2 in data analytics workloads 3 - Introduction to Azure Synapse Analytics What is Azure Synapse Analytics How Azure Synapse Analytics works When to use Azure Synapse Analytics 4 - Use Azure Synapse serverless SQL pool to query files in a data lake Understand Azure Synapse serverless SQL pool capabilities and use cases Query files using a serverless SQL pool Create external database objects 5 - Use Azure Synapse serverless SQL pools to transform data in a data lake Transform data files with the CREATE EXTERNAL TABLE AS SELECT statement Encapsulate data transformations in a stored procedure Include a data transformation stored procedure in a pipeline 6 - Create a lake database in Azure Synapse Analytics Understand lake database concepts Explore database templates Create a lake database Use a lake database 7 - Analyze data with Apache Spark in Azure Synapse Analytics Get to know Apache Spark Use Spark in Azure Synapse Analytics Analyze data with Spark Visualize data with Spark 8 - Transform data with Spark in Azure Synapse Analytics Modify and save dataframes Partition data files Transform data with SQL 9 - Use Delta Lake in Azure Synapse Analytics Understand Delta Lake Create Delta Lake tables Create catalog tables Use Delta Lake with streaming data Use Delta Lake in a SQL pool 10 - Analyze data in a relational data warehouse Design a data warehouse schema Create data warehouse tables Load data warehouse tables Query a data warehouse 11 - Load data into a relational data warehouse Load staging tables Load dimension tables Load time dimension tables Load slowly changing dimensions Load fact tables Perform post load optimization 12 - Build a data pipeline in Azure Synapse Analytics Understand pipelines in Azure Synapse Analytics Create a pipeline in Azure Synapse Studio Define data flows Run a pipeline 13 - Use Spark Notebooks in an Azure Synapse Pipeline Understand Synapse Notebooks and Pipelines Use a Synapse notebook activity in a pipeline Use parameters in a notebook 14 - Plan hybrid transactional and analytical processing using Azure Synapse Analytics Understand hybrid transactional and analytical processing patterns Describe Azure Synapse Link 15 - Implement Azure Synapse Link with Azure Cosmos DB Enable Cosmos DB account to use Azure Synapse Link Create an analytical store enabled container Create a linked service for Cosmos DB Query Cosmos DB data with Spark Query Cosmos DB with Synapse SQL 16 - Implement Azure Synapse Link for SQL What is Azure Synapse Link for SQL? Configure Azure Synapse Link for Azure SQL Database Configure Azure Synapse Link for SQL Server 2022 17 - Get started with Azure Stream Analytics Understand data streams Understand event processing Understand window functions 18 - Ingest streaming data using Azure Stream Analytics and Azure Synapse Analytics Stream ingestion scenarios Configure inputs and outputs Define a query to select, filter, and aggregate data Run a job to ingest data 19 - Visualize real-time data with Azure Stream Analytics and Power BI Use a Power BI output in Azure Stream Analytics Create a query for real-time visualization Create real-time data visualizations in Power BI 20 - Introduction to Microsoft Purview What is Microsoft Purview? How Microsoft Purview works When to use Microsoft Purview 21 - Integrate Microsoft Purview and Azure Synapse Analytics Catalog Azure Synapse Analytics data assets in Microsoft Purview Connect Microsoft Purview to an Azure Synapse Analytics workspace Search a Purview catalog in Synapse Studio Track data lineage in pipelines 22 - Explore Azure Databricks Get started with Azure Databricks Identify Azure Databricks workloads Understand key concepts 23 - Use Apache Spark in Azure Databricks Get to know Spark Create a Spark cluster Use Spark in notebooks Use Spark to work with data files Visualize data 24 - Run Azure Databricks Notebooks with Azure Data Factory Understand Azure Databricks notebooks and pipelines Create a linked service for Azure Databricks Use a Notebook activity in a pipeline Use parameters in a notebook Additional course details: Nexus Humans DP-203T00 Data Engineering on Microsoft Azure 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 DP-203T00 Data Engineering on Microsoft Azure 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.