1671 Architecture courses

GSM training course description GSM is in widespread use today. This seminar gives an comprehensive overview of GSM. What will you learn Explain what GSM is. Describe the architecture of the GSM network. Describe the GSM protocol stack. GSM training course details Who will benefit: Anyone who needs to know more about GSM. Prerequisites: Telecommunications Introduction Duration 2 days GSM training course contents Introduction History of GSM, analogue networks, digital networks, PCS1900. GSM services Telephony, digital encoding, data rates, Group 3 fax, SMS, Supplementary services. GSM architecture Mobile station Mobile Equipment (ME), Subscriber Identity Module (SIM). Base Station Subsystem Base Transceiver Station (BTS), Base Station Controller (BSC). Network Subsystem Mobile Services Switching Centre (MSC), Home Location Register (HLR), Visitor Location Register (VLR), Equipment Identity Register (EIR), Visitor Location register (VLR), Authentication Centre (AuC) Radio Link Aspects Bands, FDMA, TDMA, Traffic channels, Control channels, Speech coding, Channel coding and modulation, Multipath equalisation, Frequency hopping. GSM signalling SS7 overview, GSM SS7 nodes, Base Station Subsystem Application Part (BSSAP), Transaction Capabilities Application Part (TCAP), Mobile Application Part (MAP). Interfaces Um, Abis and A interfaces. Mobility and call processing in GSM Attach & location update process, mobile originate, mobile termination, handovers. GSM services Tele services, Bearer services, supplementary services, SMS, security. GSM futures GPRS, UMTS.

LTE Airside training course description This course provides a concise insight into the LTE airside. Key parts of the course are detailed looks at the air interface protocol stack, cell acquisition, transmission and reception of data and of he layer 1 procedures along with layer 2 procedures. What will you learn Explain the RF optimisation flowchart. Describe the importance of Reference Signal Received Power (RSRP). List many of the 3GPP recommended KPIs. Describe the concept of APN AMBR and UE AMBR within LTE. Describe the use of planning and optimisation computer tools. LTE Airside training course details Who will benefit: Anyone working with LTE. Prerequisites: Essential LTE Duration 2 days LTE Airside training course contents Introduction and review of LTE This section describes the requirements of LTE and key technical features, and reviews the system architecture. LTE Architecture, UE, E-UTRAN and EPC. Specifications. OFDMA, SC-FDMA and MIMO antennas This section describes the techniques used in the LTE air interface, notably orthogonal frequency division multiple access (OFDMA) and multiple input multiple output (MIMO) antennas. Communication techniques for fading multipath channels. OFDMA, FFT processing and cyclic prefix insertion. SC-FDMA in the LTE uplink. Multiple antenna techniques including transmit & receive diversity and spatial multiplexing. Introduction to the air interface This section covers the operation of the air interface, the channels that it uses, and the mapping to the time and frequency domains of OFDMA and SC-FDMA. Air interface protocol stack. Logical, transport and physical channels. Frame and slot structure, the resource grid. Resource element mapping of the physical channels and physical signals. LTE spectrum allocation. Cell acquisition This is the first of three sections covering the air interface physical layer. Here, we cover mobile procedures to start low-level communications with the cell, and base station transmission of the corresponding information. Primary/secondary synchronisation signals. Downlink reference signals. The master information block. Physical control format indicator channel. Organisation and transmission of the system information. Data transmission and reception In this section, we cover procedures used for data transmission and reception on the shared channels, and describe in detail the individual steps. Data transmission and reception on the uplink and downlink. Scheduling commands and grants on the PDCCH. DL-SCH and UL-SCH. Physical channel processing of the PDSCH and PUSCH. Hybrid ARQ indicators on the PHICH. Uplink control information on the PUCCH. Uplink demodulation and sounding reference signals. Additional physical layer procedure This section concludes our discussion of the air interface physical layer, by discussing a number of procedures that support its operation. Transmission of the physical random access channel. Contention and non-contention based random access procedures. Discontinuous transmission in idle and connected modes. Uplink power control and timing advance. Air interface layer 2 This section describes the architecture and operation of layer 2 of the air interface protocol stack. MAC protocol, interactions with the physical layer, use for scheduling. RLC protocol, transparent, unacknowledged and acknowledged modes. PDCP, including header compression, security functions and recovery from handover.

Ansible for engineers training course description An introduction to automation using ansible. Ansible is a general purpose IT automation platform that can be use for a number of purposes. The course covers configuration management, cloud provisioning and application deployment with ansible. Hands on sessions follow all major sections. What will you learn Install ansible. Automate tasks with ansible. Write ansible playbooks. Ansible for engineers training course details Who will benefit: Administrators and developers automating tasks. Prerequisites: Linux administration skills Duration 3 days Ansible for engineers training course contents What is ansible? The language, the engine, the framework. Uses of ansible, orchestration. Hands on Installing ansible. Ansible architecture ible architecture Controlling machines, nodes, Agentless, SSH, modules, JSON protocol. Configuration management, inventories, playbooks, modules, roles. Hands on Getting started, running ad hoc commands. Ansible and Vagrant Prototyping and testing. Hands on Using ansible with Vagrant. Ad hoc commands Parallelism, shell commands, managing files and directories, file transfer, package management, manage user and groups, deploying applications, service management, background jobs, checking log files, managing cron jobs. Hands on Using ansible with Vagrant. Playbooks ansible-playbook, users, sudo, YAML, plays, tasks, handlers, modules. 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. 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. Inventories /etc/ansible/hosts, inventory variables, static inventories, dynamic inventories. Hands on Inventories and variables. Miscellanea Individual server cookbooks, Main playbook for configuring all servers. Hands onPlaybooks.

ICA International Diploma in Managing Sanctions Risk Sanctions are a crucial instrument in the international battle against financial crime proliferation, terrorism and human rights abuses. It's a complex area and those who manage the risk need the right combination of knowledge, capabilities and behaviours to do so effectively. Technical skills - develop a deeper understanding of sanctions architecture, screening and the control framework; enrich your professional skillset Critical thinking - enhance your judgment-making and problem-solving skills Collaboration and communication - ensure a joined-up approach in your management of sanctions cases Flexibility and adaptability - be prepared to respond to fast-changing regimes and rules Leadership - be empowered to make effective decisions quickly and manage resources appropriately This course is awarded in association with Alliance Manchester Business School, the University of Manchester. Through this Level 6- Advanced qualification you will learn: Global sanctions architecture - Sanctions in context How sanctions regimes are implemented Evolving scope of sanctions - A changing tool Sector-based sanctions Identifying higher risk jurisdictions and activities Transparency, control, and ownership Licensing and permissible payments Management of global exposure to unilateral and regional sanctions Developing the control framework Sanctions screening Incident management and holding of sanctioned funds Sanctions lifting and roll back

A complete guide to the Cassandra architecture, the Cassandra query language, cluster management, and Java/Spark integration.

CCNP training course description The Implementing and Operating Cisco Enterprise Network Core Technologies (ENCOR) v1.2 course provides the knowledge and skills needed to configure, troubleshoot, and manage enterprise wired and wireless networks. You'll learn to implement security principles within an enterprise network and how to overlay network design using solutions such as SDAccess and SD-WAN. Course content includes 3 days of self-study material. This course helps you prepare for the 350-401 Implementing Cisco Enterprise Network Core Technologies (ENCOR) exam What will you learn Configure, troubleshoot, and manage enterprise wired and wireless networks Implement security principles within an enterprise network Prepare you prepare to take the 350-401 Implementing Cisco Enterprise Network Core Technologies (ENCOR) exam CCNP training course details Who will benefit: Mid-level network engineers, Network administrators, Network support technicians, Help desk technicians. Prerequisites: Implementation of Enterprise LAN networks. Basic understanding of Enterprise routing and wireless connectivity, and Python scripting Duration 5 days CCNP training course content Cisco Enterprise Network Architecture: Access, distribution, core in the hierarchical network. Cisco Switching Paths: Switching mechanisms, TCAM, CAM, process switching, fast switching, and CEF. Implementing Campus LAN Connectivity: Troubleshoot L2 connectivity using VLANs and trunkingBuilding Redundant Switched Topology: STP Implementing Layer 2 Port Aggregation Troubleshoot link aggregation using Etherchannel EIGRP Implement and optimize OSPFv2/v3, including adjacencies, packet types, and areas, summarization, and route filtering for IPv4/v6 Implement EBGP interdomain routing, path selection, and single and dual-homed networkingImplementing Network Redundancy: HSRP and VRRP Implement static and dynamic NAT Virtualization Protocols and TechniquesVPNs and Interfaces: Overlay technologies such as VRF, GRE, VPN, and LISP Wireless Principles: RF, antenna characteristics, and wireless standards.Wireless Deployment: Models available, autonomous AP deployments and cloud-based designs within the centralized Cisco WLC architecture Wireless Roaming and Location ServicesWireless AP Operation: How APs communicate with WLCs to obtain software, configurations, and centralized managementWireless Client Authentication: EAP, WebAuth, and PSK wireless client authentication on a WLC. Troubleshoot wireless client connectivity issues using various available tools Troubleshoot networks using services such as NTP, SNMP, Cisco IP SLAs, NetFlow, and Cisco IOS EEM Explain network analysis and troubleshooting tools, which include show and debug commands, as well as best practices in troubleshootingMulticast Protocols: IGMP v2/v3, PIM DM/SM and RPs Introducing QoS: Concepts and features. Implementing Network Services: Secure administrative access for Cisco IOS devices using CLI access, RBAC, ACL, and SSH, and device hardening concepts to secure devices from less secure applications Using Network Analysis ToolsInfrastructure Security: Scalable administration using AAA and the local database, features and benefits Enterprise Network Security Architecture: VPNs, content security, logging, endpoint security, personal firewalls, and other security features. Automation and Assurance with Cisco DNA Center: Purpose, function, features, and workflow. Intent-Based Networking, for network visibility, proactive monitoring, and application experienceCisco SD-Access Solution: Nodes, fabric control plane, and data plane, VXLAN gatewaysCisco SD-WAN Solution: Components and features of Cisco SD-WAN solutions, including the orchestration, management, control, and data planesBasics of Python Programming: Python components and conditionals with script writing and analysis Network Programmability: NETCONF and RESTCONF APIs in Cisco DNA Center and vManage Labs: Investigate the CAM. Analyze CEF. Troubleshoot VLAN and Trunk Issues. Tuning STP and Configuring RSTP. Configure MSTP. Troubleshoot EtherChannel. Implement Multi-area OSPF. Implement OSPF Tuning. Apply OSPF Optimization. Implement OSPFv3. Configure and Verify Single-Homed EBGP. Implementing HSRP. Configure VRRP. Implement NAT. Configure and Verify VRF. Configure and Verify a GRE Tunnel. Configure Static VTI Point-to-Point Tunnels. Configure Wireless Client Authentication in a Centralized Deployment. Troubleshoot Wireless Client Connectivity Issues. Configure Syslog. Configure and Verify Flexible NetFlow. Configuring Cisco IOS EEM. Troubleshoot Connectivity and Analyze Traffic with Ping, Traceroute, and Debug. Configure and Verify Cisco IP SLAs. Configure Standard and Extended ACLs. Configure Control Plane Policing. Implement Local and Server-Based AAA. Writing and Troubleshooting Python Scripts. Explore JSON Objects and Scripts in Python. Use NETCONF Via SSH. Use RESTCONF with Cisco IOS XE.

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.

Duration 4 Days 24 CPD hours This course is intended for This course is designed for data scientists with existing knowledge of Python and machine learning frameworks like Scikit-Learn, PyTorch, and Tensorflow, who want to build and operate machine learning solutions in the cloud. Overview Learn how to operate machine learning solutions at cloud scale using Azure Machine Learning. This course teaches you to leverage your existing knowledge of Python and machine learning to manage data ingestion and preparation, model training and deployment, and machine learning solution monitoring in Microsoft Azure. Learn how to operate machine learning solutions at cloud scale using Azure Machine Learning. This course teaches you to leverage your existing knowledge of Python and machine learning to manage data ingestion and preparation, model training and deployment, and machine learning solution monitoring with Azure Machine Learning and MLflow. Prerequisites Creating cloud resources in Microsoft Azure. Using Python to explore and visualize data. Training and validating machine learning models using common frameworks like Scikit-Learn, PyTorch, and TensorFlow. Working with containers AI-900T00: Microsoft Azure AI Fundamentals is recommended, or the equivalent experience. 1 - Design a data ingestion strategy for machine learning projects Identify your data source and format Choose how to serve data to machine learning workflows Design a data ingestion solution 2 - Design a machine learning model training solution Identify machine learning tasks Choose a service to train a machine learning model Decide between compute options 3 - Design a model deployment solution Understand how model will be consumed Decide on real-time or batch deployment 4 - Design a machine learning operations solution Explore an MLOps architecture Design for monitoring Design for retraining 5 - Explore Azure Machine Learning workspace resources and assets Create an Azure Machine Learning workspace Identify Azure Machine Learning resources Identify Azure Machine Learning assets Train models in the workspace 6 - Explore developer tools for workspace interaction Explore the studio Explore the Python SDK Explore the CLI 7 - Make data available in Azure Machine Learning Understand URIs Create a datastore Create a data asset 8 - Work with compute targets in Azure Machine Learning Choose the appropriate compute target Create and use a compute instance Create and use a compute cluster 9 - Work with environments in Azure Machine Learning Understand environments Explore and use curated environments Create and use custom environments 10 - Find the best classification model with Automated Machine Learning Preprocess data and configure featurization Run an Automated Machine Learning experiment Evaluate and compare models 11 - Track model training in Jupyter notebooks with MLflow Configure MLflow for model tracking in notebooks Train and track models in notebooks 12 - Run a training script as a command job in Azure Machine Learning Convert a notebook to a script Run a script as a command job Use parameters in a command job 13 - Track model training with MLflow in jobs Track metrics with MLflow View metrics and evaluate models 14 - Perform hyperparameter tuning with Azure Machine Learning Define a search space Configure a sampling method Configure early termination Use a sweep job for hyperparameter tuning 15 - Run pipelines in Azure Machine Learning Create components Create a pipeline Run a pipeline job 16 - Register an MLflow model in Azure Machine Learning Log models with MLflow Understand the MLflow model format Register an MLflow model 17 - Create and explore the Responsible AI dashboard for a model in Azure Machine Learning Understand Responsible AI Create the Responsible AI dashboard Evaluate the Responsible AI dashboard 18 - Deploy a model to a managed online endpoint Explore managed online endpoints Deploy your MLflow model to a managed online endpoint Deploy a model to a managed online endpoint Test managed online endpoints 19 - Deploy a model to a batch endpoint Understand and create batch endpoints Deploy your MLflow model to a batch endpoint Deploy a custom model to a batch endpoint Invoke and troubleshoot batch endpoints

ADO.NET training course description This ADO.net training course is designed to enable developers to use the toolset provided with.NET for data access including ADO.net objects, data controls, designers and interoperability with earlier ADO objects. The course is applicable for those using C# or VB.NET with ADO.NET What will you learn Retrieve and manipulate data using Microsoft's ADO.NET library. Work with the ADO.NET object model. Update data, including handling stored procedures, parameters, and return value. Search, sort and filter data. Leverage the power of XML. ADO.NET training course details Who will benefit: Programmers working with ADO.Net. Prerequisites: Effective programming with VB.NET or Concise introduction to C# Duration 2 days ADO.NET training course contents Introducing ADO.Net Traditional Data Access Architecture. ADO.Net Disconnected Data Access Architecture. Different components of ADO.Net. A review of basic SQL queries SQL SELECT Statement. SQL INSERT Statement. SQL UPDATE Statement. SQL DELETE Statement. Common data access tasks with ADO.Net Accessing Data using ADO.Net. Defining the connection string. Defining a Connection. Defining the command or command string. Defining the Data Adapter. Creating and filling the DataSet. A Demonstration Application The Interface. Loading the table. Filling the controls on the Form. Navigating through the records. Updating Data Steps for updating the table. Building the Application. Loading the table and displaying data in the form's controls. Initialising Commands. Adding Parameters to the commands. The ToggleControls() method of our application. Editing (or Updating) Records. Event Handler for the Save Button. Event Handler for the Cancel Button. Inserting Records. Deleting a Record. Using Stored Procedures Sample Stored Procedures. UPDATE Stored Procedure. INSERT Stored Procedure. DELETE Stored Procedure. SELECT Stored Procedure. Using Stored Procedures with ADO.Net.

Total sFlow training course description A comprehensive hands on course covering sFlow. The course starts with the basics of flows moving swiftly onto configuring sFlow and studying the information it provides. What will you learn Describe sFlow. Use Nmap. Recognise how sFlow can be used. Describe the issues in using sFlow. Compare SFlow with SNMP and NetFlow. Total sFlow training course details Who will benefit: Technical staff working with sFlow. Prerequisites: TCP/IP foundation for engineers. Duration 1 day Total sFlow training course content What is SFlow? Where to monitor traffic. Packet based sampling, Time based sampling. Adaptive sampling. Flow samples, Counter samples. Hands on Wireshark flow analysis. Getting started with sFlow sFlow configuration. Enabling sFlow. Per interface. Hands on Accessing sFlow data using the CLI. sFlow architecture SFlow agents and collectors. When flows are exported. Distributed sFlow architecture, subagents. sFlow reporting products. SolarWinds. Hands on Collector software. sFlow features and benefits Troubleshooting with sFlow, controlling congestion, security and audit trail analysis. Hands on Using sFlow. sFlow versus other technologies Flows. sFlow impact and scalability. sFlow versus SNMP and RMON, SFlow versus NetFlow/IPFIX. Hands on Advanced sFlow configuration.