Complete Python training course description Python is an agile, robust, expressive, fully objectoriented, extensible, and scalable programming language. It combines the power of compiled languages with the simplicity and rapid development of scripting languages. This course covers Python from the very basics of 'hello world!' through to object oriented programming and advanced topics such as multi threading. Hands on follows all the major sections in order to reinforce the theory. What will you learn Read Python programs. Write Python programs. Debug Python programs. Use Python's objects and memory model as well as its OOP features. Complete Python programming training course details Who will benefit: Anyone wishing to learn Python. Prerequisites: None. Duration 5 days Complete Python programming training course contents Welcome to Python: What is Python? Origins, features. Downloading and installing Python, Python manuals, comparing Python, other implementations. Getting started: Program output, the print statement, "hello world!", Program input, raw_input(), comments, operators, variables and assignment, numbers, strings, lists and tuples, dictionaries, indentation, if statement, while Loop, for loop. range(), list comprehensions. Files, open() and file() built-in functions. Errors and exceptions. Functions, Classes, Modules, useful functions. Python basics: Statements and syntax, variable assignment, identifiers, basic style guidelines, memory management, First Python programs, Related modules/developer tools. Python Objects: Other built-in types, Internal Types, Standard type operators, Standard type built-in functions, Categorizing standard types, Unsupported types. Numbers: Integers, Double precision floating point numbers, Complex numbers, Operators, Built-in and factory functions, Other numeric types. Sequences: strings, lists, and tuples: Sequences, Strings, Strings and operators, String-only operators, Built-in functions, String built-in methods, Special features of strings, Unicode, Summary of string highlights, Lists, Operators, Built-in functions, List type built-in methods, Special features of lists, Tuples, Tuple operators and built-in functions, Tuples special features, Copying Python objects and shallow and deep copies. Mapping and set types: Mapping Type: dictionaries and operators, Mapping type built-in and factory functions, Mapping type built-in methods, Dictionary keys, Set types, Set type operators, Built-in functions, Set type built-in methods. Conditionals and loops: If, else and elif statements, Conditional expressions, while, for, break, continue and pass statements, else statement . . . take two, Iterators and iter(), List comprehensions, Generator expressions. Files and input/output: File objects, File built-in functions [open() and file()], File built-in methods and attributes, Standard files, Command-line arguments, File system, File execution, Persistent storage modules. Errors and exceptions: What are exceptions? Detecting and handling exceptions, Context management, Exceptions as strings, Raising exceptions, Assertions, Standard exceptions, Creating Exceptions, Why exceptions, Exceptions and the sys module. Functions: Calling, creating and passing functions, formal arguments, variable-length arguments, functional programming, Variable scope, recursion, generators. Modules: Modules and files, Namespaces, Importing modules, Module import features, Module built-in functions, Packages, Other features of modules. Object-Oriented Programming (OOP): Classes, Class attributes, Instances, Instance attributes, Binding and method invocation, Static methods and class methods, Composition, Sub-classing and derivation, Inheritance, Built-in functions for classes, and other objects, Customizing classes with special methods, Privacy, Delegation, Advanced features of new-style classes (Python 2.2+), Related modules and documentation. Execution environment: Callable and code Objects, Executable object statements and built-in functions, Executing other programs. 'Restricted' and 'Terminating' execution, operating system interface. Regular expressions: Special symbols and characters, REs and Python, Regular expressions example. Network programming: Sockets: communication endpoints, Network programming in Python, SocketServer module, Twisted framework introduction. Internet client programming: What are internet clients? Transferring files, Network news, E-mail. Multithreaded Programming: Threads and processes Python, threads, and the global interpreter lock, The thread and threading Modules. GUI programming: Tkinter and Python programming, Tkinter Examples, Brief tour of other GUIs. Web programming: Web surfing with Python: creating simple web clients, Advanced Web clients, CGI: helping web servers process client data, Building CGI applications, Using Unicode with CGI, Advanced CGI, Web (HTTP) Servers. Database programming: Python database application programmer's interface (DB-API), ORMs. Miscellaneous Extending Python by writing extensions, Web Services, programming MS Office with Win32 COM, Python and Java programming with Jython.
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.
Our MA Taster Session with Ben Gibson, is perfect for anyone interested in doing a postgraduate degree in Filmmaking or Screenwriting. Our taster session will consist of a: Deep dive of our current postgraduate programmes in Filmmaking and Screenwriting Short sample session Virtual tour of our Clapham campus Q&A session with one of our current MA students This is an event not to be missed, and we're confident that you'll come away from it with a wealth of knowledge and insights of what our MA programmes are all about, as well as life at Central Film School. About Ben Gibson: Ben Gibson is the Postgraduate Course Leader here at CFS, as well as a producer and consultant. He’s recently worked with Ecole Louis Lumiere, Paris and Studios La Victorine, Nice and on projects with Raoul Peck (Director of, I Am Not Your Negro). In the past Ben has worked as an independent producer and Head of Production at the British Film Institute. He has also co-managed The Other Cinema/Metro Pictures, operating London’s Metro Cinema. As well as this, he has been on-stage host for the Berlinale, a dramaturg, a theatre director, a repertory film programmer, a film critic and a journalist. When: Wednesday, 27th November, from 13:00 - 14:00pm. Where: This will be an online event, meaning you can join us from anywhere you like!
Course Summary: This workshop is designed for Club Welfare Officers and it is highly recommended that attendees complete UK Coaching's Safeguarding and Protecting Children Workshop first. Are you new to the Welfare Officer role or has it been three years since you last attended a Time to Listen workshop? The 3 hour workshop covers the following and learners will be able to: Describe how a club welfare officer works with others to create a child centered environment. Explain how the club welfare officer role fits into the wider safeguarding environment. Apply learning to case studies including sharing good safeguarding practice.
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UNIX Virtualization and High Availability course description This course covers administering UNIX enterprise-wide with an emphasis on virtualization and high availability. What will you learn Manage Virtual Machines. Manage containers. Manage HA clusters. Manage HA cluster storage. UNIX Virtualization and High Availability course details Who will benefit: Enterprise-level UNIX professional. UNIX professionals working with virtualization and/or High availability. Prerequisites: Linux network administration 2 (LPIC-2) Duration 5 days UNIX Virtualization and High Availability course contents VIRTUALIZATION Virtualization concepts and theory Terminology, Pros and Cons of virtualization, variations of Virtual Machine monitors, migration of physical to VMs, migration of VMs between host systems, cloud computing. Xen Xen architecture, networking and storage, Xen configuration, Xen utilities, troubleshooting Xen installations, XAPI, XenStore, Xen Boot Parameters, the xm utility. KVM KVM architecture, networking and storage, KVM configuration, KVM utilities, troubleshooting KVM installations. Other virtualization solutions OpenVZ and LXC, other virtualization technologies, virtualization provisioning tools. Libvirt and Related Tools libvirt architecture, networking and storage, basic technical knowledge of libvirt and virsh, oVirt. Cloud Management Tools Basic feature knowledge of OpenStack and CloudStack, awareness of Eucalyptus and OpenNebula. Containers Containers versus VMs, Docker, Kubernetes. Load balanced clusters of LVS/IPVS, VRRP, configuration of keepalived, configuration of ldirectord, backend server network configuration. HAProxy, configuration of HAProxy. Failover clusters Pacemaker architecture and components (CIB, CRMd, PEngine, LRMd, DC, STONITHd), Pacemaker cluster configuration, Resource classes (OCF, LSB, Systemd, Upstart, Service, STONITH, Nagios), Resource rules and constraints (location, order, colocation), Advanced resource features (templates, groups, clone resources, multi-state resources), Pacemaker management using pcs, Pacemaker management using crmsh, configuration and management of corosync in conjunction with Pacemaker, other cluster engines (OpenAIS, Heartbeat, CMAN). HIGH AVAILABILITY CLUSTER STORAGE DRBD/cLVM DRBD resources, states and replication modes, configuration of DRBD resources, networking, disks and devices, configuration of DRBD automatic recovery and error handling, management of DRBD using drbdadm. drbdsetup and drbdmeta, Integration of DRBD with Pacemaker, cLVM, integration of cLVM with Pacemaker. Clustered File Systems Principles of cluster file systems. Create, maintain and troubleshoot GFS2 file systems in a cluster, create, maintain and troubleshoot OCFS2 file systems in a cluster, Integration of GFS2 and OCFS2 with Pacemaker, the O2CB cluster stack, other commonly used clustered file systems.
Linux virtualization and HA training course description The LPIC-3 certification is the culmination of LPI's multi -level professional certification program. LPIC-3 is designed for the enterprise-level Linux professional and represents the highest level of professional, distribution neutral Linux certification within the industry. LPIC-3 304 covers administering Linux enterprise-wide with an emphasis on virtualization and high availability. At SNT we have enhanced the contents of the course by covering containers. What will you learn Manage Virtual Machines. Manage containers. Manage HA clusters. Manage HA cluster storage. Linux virtualization and HA training course details Who will benefit: Linux professionals working with virtualization and/or High availability. Prerequisites: Linux network administration 2 (LPIC-2) Duration 5 days Linux virtualization and HA training course contents VIRTUALIZATION Virtualization concepts and theory Terminology, Pros and Cons of virtualization, variations of Virtual Machine monitors, migration of physical to VMs, migration of VMs between host systems, cloud computing. Xen Xen architecture, networking and storage, Xen configuration, Xen utilities, troubleshooting Xen installations, XAPI, XenStore, Xen Boot Parameters, the xm utility. KVM KVM architecture, networking and storage, KVM configuration, KVM utilities, troubleshooting KVM installations. Other virtualization solutions OpenVZ and LXC, other virtualization technologies, virtualization provisioning tools. Libvirt and Related Tools libvirt architecture, networking and storage, basic technical knowledge of libvirt and virsh, oVirt. Cloud Management Tools Basic feature knowledge of OpenStack and CloudStack, awareness of Eucalyptus and OpenNebula. Containers Containers versus VMs, Docker, Kubernetes. Load balanced clusters of LVS/IPVS, VRRP, configuration of keepalived, configuration of ldirectord, backend server network configuration. HAProxy, configuration of HAProxy. Failover clusters Pacemaker architecture and components (CIB, CRMd, PEngine, LRMd, DC, STONITHd), Pacemaker cluster configuration, Resource classes (OCF, LSB, Systemd, Upstart, Service, STONITH, Nagios), Resource rules and constraints (location, order, colocation), Advanced resource features (templates, groups, clone resources, multi-state resources), Pacemaker management using pcs, Pacemaker management using crmsh, configuration and management of corosync in conjunction with Pacemaker, other cluster engines (OpenAIS, Heartbeat, CMAN). HIGH AVAILABILITY CLUSTER STORAGE DRBD/cLVM DRBD resources, states and replication modes, configuration of DRBD resources, networking, disks and devices, configuration of DRBD automatic recovery and error handling, management of DRBD using drbdadm. drbdsetup and drbdmeta, Integration of DRBD with Pacemaker, cLVM, integration of cLVM with Pacemaker. Clustered File Systems Principles of cluster file systems. Create, maintain and troubleshoot GFS2 file systems in a cluster, create, maintain and troubleshoot OCFS2 file systems in a cluster, Integration of GFS2 and OCFS2 with Pacemaker, the O2CB cluster stack, other commonly used clustered file systems.
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.
This course is designed to enhance the speaking and conversational skills of adult learners in English. Through a combination of interactive activities, discussions, and real-life scenarios, participants will develop the confidence and fluency needed to engage in various social and professional situations. Emphasis will be placed on improving pronunciation, expanding vocabulary, and refining grammar structures to communicate effectively in English. Course Duration: 10 weeks (20 sessions) Course Objectives: By the end of this course, participants will: 1. Improve their overall speaking fluency and accuracy in English. 2. Enhance their listening skills to understand and respond appropriately in conversations. 3. Expand their vocabulary and idiomatic expressions for effective communication. 4. Develop confidence in speaking English in social and professional settings. 5. Gain a deeper understanding of cultural nuances and non-verbal communication in English-speaking countries. Course Outline: Week 1: Introduction to Conversational English - Icebreaker activities to get to know each other - Assessing participants' current speaking level - Setting personal goals for the course Week 2: Pronunciation and Intonation - Identifying common pronunciation challenges - Practicing correct stress and intonation patterns - Role-playing exercises for clear communication Week 3: Everyday Conversations - Engaging in small talk and greetings - Discussing personal interests and hobbies - Describing daily routines and activities Week 4: Travel and Tourism - Asking for directions and recommendations - Role-playing scenarios at airports, hotels, and tourist attractions - Vocabulary related to travel and cultural experiences Week 5: Socialising and Networking - Discussing personal and professional backgrounds - Participating in group discussions and debates - Practicing active listening and turn-taking in conversations Week 6: Business Communication - Presenting ideas and opinions in a professional setting - Negotiating and persuading effectively - Writing and delivering effective elevator pitches Week 7: Job Interviews and Resume Building - Preparing for job interviews in English - Practicing common interview questions and answers - Crafting a compelling resume and cover letter Week 8: Public Speaking and Presentation Skills - Overcoming public speaking anxiety - Structuring and delivering engaging presentations - Using visual aids and body language effectively Week 9: Cultural Awareness and Non-verbal Communication - Understanding cultural differences in communication - Interpreting body language and gestures - Role-playing cross-cultural scenarios Week 10: Real-life Simulations - Applying all learned skills in real-life scenarios - Group discussions and feedback sessions - Reviewing progress and setting future language goals Note: This syllabus is a guideline and can be customised based on the specific needs and preferences of the participants. You can opt in and out of different modules.