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Definitive Salt training course description Salt is a remote execution framework and configuration management system. This course covers Salt from the basics. After a quick first taste the course moves onto execution modules, salt states, minion and master data, jinja, Salt extensions and then topology and configuration options. Hands on sessions are used to reinforce the theory rather than teach specific manufacturer equipment. What will you learn Install and use Salt. Describe the architecture of Salt. Manage configurations with Salt. Extend Salt. Definitive Salt training course details Who will benefit: Anyone working with Salt. Prerequisites: Linux fundamentals. Duration 2 days Definitive Salt training course contents Introduction What is Salt? High- level architecture, Some quick examples, system management, configuration management, A brief history, Topology options, Extending Salt. Quick start: First taste of Salt Single-master setup, from packages, bootstrap scripts, Starting up, Basic commands, salt: the main workhorse, salt-key: key management, salt-call: execution on the minion, salt-run: co-ordination of jobs on the master, summary of commands, Key management, viewing keys, accepting keys, rejecting keys, key files, Minion targeting, minion ID, list (-L), glob, regular expressions (-E), grains (-G), compound (-C), targeting summary, Additional remote execution details, Conclusion. Execution modules: The functional foundation sys: information and documentation about modules, sys.doc basic documentation, sys.list_modules, sys.list_functions: simple listings, cmd: execute via shell, cmd.run: run any command, pkg: manage packages, virtual modules, pkg.lists_pkgs: list all installed packages, pkg.available version: see what version will be installed, pkg.install: install packages, user: manage users, user.add: add users, user.list_users, user info: get user info, saltutil: access various Salt utilities, Summary. Configuration management: Salt states Salt files overview, SLS example: adding a user, working with the multi-layered state system, Highstate and the top file, the top file, State ordering, require: depend on another state, watch: run based on other changes, odds and ends, Summary. Minion data / master data Grains are minion data, performing basic grain operations, setting grains, targeting with grains in the top file, Pillars are data from the master, querying pillar data, querying other sources with external pillars, Renderers give data options. Extending Salt: part I Introduction to Jinja, Jinja basics, Templating with Jinja, filtering by grains, Custom execution module, Custom state modules, Custom grains, External pillars, Summary. More on the matter Runners, manage minions, manage jobs, The orchestrate runner, The event system, The reactor system, Summary. Extending Salt: part II Python client API, reading configuration data on a master and minion, using the master client (localclient) API, Using the caller client API, Custom runners, writing a custom runner, using the runnerclient API, Summary. Topology and configuration options Master configuration, directories and files, logging, access control, files server options, Topology variations, masterless minions, peer systems, syndication masters, multiple masters. Brief introduction to salt-cloud Overview, Setup AWS and salt-cloud, installing salt-cloud, cloud providers, cloud profiles, cloud maps, Introspection via salt cloud, Creating infrastructure, More information. Using vagrant to run Salt examples YAML.

The easy way to store your data and retrieve it when you need it! Database training is vital for success if you want to work in the technology business. Companies are looking for experts who can use databases effectively and have a solid understanding of them. Our course can assist you in developing the skills and information required to flourish in the computer business. This well-designed course can teach you the fundamentals of database design, including creating and managing databases, manipulating data, and developing data-driven applications. You'll gain knowledge of several database types, including relational, object-oriented, distributed, and NoSQL. Along with measures to protect data security, you will learn about database performance and optimisation. Our course is a fantastic method to get started in the profession or obtain expertise for a present position. Many businesses are looking for candidates with good database knowledge and effective usage skills. You may differentiate yourself from the competition by enrolling in a course and gaining the skills and knowledge you need. Along with this Database Course, you will get 11 premium courses, an original hardcopy, 11 PDF Certificates (Main Course + Additional Courses) Student ID card as gifts. So, don't wait up. Enrol now! This Database Bundle Consists of the following Premium courses: Courses are included in this Database Bundle? Course 01: Microsoft SQL Server Development for Everyone Course 02: SQL Programming Masterclass Course 03: SQL NoSQL Big Data and Hadoop Course 04: Python Programming for Everybody Course 05: Data Science with Python Course 06: JavaScript Foundations for Everyone Course 07: C# Programming - Beginner to Advanced Course 08: R Programming for Data Science Course 09: Three.js & WebGL 3D Programming Course for Beginners Course 10: Basic Google Data Studio Course 11: Data Analytics with Tableau Learning Outcomes Have a fundamental understanding of database design, implementation, and upkeep. Be able to query databases and learn the SQL language. To preserve data, use security procedures and backup procedures. Examine database performance and note any enhancements. Be familiar with approaches for database normalisation and optimisation. Create web services and database applications. Use DBMS software for managing and storing data. Identify technologies and trends in databases. These 11 courses cover programming and data science topics such as SQL, Python, JavaScript, C#, R, Three.js, WebGL, Google Data Studio, and Tableau. They teach skills in database management, data analysis, manipulation, visualization, and reporting for beginners to advanced learners. The bundle incorporates skills to shed some light on your way and boost your career. Hence, you can strengthen your Database Expertise and essential knowledge, which will assist you in reaching your goal. Certificate: PDF Certificate: Free (Previously it was £6*11 = £66) Hard Copy Certificate: Free (For The Title Course: Previously it was £10) CPD 120 CPD hours / points Accredited by CPD Quality Standards Who is this course for? Individuals interested in learning programming and data science skills Professionals seeking to enhance their knowledge and skill set Entrepreneurs or business owners wanting to understand and manage data effectively Students or graduates in computer science, data science, or related fields Anyone looking to start a career in programming or data science Data analysts, data scientists, or data engineers looking to expand their skill set Requirements There is no time limit for completing this course; it can be studied in your own time at your own pace. Career path People tend to pursue their careers in the following professions in the database sector Database Administrator Database Developer Database Architect Database Analyst Database Designer The salary range for a Database Professional in the UK is typically between £25,000 and £50,000 per annum. Certificates Certificate of completion Hard copy certificate - Included You will get the Hard Copy certificate for the title course (Microsoft SQL Server Development for Everyone) absolutely Free! Other Hard Copy certificates are available for £10 each. Please Note: The delivery charge inside the UK is £3.99, and the international students must pay a £9.99 shipping cost. Certificate of completion Digital certificate - Included

In this course, you will learn how to perform data cleaning and data preparation with KNIME and without coding. You should be familiar with KNIME as no basics are covered in this course. Basic knowledge of machine learning is certainly helpful for the later lectures in this course.

Duration 3 Days 18 CPD hours This course is intended for This course is designed primarily for network and software engineers who are interested in learning about automation and programmability and hold the following job roles: Network engineer Systems engineer Wireless engineer Consulting systems engineer Technical solutions architect Network administrator Wireless design engineer Network manager Sales engineer Account manager Overview Upon completing this course, the learner will be able to meet these overall objectives: Get familiar with different API styles (REST, RPC) and synchronous and asynchronous API requests Learn how to use Postman software development tool in order to test the API calls Learn how to automate repetitive tasks using Ansible automation engine Explore a Python programming language, Python libraries and Python virtual environments and learn how can they be used for automation of network configuration tasks Get introduced to GIT version control system and its common operations Learn how to leverage the various models and APIs of the Cisco IOS XE platform to perform day-zero operations, improve troubleshooting methodologies with custom tools, augment the CLI using scripts, and integrate various workflows using Ansible and Python Learn about the paradigm shift of model-driven telemetry and the building blocks of a working solution Learn how to leverage the tools and APIs to automate Cisco DNA infrastructure managed by Cisco DNA Center™ Demonstrate workflows (configuration, verification, health checking, and monitoring) using Python, Ansible, and Postman Understand Cisco SD-WAN solution components, implement a Python library that works with the Cisco SD-WAN APIs to perform configuration, inventory management, and monitoring tasks, and implement reusable Ansible roles to automate provisioning new branch sites on an existing Cisco SD-WAN infrastructure Learn how to leverage the tools and APIs to automate Cisco Meraki managed infrastructure and demonstrate workflows (configuration, verification, health checking, monitoring) using Python, Ansible, and Postman Implementing Automation for Cisco Enterprise Solutions (ENAUI) v.1.2 teaches you how to implement Cisco Enterprise automated solutions, including programming concepts, orchestration, telemetry, and automation tools. This course highlights the tools and the benefits of leveraging programmability and automation in the Cisco-powered Enterprise Campus and WAN. You will also examine platforms including IOS XE software for device-centric automation, Cisco DNA Center for the intent-based enterprise network, Cisco Software-Defined WAN, and Cisco Meraki. Their current ecosystem of APIs, software development toolkits, and relevant workflows are studied in detail together with open industry standards, tools, and APIs, such as Python, Ansible, Git, JSON/YAML, NETCONF/RESTCONF, and YANG. The course qualifies for 24 Cisco Continuing Education credits (CE) towards recertification. This course will help you:Gain high-demand skills using modern programming languages, APIs, and systems such as Python, Ansible, and Git to automate, streamline, and enhance business operationsAcquire the skills and knowledge to customize tools, methods, and processes that improve network performance and agilityPrepare for the 300-435 ENAUTO exam Course Outline Network Programmability Foundation Automating APIs and Protocols Managing Configuration with Python and Ansible Implementing On-Box Programmability and Automation with Cisco IOS XE Software Implementing Model-Driven Telemetry Day 0 Provisioning with Cisco IOS-XE Software Implementing Automation in Enterprise Networks Building Cisco DNA Center Automation with Python Automating Operations using Cisco DNA Center Introducing Cisco SD-WAN Programmability Building Cisco SD-WAN Automation with Python Building Cisco SD-WAN Automation with Ansible Automating Cisco Meraki Implementing Meraki Integration APIs Additional course details: Nexus Humans Cisco Implementing Automation for Cisco Enterprise Solutions v1.2 (ENAUI) training program is a workshop that presents an invigorating mix of sessions, lessons, and masterclasses meticulously crafted to propel your learning expedition forward. This immersive bootcamp-style experience boasts interactive lectures, hands-on labs, and collaborative hackathons, all strategically designed to fortify fundamental concepts. Guided by seasoned coaches, each session offers priceless insights and practical skills crucial for honing your expertise. Whether you're stepping into the realm of professional skills or a seasoned professional, this comprehensive course ensures you're equipped with the knowledge and prowess necessary for success. While we feel this is the best course for the Cisco Implementing Automation for Cisco Enterprise Solutions v1.2 (ENAUI) 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.

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CNC Operator CAD Technician Production Engineer Data Analyst Software Developer Machine Learning Expert Certificates CPD Accredited Digital Certificate Digital certificate - Included Upon passing the Course, you need to order a Digital Certificate for each of the courses inside this bundle as proof of your new skills that are accredited by CPD QS for Free. CPD Accredited Hard Copy Certificate Hard copy certificate - Included If you are an international student, then you have to pay an additional 10 GBP for each certificate as an international delivery charge.

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This course will provide the information you need to master the Raspberry Pi 3 and Raspberry Pi 4. It walks you through everything you need to know to use the platform to the fullest and assumes no prior programming or electronics knowledge. The course also covers details about Raspberry Pi OS and Raspberry Pi Imager.

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

In this course, you will learn how to perform data cleaning and data preparation with KNIME and without coding. You should be familiar with KNIME as no basics are covered in this course. Basic knowledge of machine learning is certainly helpful for the later lectures in this course.

Duration 2 Days 12 CPD hours This course is intended for This course is designed primarily for customer engineers and systems engineers in the following job roles: Automation architect Automation engineer Consulting systems engineer DevOps engineer Network administrator Network architect Network consulting engineer Network design engineer Network engineer Network operator Network reliability engineer Sales engineer Site reliability engineer Systems engineer Technical solutions architect Overview After taking this course, you should be able to: Articulate the role network automation and programmability play in the context of end-to-end network management and operations Define and differentiate between waterfall and agile software development methodologies Interpret and troubleshoot Python scripts with fundamental programming constructs built for network automation use cases Describe how DevOps principles, tools, and pipelines can be applied to network operations Understand the role of network automation development environments and associated technologies such as Python virtual environments, Vagrant, and Docker Understand and construct HTTP-based API calls to network devices Articulate the differences among and common use cases for XML, JSON, YAML, and protobuf Construct and interpret Python scripts using the Python requests module to automate devices that have HTTP-based APIs Understand the role YANG plays in network automation Understand that a number of tools exist to simplify working with YANG models Describe the functionality of RESTCONF and NETCONF and the differences between them Construct Ansible playbooks to configure network devices and retrieve operational state data from them Build Jinja2 templates and YAML data structures to generate desired state configurations The Introducing Automation for Cisco Solutions (CSAU) v1.1 course gives you a broad overview of network automation skills. Through a combination of lecture and hands-on labs, you will learn the fundamentals of automation such as working on model-driven programmability solutions with Representational State Transfer Configuration Protocol (RESTCONF) and Network Configuration Protocol (NETCONF) protocols. The course also covers data formats and types, including Extensible Markup Language (XML), JavaScript Object Notation (JSON), Yaml Ain?t Markup Language (YAML), and Yet Another Next Generation (YANG), and their value in network automation, along with DevOps tools such as Ansible and Git. Course Outline Examining Network Management and Operations Exploring Software Development Methodologies Using Python for Network Automation Describing NetDevOps: DevOps for Networking Managing Automation Development Environments Introducing HTTP Network APIs Reviewing Data Formats and Data Encoding Using Python Requests to Automate HTTP-Based APIs Exploring YANG Using YANG Tools Automating Model-Driven APIs with Python Introducing Ansible for Network Automation Templating Configurations with Jinja2