120 Apache courses

Register on the Install NGINX, PHP, MySQL, SSL & WordPress on Ubuntu today and build the experience, skills and knowledge you need to enhance your professional development and work towards your dream job. Study this course through online learning and take the first steps towards a long-term career. The course consists of a number of easy to digest, in-depth modules, designed to provide you with a detailed, expert level of knowledge. Learn through a mixture of instructional video lessons and online study materials. Receive online tutor support as you study the course, to ensure you are supported every step of the way. Get an e-certificate as proof of your course completion. The Install NGINX, PHP, MySQL, SSL & WordPress on Ubuntu is incredibly great value and allows you to study at your own pace. Access the course modules from any internet-enabled device, including computers, tablet, and smartphones. The course is designed to increase your employability and equip you with everything you need to be a success. Enrol on the now and start learning instantly! What You Get With The Install NGINX, PHP, MySQL, SSL & WordPress on Ubuntu Receive a e-certificate upon successful completion of the course Get taught by experienced, professional instructors Study at a time and pace that suits your learning style Get instant feedback on assessments 24/7 help and advice via email or live chat Get full tutor support on weekdays (Monday to Friday) Course Design The course is delivered through our online learning platform, accessible through any internet-connected device. There are no formal deadlines or teaching schedules, meaning you are free to study the course at your own pace. You are taught through a combination of Video lessons Online study materials Certification Upon successful completion of the course, you will be able to obtain your course completion e-certificate free of cost. Print copy by post is also available at an additional cost of £9.99 and PDF Certificate at £4.99. Who Is This Course For: The course is ideal for those who already work in this sector or are an aspiring professional. This course is designed to enhance your expertise and boost your CV. Learn key skills and gain a professional qualification to prove your newly-acquired knowledge. Requirements: The online training is open to all students and has no formal entry requirements. To study the Install NGINX, PHP, MySQL, SSL & WordPress on Ubuntu, all your need is a passion for learning, a good understanding of English, numeracy, and IT skills. You must also be over the age of 16.  Course Content Section 01: Introduction Apache vs. NGINX 00:03:00 History of Apache 00:02:00 Advantages of NGINX 00:02:00 Section 02: Virtual Server Basics Deploying a Droplet on DigitalOcean 00:04:00 Attaching a Floating IP 00:01:00 Connecting to your Virtual Server 00:03:00 Section 03: Install & Configure LEMP Stack (Linux, NGINX, MySQL, PHP) Install & Configure NGINX 00:02:00 Install & Configure MySQL on NGINX 00:07:00 Install & Configure PHP on NGINX 00:11:00 Creating a PHP Test File 00:03:00 Section 04: Domain Names & SSL Modifying Domain Name Servers 00:03:00 Configuring DNS Zone Files 00:05:00 Updating the NGINX Block File Configuration File 00:03:00 Installing Let's Encrypt SSL on NGINX 00:08:00 Section 05: PhpMyAdmin on NGINX Installing PhpMyAdmin 00:05:00 Securing PhpMyAdmin with Symbolic Links 00:03:00 Securing PhpMyAdmin with Authentication Gateways 00:03:00 Enabling Authentication Gateways on NGINX 00:04:00 Section 06: WordPress on NGINX Introduction to WordPress 00:01:00 Creating a Database for WordPress 00:03:00 Installing PHP Extensions for WordPress 00:01:00 NGINX Block File Configuration for WordPress 00:03:00 Downloading WordPress 00:03:00 WordPress Configuration 00:04:00 WordPress Setup 00:04:00 Frequently Asked Questions Are there any prerequisites for taking the course? There are no specific prerequisites for this course, nor are there any formal entry requirements. All you need is an internet connection, a good understanding of English and a passion for learning for this course. Can I access the course at any time, or is there a set schedule? You have the flexibility to access the course at any time that suits your schedule. Our courses are self-paced, allowing you to study at your own pace and convenience. How long will I have access to the course? For this course, you will have access to the course materials for 1 year only. This means you can review the content as often as you like within the year, even after you've completed the course. However, if you buy Lifetime Access for the course, you will be able to access the course for a lifetime. Is there a certificate of completion provided after completing the course? Yes, upon successfully completing the course, you will receive a certificate of completion. This certificate can be a valuable addition to your professional portfolio and can be shared on your various social networks. Can I switch courses or get a refund if I'm not satisfied with the course? We want you to have a positive learning experience. If you're not satisfied with the course, you can request a course transfer or refund within 14 days of the initial purchase. How do I track my progress in the course? Our platform provides tracking tools and progress indicators for each course. You can monitor your progress, completed lessons, and assessments through your learner dashboard for the course. What if I have technical issues or difficulties with the course? If you encounter technical issues or content-related difficulties with the course, our support team is available to assist you. You can reach out to them for prompt resolution.

This course takes you through the concepts of containers and Kubernetes in a practical way. You will learn how to create, ship, run, and manage containerized web applications on local premises as well as on the cloud.

This video course teaches you how to secure Java framework applications with Spring Security. With the help of interesting activities and examples, you'll learn about using the capabilities of Spring Boot for securing web applications and you'll also delve into the Test-Driven Development approach to understand the features of Spring Security.

Duration 2 Days 12 CPD hours This course is intended for This course is intended for System and network engineers, technical architects and technical support personnel Overview Upon successful completion of this course, students will be able to install and operate a Cisco DNA Center (DNAC) This course will cover the basics of installing and operation of the Cisco DNA Center (DNAC). The Cisco DNAC is a stand-alone product that provides a single dashboard for every fundamental management task to simplify running an enterprise network. The DNAC is the management piece of the Software Defined Access (SDA) solution. Intent-based Networking overview DNA Center overview. DNA Center as a Platform. DNA Center Architecture & Design. DNA Center Installation DNA Center/Identity Services Engine (ISE) Integration ISE Integration configuration in DNA Center. DNA - Global - Add servers (e.g. ISE server(s)). DNA Center integration configuration in ISE. Approve pxGrid in ISE.Verify DNA/ISE integration DNA Center - Device Inventory Add networks devices to the DNA Center device inventory. Verify DNA Center Inventory configuration. DNA Center - Design - Network Hierarchy. Verify DNA Center - design configuration DNA Center - Design - Software Image Management (SWIM) Review SWIM image repository listing. Create golden software image & role. Verify golden software image creation DNA Center - Design ? Templates and Policies Templates ? Apache Velocity Engine. Command Runner. Policies: Group-Based, Application,Traffic Copy, IP-Based DNA Center - Provision Configuration Add devices to newly created sites/locations. Plug and Play (PnP). Verify DNA Center - provision configuration. DNA Center - Assurance Collection. DNA Center ? Administration

In this course, we take you step by step through the most common features and programming idioms of the Groovy programming language, enabling you to supercharge your developer productivity by harnessing the power of Groovy's lightweight and succinct programming syntax.

Learn to build a complete Internet of Things solution with Arduino, a SQL Database, and a web server

This course presents an approach for dealing with security and privacy throughout the entire software development lifecycle. You will learn about vulnerabilities that undermine security, and how to identify and remediate them in your own projects.

Duration 4 Days 24 CPD hours This course is intended for This class is intended for experienced developers who are responsible for managing big data transformations including: Extracting, loading, transforming, cleaning, and validating data. Designing pipelines and architectures for data processing. Creating and maintaining machine learning and statistical models. Querying datasets, visualizing query results and creating reports Overview Design and build data processing systems on Google Cloud Platform. Leverage unstructured data using Spark and ML APIs on Cloud Dataproc. Process batch and streaming data by implementing autoscaling data pipelines on Cloud Dataflow. Derive business insights from extremely large datasets using Google BigQuery. Train, evaluate and predict using machine learning models using TensorFlow and Cloud ML. Enable instant insights from streaming data Get hands-on experience with designing and building data processing systems on Google Cloud. This course uses lectures, demos, and hand-on labs to show you how to design data processing systems, build end-to-end data pipelines, analyze data, and implement machine learning. This course covers structured, unstructured, and streaming data. Introduction to Data Engineering Explore the role of a data engineer. Analyze data engineering challenges. Intro to BigQuery. Data Lakes and Data Warehouses. Demo: Federated Queries with BigQuery. Transactional Databases vs Data Warehouses. Website Demo: Finding PII in your dataset with DLP API. Partner effectively with other data teams. Manage data access and governance. Build production-ready pipelines. Review GCP customer case study. Lab: Analyzing Data with BigQuery. Building a Data Lake Introduction to Data Lakes. Data Storage and ETL options on GCP. Building a Data Lake using Cloud Storage. Optional Demo: Optimizing cost with Google Cloud Storage classes and Cloud Functions. Securing Cloud Storage. Storing All Sorts of Data Types. Video Demo: Running federated queries on Parquet and ORC files in BigQuery. Cloud SQL as a relational Data Lake. Lab: Loading Taxi Data into Cloud SQL. Building a Data Warehouse The modern data warehouse. Intro to BigQuery. Demo: Query TB+ of data in seconds. Getting Started. Loading Data. Video Demo: Querying Cloud SQL from BigQuery. Lab: Loading Data into BigQuery. Exploring Schemas. Demo: Exploring BigQuery Public Datasets with SQL using INFORMATION_SCHEMA. Schema Design. Nested and Repeated Fields. Demo: Nested and repeated fields in BigQuery. Lab: Working with JSON and Array data in BigQuery. Optimizing with Partitioning and Clustering. Demo: Partitioned and Clustered Tables in BigQuery. Preview: Transforming Batch and Streaming Data. Introduction to Building Batch Data Pipelines EL, ELT, ETL. Quality considerations. How to carry out operations in BigQuery. Demo: ELT to improve data quality in BigQuery. Shortcomings. ETL to solve data quality issues. Executing Spark on Cloud Dataproc The Hadoop ecosystem. Running Hadoop on Cloud Dataproc. GCS instead of HDFS. Optimizing Dataproc. Lab: Running Apache Spark jobs on Cloud Dataproc. Serverless Data Processing with Cloud Dataflow Cloud Dataflow. Why customers value Dataflow. Dataflow Pipelines. Lab: A Simple Dataflow Pipeline (Python/Java). Lab: MapReduce in Dataflow (Python/Java). Lab: Side Inputs (Python/Java). Dataflow Templates. Dataflow SQL. Manage Data Pipelines with Cloud Data Fusion and Cloud Composer Building Batch Data Pipelines visually with Cloud Data Fusion. Components. UI Overview. Building a Pipeline. Exploring Data using Wrangler. Lab: Building and executing a pipeline graph in Cloud Data Fusion. Orchestrating work between GCP services with Cloud Composer. Apache Airflow Environment. DAGs and Operators. Workflow Scheduling. Optional Long Demo: Event-triggered Loading of data with Cloud Composer, Cloud Functions, Cloud Storage, and BigQuery. Monitoring and Logging. Lab: An Introduction to Cloud Composer. Introduction to Processing Streaming Data Processing Streaming Data. Serverless Messaging with Cloud Pub/Sub Cloud Pub/Sub. Lab: Publish Streaming Data into Pub/Sub. Cloud Dataflow Streaming Features Cloud Dataflow Streaming Features. Lab: Streaming Data Pipelines. High-Throughput BigQuery and Bigtable Streaming Features BigQuery Streaming Features. Lab: Streaming Analytics and Dashboards. Cloud Bigtable. Lab: Streaming Data Pipelines into Bigtable. Advanced BigQuery Functionality and Performance Analytic Window Functions. Using With Clauses. GIS Functions. Demo: Mapping Fastest Growing Zip Codes with BigQuery GeoViz. Performance Considerations. Lab: Optimizing your BigQuery Queries for Performance. Optional Lab: Creating Date-Partitioned Tables in BigQuery. Introduction to Analytics and AI What is AI?. From Ad-hoc Data Analysis to Data Driven Decisions. Options for ML models on GCP. Prebuilt ML model APIs for Unstructured Data Unstructured Data is Hard. ML APIs for Enriching Data. Lab: Using the Natural Language API to Classify Unstructured Text. Big Data Analytics with Cloud AI Platform Notebooks What's a Notebook. BigQuery Magic and Ties to Pandas. Lab: BigQuery in Jupyter Labs on AI Platform. Production ML Pipelines with Kubeflow Ways to do ML on GCP. Kubeflow. AI Hub. Lab: Running AI models on Kubeflow. Custom Model building with SQL in BigQuery ML BigQuery ML for Quick Model Building. Demo: Train a model with BigQuery ML to predict NYC taxi fares. Supported Models. Lab Option 1: Predict Bike Trip Duration with a Regression Model in BQML. Lab Option 2: Movie Recommendations in BigQuery ML. Custom Model building with Cloud AutoML Why Auto ML? Auto ML Vision. Auto ML NLP. Auto ML Tables.

In the fast-paced world of data science and machine learning, you have to stay up-to-date and keep ahead of the competition. For this, you have to constantly be on the lookout for the latest trends in tools and techniques for data science and machine learning. You don't want to miss out on the latest trend and the tool of the future! Right now, that tool is the Julia programming language. It's the hot new language that all ML and data science experts are very excited about. Learning Julia will open up several doors for you in your career!

This is a hands-on comprehensive course for beginners and in just two hours, you will learn the fundamentals of the Hadoop Ecosystem and its three main building blocks. This course will prepare you to start learning more about big data and to implement Hadoop components in Azure Cloud using HDInsight.