5681 Computing & IT courses in Batley delivered Online

Duration 4 Days 24 CPD hours This course is intended for This course is for technical professionals who need to know how to deploy open source intrusion detection systems (IDS) and intrusion prevention systems (IPS), and how to write Snort rules. Security administrators Security consultants Network administrators System engineers Technical support personnel Channel partners and resellers Overview After taking this course, you should be able to: Describe Snort technology and identify resources available for maintaining a Snort deployment Install Snort on a Linux-based operating system Describe the Snort operation modes and their command-line options Describe the Snort intrusion detection output options Download and deploy a new rule set to Snort Describe and configure the snort.conf file Configure Snort for inline operation and configure the inline-only features Describe the Snort basic rule syntax and usage Describe how traffic is processed by the Snort engine Describe several advanced rule options used by Snort Describe OpenAppID features and functionality Describe how to monitor Snort performance and how to tune rules The Securing Cisco Networks with Open Source Snort (SSFSNORT) v2.1 course shows you how to deploy a network intrusion detection system based on Snort. You?ll learn how to install, configure, operate, and manage a Snort system, rules writing with an overview of basic options, advanced rules writing, how to configure Pulled Pork, and how to use OpenAppID to provide protection of your network from malware. You will learn techniques of tuning and performance monitoring, traffic flow through Snort rules, and more Course outline Introduction to Snort Technology Snort Installation Snort Operation Snort Intrusion Detection Output Rule Management Snort Configuration Inline Operation and Configuration Snort Rule Syntax and Usage Traffic Flow Through Snort Rules Advanced Rule Options OpenAppID Detection Tuning Snort Additional course details: Nexus Humans Cisco Securing Cisco Networks with Open Source Snort v2.1 (SSFSNORT) 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 Securing Cisco Networks with Open Source Snort v2.1 (SSFSNORT) 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.

Duration 0.5 Days 3 CPD hours This course is intended for This course is designed for business leaders and decision makers, including C-level executives, project managers, HR leaders, Marketing and Sales leaders, and technical sales consultants, who want to increase their knowledge of and familiarity with concepts surrounding data science. Other individuals who want to know more about basic data science concepts are also candidates for this course. This course is also designed to assist learners in preparing for the CertNexus DSBIZ™ (Exam DSZ-110) credential. Overview In this course, you will identify how data science supports business decisions. You will: Explain the fundamentals of data science Describe common implementations of data science. Identify the impact data science can have on a business The ability to identify and respond to changing trends is a hallmark of a successful business. Whether those trends are related to customers and sales or to regulatory and industry standards, businesses are wise to keep track of the variables that can affect the bottom line. In today's business landscape, data comes from numerous sources and in diverse forms. By leveraging data science concepts and technologies, businesses can mold all of that raw data into information that facilitates decisions to improve and expand the success of the business. Data Science Fundamentals What is Data Science? Types of Data Data Science Roles Data Science Implementation The Data Science Lifecycle Data Acquisition and Preparation Data Modeling and Visualization The Impact of Data Science Benefits of Data Science Challenges of Data Science Business Use Cases for Data Science Additional course details: Nexus Humans CertNexus Data Science for Business Professionals (DSBIZ) 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 CertNexus Data Science for Business Professionals (DSBIZ) 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.

Duration 5 Days 30 CPD hours This course is intended for This is an introductory-level systems administration course geared for Systems Administrators and users who wish to learn how to how to install, configure and maintain an Enterprise Linux system in a networked environment. Overview This course is about 50% lab to lecture ratio, combining expert instructor-led discussions with practical hands-on skills that emphasize current techniques, best practices and standards. Working in this hands-on lab environment, guided by our expert practitioner, attendees will explore Installing the Linux operating system and configuring peripherals Performing and modifying startup and shutdown processes Configuring and maintaining basic networking services Creating and maintaining system users and groups Understanding and administering file permissions on directories and regular files Planning and creating disk partitions and file systems Performing maintenance on file systems Identifying and managing Linux processes Automating tasks with cron Performing backups and restoration of files Working with system log files Troubleshooting system problems Analyzing and taking measures to increase system performance Configuring file sharing with NFS Configuring Samba for file sharing with the Windows clients Setting up a basic Web server Understanding the components for setting up a LAMP server Implementing basic security measures Linux System Administration is a comprehensive hands-on course that teaches students how to install, configure and maintain an Enterprise Linux system in a networked environment. This lab-intensive class explores core administrative tasks such as: creating and managing users, creating and maintaining file systems, determining and implementing security measures and performing software installation and package management. Linux networking topics include installing and supporting SSH, NFS, Samba and the Apache Web server. Students will explore common security issues, as well as several tools, such as the PAM modules that help secure the operating system and network environment. Upon successful completion of this course, students will be prepared to maintain Linux systems in a networked business environment. Although the course includes installing and configuring a CentOS 7 / RHEL 7 Linux system, much of the course content also applies to Oracle, Ubuntu, Scientific and other current versions of mainstream Linux distributions. Labs include user and group maintenance, system backups and restoration, software management, administration tasks automation, file system creation and maintenance, managing remote access, working with cron, and configuring basic file sharing and Web services, as well as working with system logging utilities such as rsyslog and much more. System Administration Overview UNIX, Linux and Open Source Duties of the System Administrator Superusers and the Root Login Sharing Superuser Privileges with Others (su and sudo Commands) TCP/IP Networking Fundamentals Online Help Installation and Configuration Planning: Hardware and Software Considerations Site Planning Installation Methods and Types Installation Classes Partitions Logical Volume Manager - LVM File System Overview Swap Partition Considerations Other Partition Considerations The Linux Boot Loader: grub Software Package Selection Adding and Configuring Peripherals Printers Graphics Controllers Basic Networking Configuration Booting to Recovery Mode Booting and Shutting Down Linux Boot Sequence The systemd Daemon The systemctl Command Targets vs. Run Levels Modifying a Target Service Unit Scripts Changing System States Booting into Rescue Mode Shutdown Commands Managing Software and Devices Identifying Software Packages Using rpm to Manage Software Using yum to Manage Software Installing and Removing Software Identifying Devices Displaying Device and System Information (PCI, USB) Plug and Play Devices Device Configuration Tools Managing Users and Groups Setting Policies User File Management The /etc/passwd file The /etc/shadow file The /etc/group file The /etc/gshadow file Adding Users Modifying User Accounts Deleting User Accounts Working with Groups Setting User Environments Login Configuration Files The Linux File System Filesystem Types Conventional Directory Structure Mounting a File System The /etc/fstab File Special Files (Device Files) Inodes Hard File Links Soft File Links Creating New File Systems with mkfs The lost+found Directory Repairing File Systems with fsck The Journaling Attribute File and Disk Management Tools Linux File Security File Permissions Directory Permissions Octal Representation Changing Permissions Setting Default Permissions Access Control Lists (ACLs) The getfacl and setfacl commands SUID Bit SGID Bit The Sticky Bit Controlling Processes Characteristics of Processes Parent-Child Relationship Examining Running Processes Background Processes Controlling Processes Signaling Processes Killing Processes Automating Processes cron and crontab at and batch System Processes (Daemons) Working with the Linux Kernel Linux Kernel Components Types of Kernels Kernel Configuration Options Recompiling the Kernel Shell Scripting Overview Shell Script Fundamentals Bash Shell Syntax Overview Shell Script Examples System Backups Backup Concepts and Strategies User Backups with the tar Command System Backup Options The xfsdump and xfsrestore Commands Troubleshooting the System Common Problems and Symptoms Troubleshooting Steps Repairing General Boot Problems Repairing the GRUB 2 Boot Loader Hard Drive Problems Restoring Shared Libraries System Logs and rsyslogd Basic Networking Networking Services Overview NetworkManager Introduction Network Configuration Files Locations and Formats Enabling and Restarting Network Services with systemtcl Configuring Basic Networking Manually Configuring Basic Networking with NetworkManager LAMP Server Basics LAMP Overview Configuring the Apache Web Server Common Directives Apache Virtual Hosting Configuring an Open Source Database MySQL MariaDB PHP Basics Perl CGI Scripting Introduction to System Security Security Overview Maintaining System Security Server Access Physical Security Network Security Security Tools Port Probing with nmap Intrusion Detection and Prevention PAM Security Modules Scanning the System Maintaining File Integrity Using Firewalls Introduction to firewalld The Samba File Sharing Facility Configure Samba for Linux to Linux/UNIX File Sharing Configure Samba for Linux to Windows File Sharing Use the smbclient Utility to Transfer Files Mount/Connect Samba Shares to Linux and Windows Clients Networked File Systems (NFS) Using NFS to Access Remote File Systems Configuring the NFS Server Configuring the NFS Client Exporting File Systems from the NFS Server to the NFS Client

Duration 5 Days 30 CPD hours This course is intended for Senior Linux system administrators who use high-availability clustering and fault-tolerant shared storage technologies to maximize resiliency of production services. Overview Install and configure a Pacemaker-based high availability cluster. Create and manage highly available services. Troubleshoot common cluster issues. Work with shared storage (iSCSI) and configure multipathing. Implement Logical Volume Manager (LVM) in cluster-aware configurations. Configure GFS2 file systems on storage shared by multiple nodes. Deploy reliable, available critical production services in a high availability cluster In the Red Hat High Availability Clustering (RH436) course, you will learn how to provide highly available network services to a mission-critical enterprise environment through the deployment and management of shared storage and server clusters. Created for senior Linux system administrators, this 4-day course strongly emphasizes lab-based activities. You will set up a cluster of systems running the Pacemaker component of the Red Hat Enterprise Linux High-Availability Add-On, and deploy Linux-based services such as web servers and databases on that cluster. Cluster storage components from the Resilient Storage Add-On are also covered; installations and applications that require multiple cluster nodes can access the same storage simultaneously. This includes Logical Volume Manager (LVM) Shared Volume Groups, Red Hat Global File System 2 (GFS2), and Device-Mapper Multipath. This course is based on Red Hat Enterprise Linux 8.3. Prerequisites Red Hat Certified System Administrator (RHCSA) exam (EX200) and associated courses. Red Hat Cerfitied Engineer (RHCE) exam (EX294) and associated courses. 1 - Creating high availability clusters Create a basic high availability cluster. 2 - Managing cluster nodes and quorum Manage node membership in the cluster and describe how it impacts cluster operation. 3 - Isolating malfunctioning cluster nodes Isolate unresponsive cluster nodes to protect data and recover services and resources after a failure. 4 - Creating and configuring resources Create basic resources and resource groups to provide highly available services. 5 - Troubleshooting high availability clusters Identify, diagnose, and fix cluster issues. 6 - Automating cluster and resource deployment Deploy a new high availability cluster and cluster resources using Ansible automation. 7 - Managing two-node clusters Operate two-node clusters while identifying and avoiding issues specific to a two-node cluster configuration. 8 - Accessing iSCSI storage Configure iSCSI initiators on your servers to access block-based storage devices provided by network storage arrays or Ceph storage clusters. 9 - Accessing storage devices resiliently Configure resilient access to storage devices that have multiple access paths. 10 - Configuring LVM in clusters Select, configure, and manage the correct LVM configuration for use in your cluster. 11 - Providing storage with the GFS2 cluster file system Use the GFS2 cluster file system to simultaneously pProvide tightly coupled shared storage that can be accessed by multiple nodes. 12 - Eliminating single points of failure Identify and eliminate single points of failure in your cluster to decrease risk and increase average service availability. Note: Course outline is subject to change with technology advances and as the nature of the underlying job evolves. For questions or confirmation on a specific objective or topic, please contact a training specialist. Additional course details: Nexus Humans Red Hat High Availability Clustering (RH436) 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 Red Hat High Availability Clustering (RH436) 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.

Duration 2 Days 12 CPD hours This course is intended for Anyone who works with IBM SPSS Statistics and wants to learn advanced statistical procedures to be able to better answer research questions. Overview Introduction to advanced statistical analysis Group variables: Factor Analysis and Principal Components Analysis Group similar cases: Cluster Analysis Predict categorical targets with Nearest Neighbor Analysis Predict categorical targets with Discriminant Analysis Predict categorical targets with Logistic Regression Predict categorical targets with Decision Trees Introduction to Survival Analysis Introduction to Generalized Linear Models Introduction to Linear Mixed Models This course provides an application-oriented introduction to advanced statistical methods available in IBM SPSS Statistics. Students will review a variety of advanced statistical techniques and discuss situations in which each technique would be used, the assumptions made by each method, how to set up the analysis, and how to interpret the results. This includes a broad range of techniques for predicting variables, as well as methods to cluster variables and cases. Introduction to advanced statistical analysis Taxonomy of models Overview of supervised models Overview of models to create natural groupings Group variables: Factor Analysis and Principal Components Analysis Factor Analysis basics Principal Components basics Assumptions of Factor Analysis Key issues in Factor Analysis Improve the interpretability Use Factor and component scores Group similar cases: Cluster Analysis Cluster Analysis basics Key issues in Cluster Analysis K-Means Cluster Analysis Assumptions of K-Means Cluster Analysis TwoStep Cluster Analysis Assumptions of TwoStep Cluster Analysis Predict categorical targets with Nearest Neighbor Analysis Nearest Neighbor Analysis basics Key issues in Nearest Neighbor Analysis Assess model fit Predict categorical targets with Discriminant Analysis Discriminant Analysis basics The Discriminant Analysis model Core concepts of Discriminant Analysis Classification of cases Assumptions of Discriminant Analysis Validate the solution Predict categorical targets with Logistic Regression Binary Logistic Regression basics The Binary Logistic Regression model Multinomial Logistic Regression basics Assumptions of Logistic Regression procedures Testing hypotheses Predict categorical targets with Decision Trees Decision Trees basics Validate the solution Explore CHAID Explore CRT Comparing Decision Trees methods Introduction to Survival Analysis Survival Analysis basics Kaplan-Meier Analysis Assumptions of Kaplan-Meier Analysis Cox Regression Assumptions of Cox Regression Introduction to Generalized Linear Models Generalized Linear Models basics Available distributions Available link functions Introduction to Linear Mixed Models Linear Mixed Models basics Hierachical Linear Models Modeling strategy Assumptions of Linear Mixed Models Additional course details: Nexus Humans 0G09A IBM Advanced Statistical Analysis Using IBM SPSS Statistics (v25) 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 0G09A IBM Advanced Statistical Analysis Using IBM SPSS Statistics (v25) 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.

Duration 4 Days 24 CPD hours This course is intended for This course is best suited to developers, engineers, and architects who want to use use Hadoop and related tools to solve real-world problems. Overview Skills learned in this course include:Creating a data set with Kite SDKDeveloping custom Flume components for data ingestionManaging a multi-stage workflow with OozieAnalyzing data with CrunchWriting user-defined functions for Hive and ImpalaWriting user-defined functions for Hive and ImpalaIndexing data with Cloudera Search Cloudera University?s four-day course for designing and building Big Data applications prepares you to analyze and solve real-world problems using Apache Hadoop and associated tools in the enterprise data hub (EDH). IntroductionApplication Architecture Scenario Explanation Understanding the Development Environment Identifying and Collecting Input Data Selecting Tools for Data Processing and Analysis Presenting Results to the Use Defining & Using Datasets Metadata Management What is Apache Avro? Avro Schemas Avro Schema Evolution Selecting a File Format Performance Considerations Using the Kite SDK Data Module What is the Kite SDK? Fundamental Data Module Concepts Creating New Data Sets Using the Kite SDK Loading, Accessing, and Deleting a Data Set Importing Relational Data with Apache Sqoop What is Apache Sqoop? Basic Imports Limiting Results Improving Sqoop?s Performance Sqoop 2 Capturing Data with Apache Flume What is Apache Flume? Basic Flume Architecture Flume Sources Flume Sinks Flume Configuration Logging Application Events to Hadoop Developing Custom Flume Components Flume Data Flow and Common Extension Points Custom Flume Sources Developing a Flume Pollable Source Developing a Flume Event-Driven Source Custom Flume Interceptors Developing a Header-Modifying Flume Interceptor Developing a Filtering Flume Interceptor Writing Avro Objects with a Custom Flume Interceptor Managing Workflows with Apache Oozie The Need for Workflow Management What is Apache Oozie? Defining an Oozie Workflow Validation, Packaging, and Deployment Running and Tracking Workflows Using the CLI Hue UI for Oozie Processing Data Pipelines with Apache Crunch What is Apache Crunch? Understanding the Crunch Pipeline Comparing Crunch to Java MapReduce Working with Crunch Projects Reading and Writing Data in Crunch Data Collection API Functions Utility Classes in the Crunch API Working with Tables in Apache Hive What is Apache Hive? Accessing Hive Basic Query Syntax Creating and Populating Hive Tables How Hive Reads Data Using the RegexSerDe in Hive Developing User-Defined Functions What are User-Defined Functions? Implementing a User-Defined Function Deploying Custom Libraries in Hive Registering a User-Defined Function in Hive Executing Interactive Queries with Impala What is Impala? Comparing Hive to Impala Running Queries in Impala Support for User-Defined Functions Data and Metadata Management Understanding Cloudera Search What is Cloudera Search? Search Architecture Supported Document Formats Indexing Data with Cloudera Search Collection and Schema Management Morphlines Indexing Data in Batch Mode Indexing Data in Near Real Time Presenting Results to Users Solr Query Syntax Building a Search UI with Hue Accessing Impala through JDBC Powering a Custom Web Application with Impala and Search

NLP Practitioner Diploma is one of our best selling and most popular course. The NLP Practitioner Diploma is organised into 02 modules and includes everything you need to become successful in this profession. To make this course more accessible for you, we have designed it for both part-time and full-time students. You can study at your own pace or become an expert in just 4hours! If you require support, our experienced tutors are always available to help you throughout the comprehensive syllabus of this course and answer all your queries through email. Why choose this course Earn an e-certificate upon successful completion. Accessible, informative modules taught by expert instructors Study in your own time, at your own pace, through your computer tablet or mobile device Benefit from instant feedback through mock exams and multiple-choice assessments Get 24/7 help or advice from our email and live chat teams Full Tutor Support on Weekdays 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 Mock exams Multiple-choice assessment Certification After the successful completion of the final assessment, you will receive a CPD-accredited certificate of achievement. The PDF certificate is for £9.99, and it will be sent to you immediately after through e-mail. You can get the hard copy for £15.99, which will reach your doorsteps by post. Who is this course for? NLP Practitioner Diploma is suitable for anyone who want to gain extensive knowledge, potential experience and professional skills in the related field. This is a great opportunity for all student from any academic backgrounds to learn more on this subject.

Looking to bring your AI knowledge to life in a visually powerful way? Our Hands-on Machine Learning Project – Auto Image Captioning for Social Media Course takes you deep into the fascinating world of machine-generated descriptions. With social media driving more engagement through visuals than ever, this course helps you grasp how AI can generate captions that not only describe but also engage, contextualise, and communicate effectively. The focus is sharply tuned to image captioning technology and its role in today’s media-driven, attention-tight landscape. Expect to work your way through a structured learning journey where you’ll explore the building blocks of machine learning and how these elements are applied in automated image captioning. Whether you're aiming to polish your ML project portfolio or understand how AI is quietly shaping the way content is created and consumed online, this course gives you just the right amount of edge — no gimmicks, no fluff, just what matters. All content is delivered fully online, making it a flexible and accessible way to deepen your understanding of AI-powered communication tools used across social media platforms. Learning Outcomes: Develop an auto image captioning system using machine learning. Preprocess image and caption data. Define and evaluate the model. Deploy your machine learning app on AWS EC2 instance.Gain real-world experience in machine learning app development. The Hands-on Machine Learning Project - Auto Image Captioning for Social Media Platform course is designed to give you a comprehensive understanding of how to develop an auto image captioning system using machine learning. The course covers topics such as importing libraries, preprocessing text and image data, defining and evaluating the model, and deploying your machine learning app on AWS EC2 instance. You'll have access to the caption dataset and image dataset for training and test purposes, providing you with hands-on experience in machine learning app development. This course is perfect for aspiring data scientists, machine learning engineers, and developers who want to gain real-world experience in machine learning app development. With the skills and knowledge gained from this course, you'll be able to create your own auto image captioning system and start a career in the exciting field of machine learning. Hands on Machine Learning Project - Auto Image Captioning for Social Media Course Curriculum Section 01: Introduction Introduction to Course Section 02: Building the Auto Image Captioning Import the Libraries Accessing the Caption Dataset for Training Accessing the Image DataSet for Training Preprocessing the Text Data Pre-Process and Load Captions Data Loading the Captions for Training and Test Data Preprocessing of Image Data Loading Features for Train and Test Dataset Text Tokenization and Sequence Text Data Generators Define the Model Evaluation of Model Test the Model Section 03: Deployment of Machine Learning App Create Streamlit App Streamlit Prediction Test Streamlit App Deploy Streamlit on AWS EC2 Instance How is the course assessed? Upon completing an online module, you will immediately be given access to a specifically crafted MCQ test. For each test, the pass mark will be set to 60%. Exam & Retakes: It is to inform our learners that the initial exam for this online course is provided at no additional cost. In the event of needing a retake, a nominal fee of £9.99 will be applicable. Certification Upon successful completion of the assessment procedure, learners can obtain their certification by placing an order and remitting a fee of __ GBP. £9 for PDF Certificate and £15 for the Hardcopy Certificate within the UK ( An additional £10 postal charge will be applicable for international delivery). CPD 10 CPD hours / points Accredited by CPD Quality Standards Who is this course for? Aspiring data scientists. Machine learning engineers. Developers interested in machine learning app development. Anyone interested in the field of machine learning. Professionals looking to upskill in the latest technology. Requirements There are no formal entry requirements for the course, with enrollment open to anyone! Career path Data Scientist: £40,000 to £80,000 per year. Machine Learning Engineer: £55,000 to £90,000 per year. Software Developer: £30,000 to £60,000 per year. Artificial Intelligence Developer: £40,000 to £80,000 per year. Computer Vision Engineer: £45,000 to £85,000 per year. Certificates Certificate of completion Digital certificate - £9 You can apply for a CPD Accredited PDF Certificate at the cost of £9. Certificate of completion Hard copy certificate - £15 Hard copy can be sent to you via post at the expense of £15.

Ready to go beyond the basics? The JavaScript Advanced Training Course is tailored for learners who already understand the fundamentals and are eager to sharpen their scripting edge. This course dives into asynchronous programming, closures, higher-order functions, module patterns, and more – all laid out with clarity and purpose. Whether you're brushing up or building out your skills, you'll find this course paced to keep things flowing without ever feeling overwhelming. Think of it as levelling up without the drama. Expect engaging lessons designed to explain the deeper mechanisms behind how JavaScript truly operates in the browser. We’ll unravel common pitfalls, explore performance techniques, and demystify complex concepts in a straightforward way. It's ideal for developers who want to write cleaner, faster, and more efficient code – all while learning in a structured, accessible format. So, if you're looking to refine your scripting finesse and take control of your code, this course is made with you in mind. Learning outcomes: Understand the basics of JavaScript programming language Learn how to work with loops and operators Understand how to enable and place JavaScript on a web page Develop skills in creating multimedia and interactive features using JavaScript Learn how to use image maps and animations in web development The JavaScript Advanced Training course is designed for individuals who are interested in expanding their knowledge of JavaScript programming language. This course covers advanced topics such as loops, variables, and operators, and how to enable and place JavaScript on a web page. Students will also learn how to use JavaScript to create multimedia and interactive features, including image maps and animations. This course is ideal for those who have a basic understanding of JavaScript and are looking to take their skills to the next level. It is also suitable for web developers who want to enhance their skill set and create more interactive and engaging web pages. JavaScript Advanced Training Course Curriculum Section 01: Introduction Section 02: Loop Section 03: Example Section 04: Print and Animation Section 05: Image Map and Multimedia Section 06: JavaScript Enabling and Placement Section 07: JavaScript Variables and Operators Section 08: While Loop How is the course assessed? Upon completing an online module, you will immediately be given access to a specifically crafted MCQ test. For each test, the pass mark will be set to 60%. Exam & Retakes: It is to inform our learners that the initial exam for this online course is provided at no additional cost. In the event of needing a retake, a nominal fee of £9.99 will be applicable. Certification Upon successful completion of the assessment procedure, learners can obtain their certification by placing an order and remitting a fee of __ GBP. £9 for PDF Certificate and £15 for the Hardcopy Certificate within the UK ( An additional £10 postal charge will be applicable for international delivery). CPD 10 CPD hours / points Accredited by CPD Quality Standards Who is this course for? Individuals with a basic understanding of JavaScript who want to expand their knowledge Web developers who want to enhance their skill set Anyone interested in creating interactive and engaging web pages Students pursuing a career in web development Entrepreneurs and business owners who want to develop their own websites Requirements There are no formal entry requirements for the course, with enrollment open to anyone! Career path Web Developer Front-end Developer Full-stack Developer Software Engineer UI/UX Designer Salary range in the UK: £25,000 - £60,000 Certificates Certificate of completion Digital certificate - £9 You can apply for a CPD Accredited PDF Certificate at the cost of £9. Certificate of completion Hard copy certificate - £15 Hard copy can be sent to you via post at the expense of £15.

Take your Python programming knowledge several notches higher with this advanced training course designed for learners who already speak Python fluently—but want to speak it better. This course delves into deeper aspects of the language, brushing aside the basics and stepping into the more elegant, expressive, and efficient use of Python. From working confidently with decorators, generators, and closures, to understanding asynchronous programming and advanced data structures—this course is tailored for those who want their code to do more, with less. Python may be known for its simplicity, but once you scratch beneath the surface, there’s an entire world of finesse waiting to be explored. Whether you’re brushing up for senior-level roles, fine-tuning your automation skills, or aiming to make your code leaner and smarter—this course offers a structured approach to tackling the tricky bits of Python with a touch of confidence and a dash of clarity. Let’s just say, if Python had an upper crust, you’re about to join it. Learning Outcomes: Gain a deeper understanding of advanced-level Python concepts. Learn how to work with files and handle advanced file operations. Discover how to create and use Python classes to write efficient and maintainable code. Understand how to use library functions to streamline your workflow and take your Python development skills to the next level. Learn how to use Python to build real-world projects and applications. The Python Advanced Training course is designed to provide you with the skills and knowledge you need to become a proficient Python developer. Whether you're a beginner or an experienced programmer looking to enhance your Python skills, this course is perfect for you. Starting with the basics of file handling and moving on to more advanced topics, such as classes and library functions, this course covers everything you need to know to become a master Python developer. You'll learn how to handle advanced file operations, create and use Python classes to write efficient and maintainable code and use library functions to streamline your workflow and take your Python development skills to the next level. Python Advanced Training Course Curriculum Section 01: Introduction Section 02: File Handling Section 03: Python Classes Section 04: Library Functions How is the course assessed? Upon completing an online module, you will immediately be given access to a specifically crafted MCQ test. For each test, the pass mark will be set to 60%. Exam & Retakes: It is to inform our learners that the initial exam for this online course is provided at no additional cost. In the event of needing a retake, a nominal fee of £9.99 will be applicable. Certification Upon successful completion of the assessment procedure, learners can obtain their certification by placing an order and remitting a fee of __ GBP. £9 for PDF Certificate and £15 for the Hardcopy Certificate within the UK ( An additional £10 postal charge will be applicable for international delivery). CPD 10 CPD hours / points Accredited by CPD Quality Standards Who is this course for? Python developers who want to expand their knowledge of advanced Python concepts. Programmers who want to enhance their Python skills and build real-world projects. Entrepreneurs who want to develop their own Python-based applications. Students who want to enhance their Python skills and prepare for a career in programming. Anyone who wants to take their Python programming skills to the next level. Career path Python Developer: £28,000 - £55,000 Data Analyst: £24,000 - £45,000 Software Engineer: £28,000 - £60,000 Technical Lead: £40,000 - £90,000 Chief Technology Officer: £90,000 - £250,000 Certificates Certificate of completion Digital certificate - £9 You can apply for a CPD Accredited PDF Certificate at the cost of £9. Certificate of completion Hard copy certificate - £15 Hard copy can be sent to you via post at the expense of £15.