2204 Developer courses in Leicester delivered Online

About This VILT This 3 half-day course is designed to give a clear businessperson’s summary of the technological, market and economic/competitive issues around the key commodities which can be decarbonised through the use of clean hydrogen in their production. It will examine direct derivatives such as ammonia, methanol and synfuels, along with the impact clean hydrogen may have on the production and trading of other products such as green steel. Clear explanations will be given on technological pathways and key terminologies, in language accessible to non-engineers and commercial businesspeople. The positioning of these hydrogen derivatives in both current and potential future markets will be presented, framed with discussion around the economic and competitive factors which will determine market growth As well as explaining key concepts, the presented content will draw on current market examples, published models, scenarios and forecasts, and on fundamental physical and chemical constraints (for example illustrated by utilising simple calculations and quantifications). Download your brochure Email me the brochure TRAINING OBJECTIVES Upon completion of this VILT course, the participants will be able to: Review the key derivatives of hydrogen, with their market drivers Understand common terminology and technologies within the sector Quantify essential metrics and constraints to the production and trade of hydrogen derivatives Assess the role of clean ammonia in the future hydrogen supply chain Analyse the pathways to combine clean hydrogen with captured CO2 Understand how different policy mechanisms and end-use drivers will influence the growth and competition between different hydrogen derivatives Examine market and project examples, both current and planned Assess the impact of decarbonisation in key sectors such as shipping, aviation and power TARGET AUDIENCE This VILT course has been specifically designed for: Business developers Company strategy developers Investors Product and project management executives Policymakers and regulators Other commercial roles (e.g. marketing, regulatory etc.) Engineers or technical people entering new roles / new to the subject COURSE LEVEL Intermediate TRAINING METHODS The VILT will be delivered online in 3 half-day sessions comprising 4 hours per day, including time for lectures, discussion, quizzes and short classroom exercises. Additionally, some self-study will be requested. Participants are invited but not obliged to bring a short presentation (10 mins max) on a practical problem they encountered in their work. This will then be explained and discussed during the VILT. A short test or quiz will be held at the end the course. TRAINER Your Expert Course Instructor is an internationally renowned energy communicator and business educator, focused on the interconnected clean energy transition topics of renewable power, energy storage, energy system electrification and hydrogen. His own independent technology tracking, market assessment and opportunity/risk analysis is delivered to clients through a mix of business advisory work, commissioned content, small-group training (online & in-person), and one-to-one executive coaching (online). In the hydrogen sector, he is currently lead consultant and trainer to the World Hydrogen Leaders network, and writer of their ‘This Week in Hydrogen’ news column. He is also co-presenter of the ‘New Energy Chinwag’ podcast, which regularly covers hydrogen-related issues. During more than 15 years as an independent energy expert, he has helped companies from large multinationals to innovative start-ups – totalling assignments in over 30 countries across 5 continents. Most recently, he has presented clean energy training in locations as diverse as Singapore, the UK, South Africa, The Philippines, the USA, Mexico, Spain and Dubai – and, in recent times of course, online to international audiences from across the world. Prior to this, he was Research Director for over 10 years at Informa, a $9 billion business intelligence provider; where he drove new market identification, analysis and project deployment work, and managed teams in the UK and US. He has a strong science background, holding a 1st Class Honours degree in Natural Sciences from the University of Cambridge, a PhD in Earth Sciences and a further Diploma in Economics & Sustainability from the UK’s Open University. Download your brochure Email me the brochure POST TRAINING COACHING SUPPORT (OPTIONAL) To further optimise your learning experience from our courses, we also offer individualized “One to One” coaching support for 2 hours post training. We can help improve your competence in your chosen area of interest, based on your learning needs and available hours. This is a great opportunity to improve your capability and confidence in a particular area of expertise. It will be delivered over a secure video conference call by one of our senior trainers. They will work with you to create a tailor-made coaching program that will help you achieve your goals faster. Request for further information post training support and fees applicable

Elevate your expertise in clean hydrogen derivatives - ammonia, methanol, and synthetic hydrocarbon with EnergyEdge's course. Enroll now for virtual instructor-led training!

DevOps demystified training course description This course is an introduction to DevOps. The course emphasizes communication, collaboration , integration, and automation to improve the workflow between developers and IT operations professionals. Improved workflows lead to more opportunities to design software and services in a more agile fashion. This course is a basis for discovering the most important DevOps concepts and to understand the principles and methods behind this. The course will leave you with the inspiration to be the advocate of change. What will you learn Explain DevOps principles. Describe the relationship between Agile , Lean and IT Service Management ( ITSM). Describe methods for automation and technology factors. Describe considerations when changing. Describe challenges, risks and critical success factors. DevOps demystifieds training course details Who will benefit: Non-technical staff involved with DevOps. Prerequisites: None. Duration 1 day DevOps demystified training course contents Why DevOps? From a business perspective From an IT perspective Stereotypes of Dev and Ops: perception and reality What is DevOps? Introduction DevOps Goals DevOps Added value of DevOps Proven Results DevOps for businesses DevOps principles (The Three Ways) DevOps and other frameworks DevOps and Agile DevOps and Lean DevOps and IT Service Management DevOps culture Characteristics of a DevOps culture Organizational Considerations DevOps DevOps stakeholders DevOps roles DevOps teams DevOps organizational structures DevOps methods Continuous Integration Continuous delivery Continuous deployment Value stream mapping Kanban Theory of Constraints Improvement Kata Deming's quality circle ITSM processes DevOps and Automation Methods for DevOps automation Longevity and tools categories DevOps applications Transitioning to a DevOps culture Implementation Challenges, risks and critical success factors Measuring DevOps successes

Duration 1 Days 6 CPD hours This course is intended for Individuals responsible for articulating the technical benefits of AWS services Individuals interested in learning how to get started with using AWS SysOps Administrators, Solution Architects and Developers interested in using AWS services Overview Recognize terminology and concepts as they relate to the AWS platform and navigate the AWS Management Console. Understand the foundational services, including Amazon Elastic Compute Cloud (EC2), Amazon Virtual Private Cloud (VPC), Amazon Simple Storage Service (S3), and Amazon Elastic Block Store (EBS). Understand the security measures AWS provides and key concepts of AWS Identity and Access Management (IAM). Understand AWS database services, including Amazon DynamoDB and Amazon Relational Database Service (RDS). Understand AWS management tools, including Auto Scaling, Amazon CloudWatch, Elastic Load Balancing (ELB), and AWS Trusted Advisor. AWS Technical Essentials introduces you to AWS services, and common solutions. It provides you with fundamental knowledge to become more proficient in identifying AWS services. It helps you make informed decisions about IT solutions based on your business requirements and get started working on AWS. Prerequisites Working knowledge of distributed systems Familiarity with general networking concepts Working knowledge of multi-tier architectures Familiarity with cloud computing concepts 1 - AWS introduction and history AWS Global Infrastructure Demonstration: AWS Management Console 2 - AWS Storage Identify key AWS storage options Describe Amazon EBS Create an Amazon S3 bucket and manage associated objects 3 - Compute, network and storage services Amazon Elastic Compute Cloud (EC2) Amazon Virtual Private Cloud (VPC) Amazon Simple Storage Service (S3) Amazon Elastic Block Store (EBS) Demonstration: Amazon Simple Storage Service (S3) Hands-on lab: Build your VPC and launch a web server 4 - AWS Security, AWS Identity and Access Management (IAM) AWS Identity and Access Management (IAM) Demonstration: AWS Identity and Access Management (IAM) 5 - Compute Services & Networking Identify the different AWS compute and networking options Describe an Amazon Virtual Private Cloud (VPC) Create an Amazon EC2 instance Use Amazon EBS with Amazon EC2 6 - Managed Services & Database Describe Amazon DynamoDB Understand key aspects of Amazon RDS Launch an Amazon RDS instance 7 - Databases (RDS, DynamoDB) SQL and NoSQL databases Data storage considerations Hands-on lab: Build your database server and connect to it 8 - AWS elasticity and management tools Auto scaling Load balancing Cloud Watch Trusted Advisor Hands-on lab: Scale and load balance your architecture 9 - Deployment and Management Identify what is CloudFormation Describe Amazon CloudWatch metrics and alarms Describe Amazon Identity and Access Management (IAM)

Overview This comprehensive course on JavaScript Project - Game Development with JS will deepen your understanding on this topic. After successful completion of this course you can acquire the required skills in this sector. This JavaScript Project - Game Development with JS comes with accredited certification from CPD, which will enhance your CV and make you worthy in the job market. So enrol in this course today to fast-track your career ladder. How will I get my certificate? You may have to take a quiz or a written test online during or after the course. After successfully completing the course, you will be eligible for the certificate. Who is This course for? There is no experience or previous qualifications required for enrolment on this JavaScript Project - Game Development with JS. It is available to all students, of all academic backgrounds. Requirements Our JavaScript Project - Game Development with JS is fully compatible with PC's, Mac's, Laptop, Tablet and Smartphone devices. This course has been designed to be fully compatible with tablets and smartphones so you can access your course on Wi-Fi, 3G or 4G. There is no time limit for completing this course, it can be studied in your own time at your own pace. Career Path Learning this new skill will help you to advance in your career. It will diversify your job options and help you develop new techniques to keep up with the fast-changing world. This skillset will help you to- Open doors of opportunities Increase your adaptability Keep you relevant Boost confidence And much more! Course Curriculum 2 sections • 12 lectures • 01:45:00 total length •Introduction to Beware of the Jolly Roger: 00:03:00 •Creating the HTML File: 00:12:00 •Adding CSS to it: 00:13:00 •Understanding Math Random: 00:12:00 •Adding Javascript: 00:05:00 •Calling the Function: 00:10:00 •Clicked on 10 Flags: 00:10:00 •Jolly Roger: 00:11:00 •Win or Lose: 00:06:00 •Flag is Displayed: 00:03:00 •Understanding Arrays: 00:12:00 •Different Flag Opening at Every Click: 00:08:00

This course will help you become familiar with the implementation of creational design patterns. Featuring real-world examples written in modern C++, each pattern is explained in detail to help you to understand how the pattern can be implemented efficiently using language features.

Delve into the world of data analysis with 'R Programming for Data Science,' a course designed to guide learners through the intricacies of R, a premier programming language in the data science domain. The course opens with a broad perspective on data science, illuminating the pivotal role of R in this field. Learners are then introduced to R and RStudio, equipping them with the foundational tools and interfaces essential for R programming. The curriculum progresses with an introduction to the basics of R, ensuring learners grasp the core principles that underpin more complex operations. A highlight of this course is its in-depth exploration of R's versatile data structures, including vectors, matrices, factors, and data frames. Each unit is crafted to provide learners with a comprehensive understanding of these structures, pivotal for effective data handling and manipulation. The course also emphasizes the importance of relational and logical operators in R, key elements for executing data operations. As the course advances, learners will engage with the nuances of conditional statements and loops, essential for writing efficient and dynamic R scripts. Moving into more advanced territories, the course delves into the creation and usage of functions, an integral part of R programming, and the exploration of various R packages that extend the language's capabilities. Learners will also gain expertise in the 'apply' family of functions, crucial for streamlined data processing. Further units cover regular expressions and effective strategies for managing dates and times in data sets. The course concludes with practical applications in data acquisition, cleaning, visualization, and manipulation, ensuring learners are well-prepared to tackle real-world data science challenges using R. Learning Outcomes Develop a foundational understanding of R's role in data science and proficiency in RStudio. Gain fluency in R programming basics, enabling the handling of complex data tasks. Acquire skills in managing various R data structures for efficient data analysis. Master relational and logical operations for advanced data manipulation in R. Learn to create functions and utilize R packages for expanded analytical capabilities. Why choose this R Programming for Data Science course? Unlimited access to the course for a lifetime. Opportunity to earn a certificate accredited by the CPD Quality Standards and CIQ after completing this course. Structured lesson planning in line with industry standards. Immerse yourself in innovative and captivating course materials and activities. Assessments designed to evaluate advanced cognitive abilities and skill proficiency. Flexibility to complete the Course at your own pace, on your own schedule. Receive full tutor support throughout the week, from Monday to Friday, to enhance your learning experience. Unlock career resources for CV improvement, interview readiness, and job success. Who is this R Programming for Data Science course for? Beginners in data science eager to learn R programming. Data analysts and scientists looking to enhance their skills in R. Researchers in various fields requiring advanced data analysis tools. Statisticians seeking to adopt R for more sophisticated data manipulations. Professionals in finance, healthcare, and other sectors needing data-driven insights. Career path Data Scientist (R Expertise): £30,000 - £70,000 Data Analyst (R Programming Skills): £27,000 - £55,000 Bioinformatics Scientist (R Proficiency): £35,000 - £60,000 Quantitative Analyst (R Knowledge): £40,000 - £80,000 Research Analyst (R Usage): £25,000 - £50,000 Business Intelligence Developer (R Familiarity): £32,000 - £65,000 Prerequisites This R Programming for Data Science does not require you to have any prior qualifications or experience. You can just enrol and start learning.This R Programming for Data Science was made by professionals and it is compatible with all PC's, Mac's, tablets and smartphones. You will be able to access the course from anywhere at any time as long as you have a good enough internet connection. Certification After studying the course materials, there will be a written assignment test which you can take at the end of the course. After successfully passing the test you will be able to claim the pdf certificate for £4.99 Original Hard Copy certificates need to be ordered at an additional cost of £8. Course Curriculum Unit 01: Data Science Overview Introduction to Data Science 00:01:00 Data Science: Career of the Future 00:04:00 What is Data Science? 00:02:00 Data Science as a Process 00:02:00 Data Science Toolbox 00:03:00 Data Science Process Explained 00:05:00 What's next? 00:02:00 Unit 02: R and RStudio Engine and coding environment 00:03:00 Installing R and RStudio 00:04:00 RStudio: A quick tour 00:04:00 Unit 03: Introduction to Basics Arithmetic with R 00:03:00 Variable assignment 00:04:00 Basic data types in R 00:03:00 Unit 04: Vectors Creating a vector 00:05:00 Naming a vector 00:04:00 Arithmetic calculations on vectors 00:07:00 Vector selection 00:06:00 Selection by comparison 00:04:00 Unit 05: Matrices What's a Matrix? 00:02:00 Analyzing Matrices 00:03:00 Naming a Matrix 00:05:00 Adding columns and rows to a matrix 00:06:00 Selection of matrix elements 00:03:00 Arithmetic with matrices 00:07:00 Additional Materials 00:00:00 Unit 06: Factors What's a Factor? 00:02:00 Categorical Variables and Factor Levels 00:04:00 Summarizing a Factor 00:01:00 Ordered Factors 00:05:00 Unit 07: Data Frames What's a Data Frame? 00:03:00 Creating Data Frames 00:20:00 Selection of Data Frame elements 00:03:00 Conditional selection 00:03:00 Sorting a Data Frame 00:03:00 Additional Materials 00:00:00 Unit 08: Lists Why would you need lists? 00:01:00 Creating a List 00:06:00 Selecting elements from a list 00:03:00 Adding more data to the list 00:02:00 Additional Materials 00:00:00 Unit 09: Relational Operators Equality 00:03:00 Greater and Less Than 00:03:00 Compare Vectors 00:03:00 Compare Matrices 00:02:00 Additional Materials 00:00:00 Unit 10: Logical Operators AND, OR, NOT Operators 00:04:00 Logical operators with vectors and matrices 00:04:00 Reverse the result: (!) 00:01:00 Relational and Logical Operators together 00:06:00 Additional Materials 00:00:00 Unit 11: Conditional Statements The IF statement 00:04:00 IFELSE 00:03:00 The ELSEIF statement 00:05:00 Full Exercise 00:03:00 Additional Materials 00:00:00 Unit 12: Loops Write a While loop 00:04:00 Looping with more conditions 00:04:00 Break: stop the While Loop 00:04:00 What's a For loop? 00:02:00 Loop over a vector 00:02:00 Loop over a list 00:03:00 Loop over a matrix 00:04:00 For loop with conditionals 00:01:00 Using Next and Break with For loop 00:03:00 Additional Materials 00:00:00 Unit 13: Functions What is a Function? 00:02:00 Arguments matching 00:03:00 Required and Optional Arguments 00:03:00 Nested functions 00:02:00 Writing own functions 00:03:00 Functions with no arguments 00:02:00 Defining default arguments in functions 00:04:00 Function scoping 00:02:00 Control flow in functions 00:03:00 Additional Materials 00:00:00 Unit 14: R Packages Installing R Packages 00:01:00 Loading R Packages 00:04:00 Different ways to load a package 00:02:00 Additional Materials 00:00:00 Unit 15: The Apply Family - lapply What is lapply and when is used? 00:04:00 Use lapply with user-defined functions 00:03:00 lapply and anonymous functions 00:01:00 Use lapply with additional arguments 00:04:00 Additional Materials 00:00:00 Unit 16: The apply Family - sapply & vapply What is sapply? 00:02:00 How to use sapply 00:02:00 sapply with your own function 00:02:00 sapply with a function returning a vector 00:02:00 When can't sapply simplify? 00:02:00 What is vapply and why is it used? 00:04:00 Additional Materials 00:00:00 Unit 17: Useful Functions Mathematical functions 00:05:00 Data Utilities 00:08:00 Additional Materials 00:00:00 Unit 18: Regular Expressions grepl & grep 00:04:00 Metacharacters 00:05:00 sub & gsub 00:02:00 More metacharacters 00:04:00 Additional Materials 00:00:00 Unit 19: Dates and Times Today and Now 00:02:00 Create and format dates 00:06:00 Create and format times 00:03:00 Calculations with Dates 00:03:00 Calculations with Times 00:07:00 Additional Materials 00:00:00 Unit 20: Getting and Cleaning Data Get and set current directory 00:04:00 Get data from the web 00:04:00 Loading flat files 00:03:00 Loading Excel files 00:05:00 Additional Materials 00:00:00 Unit 21: Plotting Data in R Base plotting system 00:03:00 Base plots: Histograms 00:03:00 Base plots: Scatterplots 00:05:00 Base plots: Regression Line 00:03:00 Base plots: Boxplot 00:03:00 Unit 22: Data Manipulation with dplyr Introduction to dplyr package 00:04:00 Using the pipe operator (%>%) 00:02:00 Columns component: select() 00:05:00 Columns component: rename() and rename_with() 00:02:00 Columns component: mutate() 00:02:00 Columns component: relocate() 00:02:00 Rows component: filter() 00:01:00 Rows component: slice() 00:04:00 Rows component: arrange() 00:01:00 Rows component: rowwise() 00:02:00 Grouping of rows: summarise() 00:03:00 Grouping of rows: across() 00:02:00 COVID-19 Analysis Task 00:08:00 Additional Materials 00:00:00 Assignment Assignment - R Programming for Data Science 00:00:00

Course Overview: The "FinTech and Big Data Analytics" course provides an in-depth exploration of the dynamic intersection between financial technology (FinTech) and big data. Learners will gain essential knowledge about the innovative solutions disrupting the financial services industry, such as cryptocurrencies, insurtech, and regtech. The course offers insights into the tools, technologies, and trends shaping the future of finance, with a specific focus on how big data analytics is transforming business models and decision-making. By the end of the course, learners will have a comprehensive understanding of FinTech's growth and its applications, enabling them to make informed decisions in this rapidly evolving field. Course Description: This course delves deeper into the core concepts of financial technology and big data, exploring the impact of FinTech innovations on traditional financial systems. Topics covered include the rise of cryptocurrencies, regulatory technology (RegTech), the development of insurance technologies (InsurTech), and the use of big data in reshaping business strategies. Learners will explore the key technologies that drive FinTech, such as blockchain, artificial intelligence (AI), and machine learning, and learn how they enable data-driven decision-making in finance. The course prepares learners for the evolving future of FinTech, equipping them with the necessary skills to understand and navigate this transformative landscape. Course Modules: Module 01: Introduction to Financial Technology – FinTech Module 02: Exploring Cryptocurrencies Module 03: RegTech Module 04: Rise of InsurTechs Module 05: Big Data Basics: Understanding Big Data Module 06: The Future of FinTech (See full curriculum) Who is this course for? Individuals seeking to understand the financial technology landscape. Professionals aiming to advance their careers in the rapidly evolving FinTech sector. Beginners with an interest in emerging financial technologies and data analytics. Entrepreneurs looking to innovate within the financial services industry. Career Path: Financial Analyst FinTech Specialist Data Analyst in Financial Services Blockchain Developer RegTech Consultant InsurTech Specialist Big Data Analyst in Finance

Duration 5 Days 30 CPD hours This course is intended for This course is designed for experienced integration specialists and senior-level developers with experience in application development, messaging middleware applications, and transport protocols such as HTTP and FTP. Overview Describe the features and uses of IBM App Connect Enterprise Develop, deploy, and test message flow applications Generate message flow applications from predefined patterns Use the IBM App Connect Enterprise Toolkit problem determination aids to diagnose and solve development and runtime errors Describe the function and appropriate use of IBM App Connect Enterprise processing nodes Write basic Extended Structured Query Language and Java programs to transform data Use the IBM Graphical Data Mapping editor to transform data Define, use, and test simple XML and Data Format Description Language (DFDL) data models Describe supported transport protocols and how to call them in message flows IBM App Connect Enterprise provides connectivity and universal data transformation in heterogeneous IT environments. It enables businesses of any size to eliminate point-to-point connections and batch processing, regardless of operating system, protocol, and data format. This course teaches you how to use IBM App Connect Enterprise to develop, deploy, and support message flow applications. These applications use various messaging topologies to transport messages between service requesters and service providers, and allow the messages to be routed, transformed, and enriched during processing. In this course, you learn how to construct applications to transport and transform data. The course explores how to control the flow of data by using various processing nodes, and how to use databases and maps to transform and enrich data during processing. You also learn how to construct data models by using the Data Format Description Language (DFDL) Course Outline Introduction to IBM App Connect Enterprise Application development fundamentals Exercise: Importing and testing a message flow Creating message flow applications Exercise: Creating a message flow application Connecting to IBM MQ Exercise: Connecting to IBM MQ Controlling the flow of messages Exercise: Adding flow control to a message flow application Modeling the data Exercise: Creating a DFDL model Processing file data Exercise: Processing file data Using problem determination tools and help resources Exercise: Using problem determination tools Exercise: Implementing explicit error handling Mapping messages with the Graphical Data Mapping editor Referencing a database in a message flow application Exercise: Referencing a database in a map Using Compute nodes to transform messages Exercise: Transforming data by using the Compute and JavaCompute nodes Processing JMS, HTTP, and web service messages Preparing for production Exercise: Creating a runtime-aware message flow Additional course details: Nexus Humans WM668G IBM App Connect Enterprise V11 Application Development 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 WM668G IBM App Connect Enterprise V11 Application Development 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.

Phonics Teaching: Phonics Teaching Online Do you worry about phonics instruction for kids learning to read and write? To help you comprehend this part, we have created a Phonics Teaching: Phonics Teaching Course. All the fundamentals are covered in this Phonics Teaching: Phonics Teaching Course, along with the importance of early phonics training for later, more advanced phonics education. The Phonics Teaching Course also explains the responsibilities of a phonics teacher. This Phonics Teaching Course describes involvement, awareness, and teaching strategies. The Phonics Teaching Course also explains how to satisfy individual requirements and maintain records. Register in the Phonics Teaching: Phonics Teaching Course to get all the necessary information, ranging from the foundations to the more intricate ideas, to effectively teach phonics. Special Offers of this Phonics Teaching: Phonics Teaching Course: This Phonics Teaching: Phonics Teaching Course includes a FREE PDF Certificate. Lifetime access to this Phonics Teaching: Phonics Teaching Course Instant access to this Phonics Teaching: Phonics Teaching Course 24/7 Support Available to this Phonics Teaching: Phonics Teaching Course Phonics Teaching: Phonics Teaching Online This Phonics Teaching Course explains all the basics including the significance of early phonics instruction to higher-level phonics instruction. Also, the Phonics Teaching Course explains the career of a phonics teacher. Teaching techniques, awareness and engagement are described in this Phonics Teaching Course. Moreover, how to keep records and meet individual needs is explained in the Phonics Teaching Course. Who is this course for? Phonics Teaching: Phonics Teaching Online Anyone who works with children, including parents, teachers, and teaching assistants, will find this Phonics Teaching: Phonics Teaching Course to be excellent. Requirements Phonics Teaching: Phonics Teaching Online To enrol in this Phonics Teaching: Phonics Teaching Course, students must fulfil the following requirements: Good Command over English language is mandatory to enrol in our Phonics Teaching: Phonics Teaching Course. Be energetic and self-motivated to complete our Phonics Teaching: Phonics Teaching Course. Basic computer Skill is required to complete our Phonics Teaching: Phonics Teaching Course. If you want to enrol in our Phonics Teaching: Phonics Teaching Course, you must be at least 15 years old. Career path Phonics Teaching: Phonics Teaching Online You can get employment as a phonics teacher, primary school teacher, curriculum developer, and more after completing the Phonics Teaching: Phonics Teaching Course!