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Description Learn the process of complete App development knowing the use of GraphQL, Prisma, Node, and React through the App Development Complete Diploma (GraphQL Prisma Node & React) course. Its contents aim to teach you the core aspects of app development so that you can establish your career learning all good of this course must. The course teaches you the functions of GraphQL, a query language for API so that you can learn how to build GraphQL server with Prisma, create a frontend CRUD App with React and Apollo Client, and upload files in GraphQL, Prisma, and React application. The App Development Complete Diploma (GraphQL Prisma Node & React) course will also teach you how to execute error handling in Prisma and React, develop your performance in React application, open Prisma and React application to Heroku, set page number in Prisma and React Appolo application, and accomplish web mark in GraphQL and Prisma. It will also teach how to execute, create, delete, and update data through CURD in Prisma and so many other effective features of app development. Look and learn its effective contents to become better app developer. Assessment: This course does not involve any MCQ test. Students need to answer assignment questions to complete the course, the answers will be in the form of written work in pdf or word. Students can write the answers in their own time. Once the answers are submitted, the instructor will check and assess the work. Certification: After completing and passing the course successfully, you will be able to obtain an Accredited Certificate of Achievement. Certificates can be obtained either in hard copy at a cost of £39 or in PDF format at a cost of £24. Who is this Course for? App Development Complete Diploma (GraphQL Prisma Node & React) is certified by CPD Qualifications Standards and CiQ. This makes it perfect for anyone trying to learn potential professional skills. As there is no experience and qualification required for this course, it is available for all students from any academic background. Requirements Our App Development Complete Diploma (GraphQL Prisma Node & React) is fully compatible with any kind of device. Whether you are using Windows computer, Mac, smartphones or tablets, you will get the same experience while learning. Besides that, you will be able to access the course with any kind of internet connection from anywhere at any time without any kind of limitation. Career Path After completing this course you will be able to build up accurate knowledge and skills with proper confidence to enrich yourself and brighten up your career in the relevant job market. Big Picture of Prisma Prisma generates GraphQL API for your datamodel FREE 00:03:00 Connect your resolvers to Prisma API 00:03:00 What is Prisma Query Engine 00:01:00 What is DataModeling in Prisma 00:02:00 What databases are supported by Prisma 00:01:00 What is Prisma Cloud 00:02:00 VS Code Setup FREE 00:03:00 Setting up Prisma 00:11:00 Build GraphQL server with Prisma Update Prisma Data Model 00:12:00 Setup GraphQL server with Prisma 00:13:00 Setup env variables for Primisa endpoint 00:04:00 CRUD in Prisma Create Data Model in Prisma 00:04:00 Fetch Records from Database 00:10:00 Create, Update and Delete Record in Prisma 00:15:00 Create Frontend CRUD App with React and Apollo Client Create Apollo client in React Application 00:07:00 Connect Apollo Client to React 00:05:00 Fetch Data using Apollo Query Component 00:12:00 Understanding render Prop pattern in React 00:09:00 Creating Forms in React 00:10:00 Send GraphQL Mutation from React Component 00:10:00 Updating Apollo Cache After Mutation 00:10:00 Adding Routing with React Router 00:09:00 Render List items to Bootstrap card component 00:01:00 Query for Single Record 00:12:00 Edit Record using update Mutation 00:10:00 Mutation for Delete Record in React Apollo 00:08:00 Authentication in Prisma and GraphQL Restructure the resolver functions into separate folder 00:04:00 Signup User in Prisma and GraphQL 00:12:00 Login User in Prisma and GraphQL 00:07:00 Apply Authentication on Resolvers 00:09:00 Authentication in React Apollo Client Application Send Login Request from Frontend App 00:12:00 Save Token to LocalStorage after LoggedIn 00:03:00 Implement Logout User 00:08:00 Require Authentication on Edit and Delete 00:03:00 Implement Signup User on Frontend 00:12:00 Protect Routes in React using React Router 00:09:00 Add Authorization header to every request in React Apollo Client 00:13:00 Error Handling Create Error Message Component to render Errors 00:07:00 Adding Spinner for Loading Data 00:05:00 Pagination in Prisma and React Apollo Application Paginate List fo records of Prisma 00:06:00 Count all Records using Prisma Connection Query 00:15:00 Create Pagination Controls in Frontend Application 00:06:00 Implement Pagination in React Application 00:12:00 Filtering Records in Prisma 00:04:00 Create Search Course Component 00:05:00 Execute Search Query and display courses 00:10:00 Apply Sorting on the Records 00:07:00 Update Cache after creating records 00:03:00 Fix Cache after Delete Records 00:03:00 Optimistic UI In React Apollo Application Improve UI Performance using Optimistic UI in React Apollo 00:06:00 GraphQL Subscription Project Setup Deploy Prisma and React Application to Heroku Deploy Prisma Project to Heroku 00:13:00 Deploy React Project to Heroku 00:14:00 Subscriptions in Prisma and React Apollo Application GraphQL Subscription Project Setup 00:06:00 Prisma Subscription Demo 00:07:00 Creating Subscription in Prisma GraphQL Server 00:05:00 Subscription in React using Apollo Client 00:13:00 State Management in React Application using Apollo Link Setup Apollo Link State 00:05:00 Fetch Records from Apollo State using Query 00:06:00 Create Task Form Component 00:05:00 Save new Record in Apollo Link State 00:11:00 Update Cache using Fragments 00:11:00 Filter Tasks on the based on Status Value 00:16:00 File Upload in Prisma and React Setup Local Development Server with Prisma and Docker 00:09:00 File Upload Demo with Prisma and React 00:14:00 Bonus: React Fundamentals Create React App using create-react-app cli 00:02:00 Creating React Element 00:05:00 Creating Nested React Elements 00:08:00 How React uses React Elements to Create Virtual DOM 00:01:00 What is DOM 00:03:00 What is Virtual DOM 00:05:00 What are Components in React 00:04:00 Create Component in React 00:06:00 Adding Props Validations 00:03:00 Create Nested Components in React 00:05:00 Create State in React Component 00:08:00 Update Component State using Events 00:08:00 Iterate Array and render Components 00:05:00 Pass Function Parent to Child Component 00:09:00 Convert React Components to JSX 00:09:00 State in React Component 00:05:00 Shallow Merging with setState 00:06:00 Use Props PropTypes and default Props in React Component 00:06:00 Create Stateless Component in React 00:04:00 Communicate with Parent and Child Component 00:07:00 What are LifeCycle Methods in React Component 00:01:00 Types and Phases of LifeCycle Methods 00:04:00 LifeCycle Mounting Methods in Action 00:09:00 LifeCycle Updating Methods in Action 00:07:00 Handling Errors with componentDidCatch 00:08:00 Bonus: GraphQL Basics What is GraphQL 00:04:00 What is GraphQL Query 00:03:00 Arguments in GraphQL Query 00:01:00 Required Arguments in Query 00:02:00 GraphQL Schema and Types 00:04:00 Aliasis in GraphQL 00:02:00 Nested Fields 00:02:00 Operations in GraphQL 00:02:00 Variables in GraphQL 00:04:00 Create Mutations 00:03:00 Directives in GraphQL 00:02:00 Certificate and Transcript Order Your Certificates and Transcripts 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This course is designed to help you master the concepts of JavaScript needed to create interactive web games. You will create five interesting word games that will teach you how to write and test the game code in JavaScript.

Learn about the jQuery library from scratch and stretch your journey from a beginner-level to advanced-level professional with a step-by-step and comprehensive course. A basic understanding of the JavaScript Document Object Model and CSS is suggested as a prerequisite to this course.

Overview The Web Design course will enable you to build and maintain expert websites that will stand out from others in the crowded online market. Whether this is for your own personal use, or on behalf of a client, you'll learn to produce pages and designs that will attract plenty of individuals to your work. You'll find that this informative training program is full of up-to-date techniques and smart tricks to construct an eye-catching site. Without having to be a technical wizard, you'll learn all the fundamentals of creating web fonts, style sheets, grid structures, images, icons, and gifs. Once you have completed this entrusted course, you will achieve a greater understanding of web design and realise that functionality and user-friendliness are as necessary as an attractive colour scheme and dynamic imagery. 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 Online study materials Mock exams Multiple-choice assessment Certificate of Achievement Endorsed Certificate of Achievement from the Quality Licence Scheme Once the course has been completed and the assessment has been passed, all students are entitled to receive an endorsed certificate. This will provide proof that you have completed your training objectives, and each endorsed certificate can be ordered and delivered to your address for only £99. Please note that overseas students may be charged an additional £10 for postage. CPD Certificate of Achievement from Janets Upon successful completion of the course, you will be able to obtain your course completion e-certificate. Print copy by post is also available at an additional cost of £9.99 and PDF Certificate at £4.99. Endorsement This course and/or training programme has been endorsed by the Quality Licence Scheme for its high-quality, non-regulated provision and training programmes. This course and/or training programme is not regulated by Ofqual and is not an accredited qualification. Your training provider will be able to advise you on any further recognition, for example progression routes into further and/or higher education. For further information please visit the Learner FAQs on the Quality Licence Scheme website. Method of Assessment In order to ensure the Quality Licensing scheme endorsed and CPD acknowledged certificate, learners need to score at least 60% pass marks on the assessment process. After submitting assignments, our expert tutors will evaluate the assignments and give feedback based on the performance. After passing the assessment, one can apply for a certificate. Requirements There is no specific requirements for our Web Design course. It is compatible and accessible from any device including Windows, Mac, Android, iOS, Tablets etc. The course requires a moderate Internet connection so it is possible to start learning with any type of Internet from anywhere at anytime without any limitations.

Build 9 projects to master 2 essential and modern technologies: Python and PostgreSQL

In this course, we will learn the basics of coding in Python by understanding the fundamentals of coding with Python, exploring some code examples, and working on three simple Python projects. This course is designed for beginners; however, basic programming understanding is required.

NodeJS allows you to build complex and powerful applications quickly and easily, writing JavaScript code. It also allows you to use JavaScript for web applications with flexibility for a wide range of different purposes. Learn about MongoDB as a database and how to build it as well as Express as a framework to build web apps on top of Node.js.

Learn Python with 200+ real-world examples implemented on PyCharm. Ace functions, classes, objects, dictionary, lists, sets, and tuples. The course also covers math, statistics, and random modules. This is the ideal course for you if you want to advance your Python programming skills or switch to Python programming.

Are you ready to be at the helm, steering the ship into a realm where data is the new gold? In the infinite world of data, where information spirals at breakneck speed, lies a universe rich in potential and discovery: the domain of Data Science and Visualisation. This 'Certificate in Data Science and Visualisation with Machine Learning at QLS Level 3' course unravels the wonders of extracting meaningful insights using Python, the worldwide leading language of data experts. Harnessing the strength of Python, you'll delve deep into data analysis, experience the finesse of visualisation tools, and master the art of Machine Learning. The need to understand, interpret, and act on this data has become paramount, with vast amounts of data increasing the digital sphere. Envision a canvas where raw numbers are transformed into visually compelling stories, and machine learning models foretell future trends. This course provides a meticulous pathway for anyone eager to learn the data representation paradigms backed by Python's robust libraries. Dive into a curriculum rich with analytical explorations, visual artistry, and machine learning predictions. Learning Outcomes Understanding the foundations and functionalities of Python, focusing on its application in data science. Applying various Python libraries like NumPy and Pandas for effective data analysis. Demonstrating proficiency in creating detailed visual narratives using tools like matplotlib, Seaborn, and Plotly. Implementing Machine Learning algorithms in Python using scikit-learn, ranging from regression models to clustering techniques. Designing and executing a holistic data analysis and visualisation project, encapsulating all learned techniques. Exploring advanced topics, encompassing recommender systems and natural language processing with Python. Attaining the confidence to independently analyse complex data sets and translate them into actionable insights.   Video Playerhttps://studyhub.org.uk/wp-content/uploads/2021/03/Data-Science-and-Visualisation-with-Machine-Learning.mp400:0000:0000:00Use Up/Down Arrow keys to increase or decrease volume. Why buy this Certificate in Data Science and Visualisation with Machine Learning at QLS Level 3? Unlimited access to the course for a lifetime. Opportunity to earn a certificate accredited by the CPD Quality Standards after completing this course. Structured lesson planning in line with industry standards. Immerse yourself in innovative and captivating course materials and activities. Assessments are designed to evaluate advanced cognitive abilities and skill proficiency. Flexibility to complete the Certificate in Data Science and Visualisation with Machine Learning at QLS Level 3 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. Who is this Certificate in Data Science and Visualisation with Machine Learning at QLS Level 3 course for? Aspiring data scientists aiming to harness the power of Python. Researchers keen to enrich their analytical and visualisation skills. Analysts aiming to add machine learning to their toolkit. Developers striving to integrate data analytics into applications. Business professionals desiring data-driven decision-making capabilities. Career path Data Scientist: £55,000 - £85,000 Per Annum Machine Learning Engineer: £60,000 - £90,000 Per Annum Data Analyst: £30,000 - £50,000 Per Annum Data Visualisation Specialist: £45,000 - £70,000 Per Annum Natural Language Processing Specialist: £65,000 - £95,000 Per Annum Business Intelligence Developer: £40,000 - £65,000 Per Annum Prerequisites This Certificate in Data Science and Visualisation with Machine Learning at QLS Level 3 does not require you to have any prior qualifications or experience. You can just enrol and start learning. This Certificate in Data Science and Visualisation with Machine Learning at QLS Level 3 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. Endorsed Certificate of Achievement from the Quality Licence Scheme Learners will be able to achieve an endorsed certificate after completing the course as proof of their achievement. You can order the endorsed certificate for only £85 to be delivered to your home by post. For international students, there is an additional postage charge of £10. Endorsement The Quality Licence Scheme (QLS) has endorsed this course for its high-quality, non-regulated provision and training programmes. The QLS is a UK-based organisation that sets standards for non-regulated training and learning. This endorsement means that the course has been reviewed and approved by the QLS and meets the highest quality standards. Please Note: Studyhub is a Compliance Central approved resale partner for Quality Licence Scheme Endorsed courses. Course Curriculum Welcome, Course Introduction & overview, and Environment set-up Welcome & Course Overview 00:07:00 Set-up the Environment for the Course (lecture 1) 00:09:00 Set-up the Environment for the Course (lecture 2) 00:25:00 Two other options to setup environment 00:04:00 Python Essentials Python data types Part 1 00:21:00 Python Data Types Part 2 00:15:00 Loops, List Comprehension, Functions, Lambda Expression, Map and Filter (Part 1) 00:16:00 Loops, List Comprehension, Functions, Lambda Expression, Map and Filter (Part 2) 00:20:00 Python Essentials Exercises Overview 00:02:00 Python Essentials Exercises Solutions 00:22:00 Python for Data Analysis using NumPy What is Numpy? A brief introduction and installation instructions. 00:03:00 NumPy Essentials - NumPy arrays, built-in methods, array methods and attributes. 00:28:00 NumPy Essentials - Indexing, slicing, broadcasting & boolean masking 00:26:00 NumPy Essentials - Arithmetic Operations & Universal Functions 00:07:00 NumPy Essentials Exercises Overview 00:02:00 NumPy Essentials Exercises Solutions 00:25:00 Python for Data Analysis using Pandas What is pandas? A brief introduction and installation instructions. 00:02:00 Pandas Introduction 00:02:00 Pandas Essentials - Pandas Data Structures - Series 00:20:00 Pandas Essentials - Pandas Data Structures - DataFrame 00:30:00 Pandas Essentials - Handling Missing Data 00:12:00 Pandas Essentials - Data Wrangling - Combining, merging, joining 00:20:00 Pandas Essentials - Groupby 00:10:00 Pandas Essentials - Useful Methods and Operations 00:26:00 Pandas Essentials - Project 1 (Overview) Customer Purchases Data 00:08:00 Pandas Essentials - Project 1 (Solutions) Customer Purchases Data 00:31:00 Pandas Essentials - Project 2 (Overview) Chicago Payroll Data 00:04:00 Pandas Essentials - Project 2 (Solutions Part 1) Chicago Payroll Data 00:18:00 Python for Data Visualization using matplotlib Matplotlib Essentials (Part 1) - Basic Plotting & Object Oriented Approach 00:13:00 Matplotlib Essentials (Part 2) - Basic Plotting & Object Oriented Approach 00:22:00 Matplotlib Essentials (Part 3) - Basic Plotting & Object Oriented Approach 00:22:00 Matplotlib Essentials - Exercises Overview 00:06:00 Matplotlib Essentials - Exercises Solutions 00:21:00 Python for Data Visualization using Seaborn Seaborn - Introduction & Installation 00:04:00 Seaborn - Distribution Plots 00:25:00 Seaborn - Categorical Plots (Part 1) 00:21:00 Seaborn - Categorical Plots (Part 2) 00:16:00 Seborn-Axis Grids 00:25:00 Seaborn - Matrix Plots 00:13:00 Seaborn - Regression Plots 00:11:00 Seaborn - Controlling Figure Aesthetics 00:10:00 Seaborn - Exercises Overview 00:04:00 Seaborn - Exercise Solutions 00:19:00 Python for Data Visualization using pandas Pandas Built-in Data Visualization 00:34:00 Pandas Data Visualization Exercises Overview 00:03:00 Panda Data Visualization Exercises Solutions 00:13:00 Python for interactive & geographical plotting using Plotly and Cufflinks Plotly & Cufflinks - Interactive & Geographical Plotting (Part 1) 00:19:00 Plotly & Cufflinks - Interactive & Geographical Plotting (Part 2) 00:14:00 Plotly & Cufflinks - Interactive & Geographical Plotting Exercises (Overview) 00:11:00 Plotly & Cufflinks - Interactive & Geographical Plotting Exercises (Solutions) 00:37:00 Capstone Project - Python for Data Analysis & Visualization Project 1 - Oil vs Banks Stock Price during recession (Overview) 00:15:00 Project 1 - Oil vs Banks Stock Price during recession (Solutions Part 1) 00:18:00 Project 1 - Oil vs Banks Stock Price during recession (Solutions Part 2) 00:18:00 Project 1 - Oil vs Banks Stock Price during recession (Solutions Part 3) 00:17:00 Project 2 (Optional) - Emergency Calls from Montgomery County, PA (Overview) 00:03:00 Python for Machine Learning (ML) - scikit-learn - Linear Regression Model Introduction to ML - What, Why and Types.. 00:15:00 Theory Lecture on Linear Regression Model, No Free Lunch, Bias Variance Tradeoff 00:15:00 scikit-learn - Linear Regression Model - Hands-on (Part 1) 00:17:00 scikit-learn - Linear Regression Model Hands-on (Part 2) 00:19:00 Good to know! How to save and load your trained Machine Learning Model! 00:01:00 scikit-learn - Linear Regression Model (Insurance Data Project Overview) 00:08:00 scikit-learn - Linear Regression Model (Insurance Data Project Solutions) 00:30:00 Python for Machine Learning - scikit-learn - Logistic Regression Model Theory: Logistic Regression, conf. mat., TP, TN, Accuracy, Specificityetc. 00:10:00 scikit-learn - Logistic Regression Model - Hands-on (Part 1) 00:17:00 scikit-learn - Logistic Regression Model - Hands-on (Part 2) 00:20:00 scikit-learn - Logistic Regression Model - Hands-on (Part 3) 00:11:00 scikit-learn - Logistic Regression Model - Hands-on (Project Overview) 00:05:00 scikit-learn - Logistic Regression Model - Hands-on (Project Solutions) 00:15:00 Python for Machine Learning - scikit-learn - K Nearest Neighbors Theory: K Nearest Neighbors, Curse of dimensionality . 00:08:00 scikit-learn - K Nearest Neighbors - Hands-on 00:25:00 scikt-learn - K Nearest Neighbors (Project Overview) 00:04:00 scikit-learn - K Nearest Neighbors (Project Solutions) 00:14:00 Python for Machine Learning - scikit-learn - Decision Tree and Random Forests Theory: D-Tree & Random Forests, splitting, Entropy, IG, Bootstrap, Bagging. 00:18:00 scikit-learn - Decision Tree and Random Forests - Hands-on (Part 1) 00:19:00 scikit-learn - Decision Tree and Random Forests (Project Overview) 00:05:00 scikit-learn - Decision Tree and Random Forests (Project Solutions) 00:15:00 Python for Machine Learning - scikit-learn -Support Vector Machines (SVMs) Support Vector Machines (SVMs) - (Theory Lecture) 00:07:00 scikit-learn - Support Vector Machines - Hands-on (SVMs) 00:30:00 scikit-learn - Support Vector Machines (Project 1 Overview) 00:07:00 scikit-learn - Support Vector Machines (Project 1 Solutions) 00:20:00 scikit-learn - Support Vector Machines (Optional Project 2 - Overview) 00:02:00 Python for Machine Learning - scikit-learn - K Means Clustering Theory: K Means Clustering, Elbow method .. 00:11:00 scikit-learn - K Means Clustering - Hands-on 00:23:00 scikit-learn - K Means Clustering (Project Overview) 00:07:00 scikit-learn - K Means Clustering (Project Solutions) 00:22:00 Python for Machine Learning - scikit-learn - Principal Component Analysis (PCA) Theory: Principal Component Analysis (PCA) 00:09:00 scikit-learn - Principal Component Analysis (PCA) - Hands-on 00:22:00 scikit-learn - Principal Component Analysis (PCA) - (Project Overview) 00:02:00 scikit-learn - Principal Component Analysis (PCA) - (Project Solutions) 00:17:00 Recommender Systems with Python - (Additional Topic) Theory: Recommender Systems their Types and Importance 00:06:00 Python for Recommender Systems - Hands-on (Part 1) 00:18:00 Python for Recommender Systems - - Hands-on (Part 2) 00:19:00 Python for Natural Language Processing (NLP) - NLTK - (Additional Topic) Natural Language Processing (NLP) - (Theory Lecture) 00:13:00 NLTK - NLP-Challenges, Data Sources, Data Processing .. 00:13:00 NLTK - Feature Engineering and Text Preprocessing in Natural Language Processing 00:19:00 NLTK - NLP - Tokenization, Text Normalization, Vectorization, BoW. 00:19:00 NLTK - BoW, TF-IDF, Machine Learning, Training & Evaluation, Naive Bayes 00:13:00 NLTK - NLP - Pipeline feature to assemble several steps for cross-validation 00:09:00 Resources Resources - Data Science and Visualisation with Machine Learning 00:00:00 Order your QLS Endorsed Certificate Order your QLS Endorsed Certificate 00:00:00

In this course, we will learn about the Google Apps Script to create custom functions within G Suite that will help you increase your productivity. This course contains 100+ coding examples. For this course, you need JavaScript and basic HTML and CSS knowledge, a Google account, and a basic web development understanding.