286 Data Structure courses in Sheffield delivered Online

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Dive into the fascinating world of Python with the Ultimate Python Training for Beginners Course — designed to gently guide you from zero coding knowledge to confident script writing. This course carefully balances clear explanations with step-by-step lessons, ensuring you grasp key concepts without being overwhelmed. Whether you’re curious about coding or aiming to boost your career prospects, Python’s versatility and simplicity make it an excellent choice to begin your programming journey. This training carefully unpacks the essentials of Python programming, including variables, loops, functions, and data structures, all delivered through engaging, easy-to-follow content. Along the way, you’ll explore real coding examples that demonstrate how Python can be used in various fields, from web development to data analysis. By the end, you’ll have a solid foundation in Python syntax and logic, ready to explore more advanced topics or develop your own projects — all at your own pace, in a friendly, supportive learning environment. Learning Outcomes: Gain a comprehensive understanding of the Python programming language. Learn how to write basic Python code, including variables, operators, loops, and functions. Discover how to use Python to perform common programming tasks, such as data analysis, web scraping, and GUI development. Understand more advanced topics such as object-oriented programming and data structures. Learn how to use Python to build real-world projects and applications. The Ultimate Python Training for Beginners course is designed to provide you with the skills and knowledge you need to become a proficient Python programmer. Whether you're a complete novice or a seasoned programmer looking to add Python to your repertoire, this course is perfect for you. Starting with the basics of the language and moving on to more advanced topics, you'll follow a journey from learner to expert, gaining confidence and expertise with each step. You'll learn how to write basic Python code, perform common programming tasks, and build real-world projects and applications using Python. Ultimate Python Training for Beginners Course Curriculum Section 01: Getting Started Section 02: Learners' Spot Section 03: Marathon Journey Section 04: Expert Path 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 who are new to programming and want to learn Python from scratch. Programmers who want to add Python to their repertoire. Data analysts who want to use Python for data analysis and visualization. Web developers who want to use Python for web development and web scraping. Anyone who wants to develop their skills in the software development industry. Career path Junior Python Developer: £20,000 - £35,000 Python Developer: £28,000 - £55,000 Senior Python Developer: £40,000 - £80,000 Python Data Analyst: £30,000 - £60,000 Python Web Developer: £25,000 - £65,000 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.

The course 'Deep Learning & Neural Networks Python - Keras' provides a comprehensive introduction to deep learning using the Keras library in Python. It covers topics ranging from basic neural networks to more advanced concepts, such as convolutional neural networks, image augmentation, and performance improvement techniques for various datasets. Learning Outcomes: Understand the fundamental concepts of deep learning and how it differs from traditional machine learning. Gain proficiency in using Keras, a powerful deep learning library, for building and training neural network models. Develop practical skills in creating and optimizing neural network models for different datasets, including image recognition tasks and regression problems. Why buy this Deep Learning & Neural Networks Python - Keras? Unlimited access to the course for forever Digital Certificate, Transcript, student ID all included in the price Absolutely no hidden fees Directly receive CPD accredited qualifications after course completion Receive one to one assistance on every weekday from professionals Immediately receive the PDF certificate after passing Receive the original copies of your certificate and transcript on the next working day Easily learn the skills and knowledge from the comfort of your home Certification After studying the course materials of the Deep Learning & Neural Networks Python - Keras there will be a written assignment test which you can take either during or at the end of the course. After successfully passing the test you will be able to claim the pdf certificate for £5.99. Original Hard Copy certificates need to be ordered at an additional cost of £9.60. Who is this course for? This Deep Learning & Neural Networks Python - Keras course is ideal for Students Recent graduates Job Seekers Anyone interested in this topic People already working in the relevant fields and want to polish their knowledge and skill. Prerequisites This Deep Learning & Neural Networks Python - Keras does not require you to have any prior qualifications or experience. You can just enrol and start learning.This Deep Learning & Neural Networks Python - Keras 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. Career path As this course comes with multiple courses included as bonus, you will be able to pursue multiple occupations. This Deep Learning & Neural Networks Python - Keras is a great way for you to gain multiple skills from the comfort of your home. Course Curriculum Course Introduction and Table of Contents Course Introduction and Table of Contents 00:11:00 Deep Learning Overview Deep Learning Overview - Theory Session - Part 1 00:06:00 Deep Learning Overview - Theory Session - Part 2 00:07:00 Choosing Between ML or DL for the next AI project - Quick Theory Session Choosing Between ML or DL for the next AI project - Quick Theory Session 00:09:00 Preparing Your Computer Preparing Your Computer - Part 1 00:07:00 Preparing Your Computer - Part 2 00:06:00 Python Basics Python Basics - Assignment 00:09:00 Python Basics - Flow Control 00:09:00 Python Basics - Functions 00:04:00 Python Basics - Data Structures 00:12:00 Theano Library Installation and Sample Program to Test Theano Library Installation and Sample Program to Test 00:11:00 TensorFlow library Installation and Sample Program to Test TensorFlow library Installation and Sample Program to Test 00:09:00 Keras Installation and Switching Theano and TensorFlow Backends Keras Installation and Switching Theano and TensorFlow Backends 00:10:00 Explaining Multi-Layer Perceptron Concepts Explaining Multi-Layer Perceptron Concepts 00:03:00 Explaining Neural Networks Steps and Terminology Explaining Neural Networks Steps and Terminology 00:10:00 First Neural Network with Keras - Understanding Pima Indian Diabetes Dataset First Neural Network with Keras - Understanding Pima Indian Diabetes Dataset 00:07:00 Explaining Training and Evaluation Concepts Explaining Training and Evaluation Concepts 00:11:00 Pima Indian Model - Steps Explained Pima Indian Model - Steps Explained - Part 1 00:09:00 Pima Indian Model - Steps Explained - Part 2 00:07:00 Coding the Pima Indian Model Coding the Pima Indian Model - Part 1 00:11:00 Coding the Pima Indian Model - Part 2 00:09:00 Pima Indian Model - Performance Evaluation Pima Indian Model - Performance Evaluation - Automatic Verification 00:06:00 Pima Indian Model - Performance Evaluation - Manual Verification 00:08:00 Pima Indian Model - Performance Evaluation - k-fold Validation - Keras Pima Indian Model - Performance Evaluation - k-fold Validation - Keras 00:10:00 Pima Indian Model - Performance Evaluation - Hyper Parameters Pima Indian Model - Performance Evaluation - Hyper Parameters 00:12:00 Understanding Iris Flower Multi-Class Dataset Understanding Iris Flower Multi-Class Dataset 00:08:00 Developing the Iris Flower Multi-Class Model Developing the Iris Flower Multi-Class Model - Part 1 00:09:00 Developing the Iris Flower Multi-Class Model - Part 2 00:06:00 Developing the Iris Flower Multi-Class Model - Part 3 00:09:00 Understanding the Sonar Returns Dataset Understanding the Sonar Returns Dataset 00:07:00 Developing the Sonar Returns Model Developing the Sonar Returns Model 00:10:00 Sonar Performance Improvement - Data Preparation - Standardization Sonar Performance Improvement - Data Preparation - Standardization 00:15:00 Sonar Performance Improvement - Layer Tuning for Smaller Network Sonar Performance Improvement - Layer Tuning for Smaller Network 00:07:00 Sonar Performance Improvement - Layer Tuning for Larger Network Sonar Performance Improvement - Layer Tuning for Larger Network 00:06:00 Understanding the Boston Housing Regression Dataset Understanding the Boston Housing Regression Dataset 00:07:00 Developing the Boston Housing Baseline Model Developing the Boston Housing Baseline Model 00:08:00 Boston Performance Improvement by Standardization Boston Performance Improvement by Standardization 00:07:00 Boston Performance Improvement by Deeper Network Tuning Boston Performance Improvement by Deeper Network Tuning 00:05:00 Boston Performance Improvement by Wider Network Tuning Boston Performance Improvement by Wider Network Tuning 00:04:00 Save & Load the Trained Model as JSON File (Pima Indian Dataset) Save & Load the Trained Model as JSON File (Pima Indian Dataset) - Part 1 00:09:00 Save & Load the Trained Model as JSON File (Pima Indian Dataset) - Part 2 00:08:00 Save and Load Model as YAML File - Pima Indian Dataset Save and Load Model as YAML File - Pima Indian Dataset 00:05:00 Load and Predict using the Pima Indian Diabetes Model Load and Predict using the Pima Indian Diabetes Model 00:09:00 Load and Predict using the Iris Flower Multi-Class Model Load and Predict using the Iris Flower Multi-Class Model 00:08:00 Load and Predict using the Sonar Returns Model Load and Predict using the Sonar Returns Model 00:10:00 Load and Predict using the Boston Housing Regression Model Load and Predict using the Boston Housing Regression Model 00:08:00 An Introduction to Checkpointing An Introduction to Checkpointing 00:06:00 Checkpoint Neural Network Model Improvements Checkpoint Neural Network Model Improvements 00:10:00 Checkpoint Neural Network Best Model Checkpoint Neural Network Best Model 00:04:00 Loading the Saved Checkpoint Loading the Saved Checkpoint 00:05:00 Plotting Model Behavior History Plotting Model Behavior History - Introduction 00:06:00 Plotting Model Behavior History - Coding 00:08:00 Dropout Regularization - Visible Layer Dropout Regularization - Visible Layer - Part 1 00:11:00 Dropout Regularization - Visible Layer - Part 2 00:06:00 Dropout Regularization - Hidden Layer Dropout Regularization - Hidden Layer 00:06:00 Learning Rate Schedule using Ionosphere Dataset - Intro Learning Rate Schedule using Ionosphere Dataset 00:06:00 Time Based Learning Rate Schedule Time Based Learning Rate Schedule - Part 1 00:07:00 Time Based Learning Rate Schedule - Part 2 00:12:00 Drop Based Learning Rate Schedule Drop Based Learning Rate Schedule - Part 1 00:07:00 Drop Based Learning Rate Schedule - Part 2 00:08:00 Convolutional Neural Networks - Introduction Convolutional Neural Networks - Part 1 00:11:00 Convolutional Neural Networks - Part 2 00:06:00 MNIST Handwritten Digit Recognition Dataset Introduction to MNIST Handwritten Digit Recognition Dataset 00:06:00 Downloading and Testing MNIST Handwritten Digit Recognition Dataset 00:10:00 MNIST Multi-Layer Perceptron Model Development MNIST Multi-Layer Perceptron Model Development - Part 1 00:11:00 MNIST Multi-Layer Perceptron Model Development - Part 2 00:06:00 Convolutional Neural Network Model using MNIST Convolutional Neural Network Model using MNIST - Part 1 00:13:00 Convolutional Neural Network Model using MNIST - Part 2 00:12:00 Large CNN using MNIST Large CNN using MNIST 00:09:00 Load and Predict using the MNIST CNN Model Load and Predict using the MNIST CNN Model 00:14:00 Introduction to Image Augmentation using Keras Introduction to Image Augmentation using Keras 00:11:00 Augmentation using Sample Wise Standardization Augmentation using Sample Wise Standardization 00:10:00 Augmentation using Feature Wise Standardization & ZCA Whitening Augmentation using Feature Wise Standardization & ZCA Whitening 00:04:00 Augmentation using Rotation and Flipping Augmentation using Rotation and Flipping 00:04:00 Saving Augmentation Saving Augmentation 00:05:00 CIFAR-10 Object Recognition Dataset - Understanding and Loading CIFAR-10 Object Recognition Dataset - Understanding and Loading 00:12:00 Simple CNN using CIFAR-10 Dataset Simple CNN using CIFAR-10 Dataset - Part 1 00:09:00 Simple CNN using CIFAR-10 Dataset - Part 2 00:06:00 Simple CNN using CIFAR-10 Dataset - Part 3 00:08:00 Train and Save CIFAR-10 Model Train and Save CIFAR-10 Model 00:08:00 Load and Predict using CIFAR-10 CNN Model Load and Predict using CIFAR-10 CNN Model 00:16:00 RECOMENDED READINGS Recomended Readings 00:00:00

Delve into the world of Python programming paired seamlessly with MySQL database management in this thoughtfully designed course. Whether you’re a complete beginner or someone keen to refresh your coding foundations, this course guides you through the essentials of Python—from understanding syntax and control structures to working with functions and modules. Alongside, you will become acquainted with MySQL, mastering the basics of database creation, queries, and data manipulation, ensuring a smooth integration between programming logic and data storage. This online course offers a clear and engaging pathway to developing your coding knowledge and database skills without the need for physical attendance. It balances technical depth with accessible explanations, making complex concepts approachable and even enjoyable. Ideal for individuals aiming to boost their programming portfolio or enhance their career prospects in software development and data handling, this course is designed to fit your schedule and learning pace with clarity and professionalism. Expert Support Dedicated tutor support and 24/7 customer support are available to all students with this premium quality course. Key Benefits Learning materials of the Design course contain engaging voiceover and visual elements for your comfort. Get 24/7 access to all content for a full year. Each of our students gets full tutor support on weekdays (Monday to Friday) Course Curriculum: Here is a curriculum breakdown of the Python Programming from Scratch with My SQL Database course: Section 01: Getting Started Section 02: HTML Section 03: HTML Basic Section 04: HTML Intermediate Section 05: HTML Advanced Section 06:Python Introduction Section 07: Python Basic Section 08: Python Strings Section 09: Python Operators Section 10: Python Data Structures And much more... Course Assessment To simplify the procedure of evaluation and accreditation for learners, we provide an automated assessment system. Upon completion of an online module, you will immediately be given access to a specifically crafted MCQ test. The results will be evaluated instantly, and the score will be displayed for your perusal. For each test, the pass mark will be set to 60%. When all tests have been successfully passed, you will be able to order a certificate endorsed by the Quality Licence Scheme. 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 £9 for PDF Certificate and £15 for the Hardcopy Certificate within the UK ( An additional £10 postal charge will be applicable for international delivery). Who is this course for? This Python Programming from Scratch with My SQL Database course is designed to enhance your expertise and boost your CV. Learn key skills and gain a certificate of achievement to prove your newly-acquired knowledge. Requirements This Python Programming from Scratch with My SQL Database course is open to all, with no formal entry requirements. Career path Upon successful completion of the Python Programming from Scratch with My SQL Database Course, learners will be equipped with many indispensable skills and have the opportunity to grab.

If data is the new oil, then coding is your refinery. Whether you're exploring the depths of machine learning or navigating databases with ease, this course sharpens your edge in the competitive world of data science. With a sharp focus on three industry-leading languages—Python, JavaScript, and Microsoft SQL—you’ll build the solid foundations needed to analyse, automate, and query data confidently. From writing clean scripts to crafting smart SQL queries, you’ll develop the mindset to speak fluently in the language of data. Delivered entirely online, the course keeps your learning agile and accessible. Python lays the groundwork for analysis and automation, JavaScript helps in data visualisation and interaction, and SQL ensures you can command databases without blinking. It's not about ticking boxes—it’s about building fluency in what matters. Whether you're upskilling or aiming for a sharper digital edge, this course speaks directly to future-focused learners ready to code with purpose. Expert Support Dedicated tutor support and 24/7 customer support are available to all students with this premium quality course. Key Benefits Learning materials of the Design course contain engaging voiceover and visual elements for your comfort. Get 24/7 access to all content for a full year. Each of our students gets full tutor support on weekdays (Monday to Friday) Course Curriculum: JavaScript Section 01: Introduction Section 02: Basics Section 03: Operators Section 04: Conditional Statements Section 05: Control Flow Statements Section 06: Functions Section 07: Error Handling Section 08: Client-Side Validations Python Section 09: Introduction Section 10: Basic Section 11: Strings Section 12: Operators Section 13: Data Structures Section 14: Conditional Statements Section 15: control flow statements Section 16: core games Section 17: functions Section 18: args, KW args for Data Science Section 19: project Section 20: Object oriented programming [OOPs] Section 21: Methods Section 22: Class and Objects Section 23: Inheritance and Polymorphism Section 24: Encapsulation and Abstraction Section 25: OOPs Games Section 26: Modules and Packages Section 27: Error Handling Microsoft SQL Section 28: Introduction Section 29: Statements Section 30: Filtering Data Section 31: Functions Section 32: Joins Section 33: Advanced commands Section 34: Structure and Keys Section 35: Queries Section 36: Structure queries Section 37: Constraints Section 38: Backup and Restore Course Assessment To simplify the procedure of evaluation and accreditation for learners, we provide an automated assessment system. Upon completion of an online module, you will immediately be given access to a specifically crafted MCQ test. The results will be evaluated instantly, and the score will be displayed for your perusal. For each test, the pass mark will be set to 60%. When all tests have been successfully passed, you will be able to order a certificate endorsed by the Quality Licence Scheme. 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 £9 for PDF Certificate and £15 for the Hardcopy Certificate within the UK ( An additional £10 postal charge will be applicable for international delivery). Who is this course for? This Learn Python, JavaScript, and Microsoft SQL for Data science course is designed to enhance your expertise and boost your CV. Learn key skills and gain a certificate of achievement to prove your newly-acquired knowledge. Requirements This Learn Python, JavaScript, and Microsoft SQL for Data science course is open to all, with no formal entry requirements. Career path Upon successful completion of the Learn Python, JavaScript, and Microsoft SQL for Data science Course, learners will be equipped with many indispensable skills and have the opportunity to grab.

Become a Python developer and build a rewarding career in tech. Python is one of the most popular and in-demand programming languages in the world. Python is used by companies of all sizes, from startups to Fortune 500 companies, to develop a wide range of applications, including web applications, data science tools, and machine learning algorithms. The demand for Python developers is rising rapidly in the UK, with job postings for Python developers increasing by 22% in the past year. The average salary for a Python developer in the UK is £65,000, making it one of the highest-paid programming languages. Our Python Programming - Beginner to Advanced course will teach you everything you need to know to become a Python developer. You will learn the fundamentals of Python programming, as well as more advanced topics such as object-oriented programming, data structures, and algorithms. You will also learn how to use popular Python libraries and frameworks, such as Django and NumPy. Why would you choose the Python Programming course from Compliance Central: Lifetime access to Python Programming course materials Full tutor support is available from Monday to Friday with the Python Programming course Learn Python Programming skills at your own pace from the comfort of your home Gain a complete understanding of Python Programming course Accessible, informative Python Programming learning modules designed by experts Get 24/7 help or advice from our email and live chat teams with the Python Programming Study Python Programming in your own time through your computer, tablet or mobile device A 100% learning satisfaction guarantee with your Python Programming course Python Programming Curriculum Breakdown of the Python Programming Course Section 01: Introduction & Getting Started Section 02: Downloading and Installing Python Editor Section 03: Getting Started Section 04: Variables and Basic Data Types in Python Section 05: Comments Section 06: Input Section 07: Exercise - Build a Program to Say Hello Section 08: Exercise - Build a Simple Calculator Section 09: Conditional Statements Section 10: Loops - For Loop Section 11: Loops - While Loop Section 12: Exercise - Building a Username Password App. Python Programming - Beginner to Advanced Course Learning Outcomes: Familiarise with Python's core principles and setup. Understand fundamental data types and variable operations in Python. Recognise the significance and application of comments in Python. Master the art of obtaining and processing user input in Python. Employ conditional structures with proficiency. Navigate confidently within both "For" and "While" loops. Conceptualise and draft rudimentary Python applications. Certificate of Achievement After successfully completing this Python course, you can get a digital and a hardcopy certificate for free. The delivery charge of the hardcopy certificate inside the UK is £3.99 and international students need to pay £9.99 to get their hardcopy certificate. CPD 10 CPD hours / points Accredited by CPD Quality Standards Who is this course for? The Python Programming course helps aspiring professionals who want to obtain the knowledge and familiarise themselves with the skillsets to pursue a career in Python Programming. It is also great for professionals who are already working in Python Programming and want to get promoted at work. Requirements To enrol in this Python Programming course, all you need is a basic understanding of the English Language and an internet connection. Career path The Python Programming course will enhance your knowledge and improve your confidence in exploring opportunities in various sectors related to Python Programming. Python Developer: £35,000 to £70,000 per year Data Analyst (Python): £30,000 to £55,000 per year Software Engineer (Python): £40,000 to £75,000 per year Machine Learning Engineer: £45,000 to £80,000 per year Certificates CPD Accredited PDF Certificate Digital certificate - Included CPD Accredited PDF Certificate CPD Accredited Hard Copy Certificate Hard copy certificate - £10.79 CPD Accredited Hard Copy Certificate Delivery Charge: Inside the UK: Free Outside of the UK: £9.99 each

***Want to Unlock the Secrets of Data? Become a Database Mastermind!*** The world runs on data, and Database Administrators (DBAs) are the heroes behind the scenes ensuring its smooth operation. Database administrators in the UK are in high demand, with an average salary of £41,501 per year. The job market is expected to grow by 9% in the next few years, so now is a great time to start a career as a database administrator. As a database administrator, you will be responsible for the design, implementation, and maintenance of databases. You will also be responsible for ensuring the security and integrity of the data. If you are interested in a challenging and rewarding career in technology, then database administration is a great option for you. Our Database Administrator course starts with the basics of Database Administrator and gradually progresses towards advanced topics. Therefore, each lesson of this Database Administrator course is intuitive and easy to understand. Learning Outcomes By the end of this Database Administrator course, you'll be able to: Install and configure MySQL Server and MySQL Workbench. Create, manage, and manipulate databases and tables using SQL. Insert, update, and delete data efficiently. Design and implement database relationships to ensure data integrity. Utilize aggregate functions to summarize and analyze data. Reverse engineer existing databases and forward engineer data models. Why would you choose the Database Administrator course from Compliance Central: Lifetime access to Database Administrator course materials Full tutor support is available from Monday to Friday with the Database Administrator course Learn Database Administrator skills at your own pace from the comfort of your home Gain a complete understanding of Database Administrator course Accessible, informative Database Administrator learning modules designed by experts Get 24/7 help or advice from our email and live chat teams with the Database Administrator Study Database Administrator in your own time through your computer, tablet or mobile device A 100% learning satisfaction guarantee with your Database Administrator Course Database Administrator Curriculum Breakdown of the Database Administrator Course Unit 01: Introduction Gain foundational knowledge of MySQL Server and databases, including installation and initial setup. Module 01: Introduction to MySQL Server and Databases Module 02: Download and Install MySQL Server and MySQL Workbench Unit 02: Manipulating Tables and Data - CRUD Operations Learn to manage databases through creating, reading, updating, and deleting (CRUD) data in SQL and MySQL Workbench. Module 01: Connect and Create a Database Module 02: Drop or Remove Database Module 03: Create an SQL Database Table Module 04: Insert Data into the Table with SQL Script Module 05: Insert Data into the Table with Workbench Module 06: Select Data from the Table with SQL Script Module 07: Select Data with Filters Module 08: Update Data in the Table Module 09: Delete Data from the Table Module 10: Reverse Engineer Database into Model Module 11: Forward Engineer Data Model into Database Unit 03: Relationships and Foreign Keys Understand and implement relationships, foreign keys, and normalization in databases, enhancing data integrity and querying capabilities.ys Module 01: What are Relationships, Foreign Keys and Normalization? Module 02: Create Relationships with Data Modeling Module 03: Create Relationships with Workbench Table Design Tool Module 04: Insert Records in Related Tables Module 05: Run Queries on Related Tables (Inner Joins) Module 06: Left, Right and Cross-Joins Unit 04: Aggregate Functions Explore aggregate functions to perform calculations on data sets, including grouping, averaging, counting, and summing data. Module 01: Grouping Data using SQL GROUP BY Clause Module 02: SQL AVG Aggregate Function Module 03: SQL COUNT Aggregate Function Module 04: SQL MIN & MAX Aggregate Functions Module 05: SQL SUM Aggregate Function Module 06: Splitting Groups using HAVING Clause CPD 10 CPD hours / points Accredited by CPD Quality Standards Who is this course for? This Database Administrator course is ideal for: Individuals with an interest in data management and database systems. IT professionals seeking to expand their skillset and transition into a Database Administrator role. Business analysts who want to gain a deeper understanding of data structures and manipulation techniques. Anyone passionate about building and maintaining robust and efficient databases. Those looking to enhance their career prospects in the ever-growing field of data. Requirements To enrol in this Database Administrator course, all you need is a basic understanding of the English Language and an internet connection. Career path A successful career as a Database Administrator can open doors to exciting opportunities. Here are some potential career paths to consider: Database Administrator Database Analyst Database Architect Data Warehouse Specialist Business Intelligence Analyst Data Scientist (with further specialization) Database Security Specialist Certificates CPD Accredited PDF Certificate Digital certificate - Included CPD Accredited PDF Certificate CPD Accredited Hard Copy Certificate Hard copy certificate - £10.79 CPD Accredited Hard Copy Certificate Delivery Charge: Inside the UK: Free Outside of the UK: £9.99 each

Ever stared at a website and thought, “How did they build that?” This course is your no-nonsense route to understanding the hows, whats and whys of web development—without needing a computer science degree or a background in tech. Whether you’re just curious or keen to reshape your digital future, we’ll walk you through HTML, CSS, JavaScript, and more—step by step, with clarity, purpose and the occasional chuckle where appropriate. Designed for complete beginners, this online course delivers the technical foundations of building websites from the ground up—clearly and without any fluff. By the end, you’ll understand how web pages come to life, how to structure content, and how styling and scripts bring everything together. No over-the-top jargon, no pressure—just a solid, well-paced approach to the world behind the screen. Expert Support Dedicated tutor support and 24/7 customer support are available to all students with this premium quality course. Key Benefits Learning materials of the Design course contain engaging voiceover and visual elements for your comfort. Get 24/7 access to all content for a full year. Each of our students gets full tutor support on weekdays (Monday to Friday) Course Curriculum: Here is a curriculum breakdown of the Learn Web Development from Scratch course: Section 01: Introduction Introduction How to Get Course requirements Getting Started on Windows, Linux or Mac How to ask Great Questions FAQ's Section 02: HTML Introduction HTML Choosing Code Editor Installing Code Editor (Sublime Text) Overview of a Webpage Structure of a Full HTML Webpage First Hello World! Webpage Section 03: HTML Basic Heading tags Paragraph Formatting Text List Items Unordered List Items Ordered Classes IDs Comments Section 04: HTML Intermediate Images Forms Marquee Text area Tables Links Navbar - Menu HTML Entities Div tag Google Maps Section 05: HTML Advanced HTML Audio HTML Video Canvas Iframes Input Types Input Attributes Registration Form Contact Us Form Coding Exercise Solution for Coding Exercise Section 06: JavaScript Introduction What is JavaScript Hello World Program Getting Output Internal JavaScript External JavaScript Inline JavaScript Async and defer Section 07: JavaScript Basics Variables Data Types Numbers Strings String Formatting Section 08: JavaScript Operators Arithmetic operators Assignment operators Comparison operators Logical operators Section 09: JavaScript Conditional Statements If-else statement If-else-if statement Section 10: JavaScript Control Flow Statements While loop Do-while loop For loop Coding Exercise Solution for Coding Exercise Section 11: JavaScript Functions Creating a Function Function Call() Function with parameters Section 12: JavaScript Error Handling Try-catch Try-catch-finally Section 13: JavaScript Client-Side Validations On Submit Validation Input Numeric Validation Section 14: Python Introduction Introduction to Python Python vs Other Languages Why It's Popular Command Line Basics Python Installation (Step By Step) PyCharm IDE Installation Getting Start PyCharm IDE First Python Hello World Program Section 15: Python Basic Variables Data Types Type Casting User Inputs Comments Section 16: Python Strings Strings String Indexing String Slicing String Built-in Functions Formatting String (Dynamic Data) Section 17: Python Operators Arithmetic Operators Assignment Operators Comparison Operators Logical Operators AND Operator OR Operator NOT Operator Booleans Section 18: Python Data Structures Arrays in Earlier Lists Add List Items Remove List Items Sort Lists Join Lists Tuples Update tuples Join tuples Dictionaries Add Dictionary Items Remove Dictionary Items Nested Dictionaries Sets Add Set Items Remove Set Items Join Set Items Section 19: Python Conditional Statements If Statement If-else Statement If-elif-else Statement If Statement Coding Exercise Section 20: Python Control Flow Statements Flow Charts While Loops Statement For Loops Statement The range() Function Nested Loops 2D List using Nested Loop Section 21: Python Core Games Guessing Game Car Game Section 22: Python Functions Creating a Function Calling a Function Function with Arguments Section 23: Python args, KW args for Data Science args, Arbitary Arguments kwargs, Arbitary Keyword Arguments Section 24: Python Project Project Overview ATM Realtime Project Course Assessment To simplify the procedure of evaluation and accreditation for learners, we provide an automated assessment system. Upon completion of an online module, you will immediately be given access to a specifically crafted MCQ test. The results will be evaluated instantly, and the score will be displayed for your perusal. For each test, the pass mark will be set to 60%. When all tests have been successfully passed, you will be able to order a certificate endorsed by the Quality Licence Scheme. 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 £9 for PDF Certificate and £15 for the Hardcopy Certificate within the UK ( An additional £10 postal charge will be applicable for international delivery). Who is this course for? This Learn Web Development from Scratch course is designed to enhance your expertise and boost your CV. Learn key skills and gain a certificate of achievement to prove your newly-acquired knowledge. Requirements This Learn Web Development from Scratch course is open to all, with no formal entry requirements. Career path Upon successful completion of the Learn Web Development from Scratch Course, learners will be equipped with many indispensable skills and have the opportunity to grab.

Overview This Deep Learning & Neural Networks Python - Keras: For Dummies course will unlock your full potential and will show you how to excel in a career in Deep Learning & Neural Networks Python - Keras: For Dummies. So upskill now and reach your full potential. Everything you need to get started in Deep Learning & Neural Networks Python - Keras: For Dummies is available in this course. Learning and progressing are the hallmarks of personal development. This Deep Learning & Neural Networks Python - Keras: For Dummies will quickly teach you the must-have skills needed to start in the relevant industry. In This Deep Learning & Neural Networks Python - Keras: For Dummies Course, You Will: Learn strategies to boost your workplace efficiency. Hone your Deep Learning & Neural Networks Python - Keras: For Dummies skills to help you advance your career. 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Course Curriculum Course Introduction and Table of Contents Course Introduction and Table of Contents 00:11:00 Deep Learning Overview Deep Learning Overview - Theory Session - Part 1 00:06:00 Deep Learning Overview - Theory Session - Part 2 00:07:00 Choosing Between ML or DL for the next AI project - Quick Theory Session Choosing Between ML or DL for the next AI project - Quick Theory Session 00:09:00 Preparing Your Computer Preparing Your Computer - Part 1 00:07:00 Preparing Your Computer - Part 2 00:06:00 Python Basics Python Basics - Assignment 00:09:00 Python Basics - Flow Control 00:09:00 Python Basics - Functions 00:04:00 Python Basics - Data Structures 00:12:00 Theano Library Installation and Sample Program to Test Theano Library Installation and Sample Program to Test 00:11:00 TensorFlow library Installation and Sample Program to Test TensorFlow library Installation and Sample Program to Test 00:09:00 Keras Installation and Switching Theano and TensorFlow Backends Keras Installation and Switching Theano and TensorFlow Backends 00:10:00 Explaining Multi-Layer Perceptron Concepts Explaining Multi-Layer Perceptron Concepts 00:03:00 Explaining Neural Networks Steps and Terminology Explaining Neural Networks Steps and Terminology 00:10:00 First Neural Network with Keras - Understanding Pima Indian Diabetes Dataset First Neural Network with Keras - Understanding Pima Indian Diabetes Dataset 00:07:00 Explaining Training and Evaluation Concepts Explaining Training and Evaluation Concepts 00:11:00 Pima Indian Model - Steps Explained Pima Indian Model - Steps Explained - Part 1 00:09:00 Pima Indian Model - Steps Explained - Part 2 00:07:00 Coding the Pima Indian Model Coding the Pima Indian Model - Part 1 00:11:00 Coding the Pima Indian Model - Part 2 00:09:00 Pima Indian Model - Performance Evaluation Pima Indian Model - Performance Evaluation - Automatic Verification 00:06:00 Pima Indian Model - Performance Evaluation - Manual Verification 00:08:00 Pima Indian Model - Performance Evaluation - k-fold Validation - Keras Pima Indian Model - Performance Evaluation - k-fold Validation - Keras 00:10:00 Pima Indian Model - Performance Evaluation - Hyper Parameters Pima Indian Model - Performance Evaluation - Hyper Parameters 00:12:00 Understanding Iris Flower Multi-Class Dataset Understanding Iris Flower Multi-Class Dataset 00:08:00 Developing the Iris Flower Multi-Class Model Developing the Iris Flower Multi-Class Model - Part 1 00:09:00 Developing the Iris Flower Multi-Class Model - Part 2 00:06:00 Developing the Iris Flower Multi-Class Model - Part 3 00:09:00 Understanding the Sonar Returns Dataset Understanding the Sonar Returns Dataset 00:07:00 Developing the Sonar Returns Model Developing the Sonar Returns Model 00:10:00 Sonar Performance Improvement - Data Preparation - Standardization Sonar Performance Improvement - Data Preparation - Standardization 00:15:00 Sonar Performance Improvement - Layer Tuning for Smaller Network Sonar Performance Improvement - Layer Tuning for Smaller Network 00:07:00 Sonar Performance Improvement - Layer Tuning for Larger Network Sonar Performance Improvement - Layer Tuning for Larger Network 00:06:00 Understanding the Boston Housing Regression Dataset Understanding the Boston Housing Regression Dataset 00:07:00 Developing the Boston Housing Baseline Model Developing the Boston Housing Baseline Model 00:08:00 Boston Performance Improvement by Standardization Boston Performance Improvement by Standardization 00:07:00 Boston Performance Improvement by Deeper Network Tuning Boston Performance Improvement by Deeper Network Tuning 00:05:00 Boston Performance Improvement by Wider Network Tuning Boston Performance Improvement by Wider Network Tuning 00:04:00 Save & Load the Trained Model as JSON File (Pima Indian Dataset) Save & Load the Trained Model as JSON File (Pima Indian Dataset) - Part 1 00:09:00 Save & Load the Trained Model as JSON File (Pima Indian Dataset) - Part 2 00:08:00 Save and Load Model as YAML File - Pima Indian Dataset Save and Load Model as YAML File - Pima Indian Dataset 00:05:00 Load and Predict using the Pima Indian Diabetes Model Load and Predict using the Pima Indian Diabetes Model 00:09:00 Load and Predict using the Iris Flower Multi-Class Model Load and Predict using the Iris Flower Multi-Class Model 00:08:00 Load and Predict using the Sonar Returns Model Load and Predict using the Sonar Returns Model 00:10:00 Load and Predict using the Boston Housing Regression Model Load and Predict using the Boston Housing Regression Model 00:08:00 An Introduction to Checkpointing An Introduction to Checkpointing 00:06:00 Checkpoint Neural Network Model Improvements Checkpoint Neural Network Model Improvements 00:10:00 Checkpoint Neural Network Best Model Checkpoint Neural Network Best Model 00:04:00 Loading the Saved Checkpoint Loading the Saved Checkpoint 00:05:00 Plotting Model Behavior History Plotting Model Behavior History - Introduction 00:06:00 Plotting Model Behavior History - Coding 00:08:00 Dropout Regularization - Visible Layer Dropout Regularization - Visible Layer - Part 1 00:11:00 Dropout Regularization - Visible Layer - Part 2 00:06:00 Dropout Regularization - Hidden Layer Dropout Regularization - Hidden Layer 00:06:00 Learning Rate Schedule using Ionosphere Dataset - Intro Learning Rate Schedule using Ionosphere Dataset 00:06:00 Time Based Learning Rate Schedule Time Based Learning Rate Schedule - Part 1 00:07:00 Time Based Learning Rate Schedule - Part 2 00:12:00 Drop Based Learning Rate Schedule Drop Based Learning Rate Schedule - Part 1 00:07:00 Drop Based Learning Rate Schedule - Part 2 00:08:00 Convolutional Neural Networks - Introduction Convolutional Neural Networks - Part 1 00:11:00 Convolutional Neural Networks - Part 2 00:06:00 MNIST Handwritten Digit Recognition Dataset Introduction to MNIST Handwritten Digit Recognition Dataset 00:06:00 Downloading and Testing MNIST Handwritten Digit Recognition Dataset 00:10:00 MNIST Multi-Layer Perceptron Model Development MNIST Multi-Layer Perceptron Model Development - Part 1 00:11:00 MNIST Multi-Layer Perceptron Model Development - Part 2 00:06:00 Convolutional Neural Network Model using MNIST Convolutional Neural Network Model using MNIST - Part 1 00:13:00 Convolutional Neural Network Model using MNIST - Part 2 00:12:00 Large CNN using MNIST Large CNN using MNIST 00:09:00 Load and Predict using the MNIST CNN Model Load and Predict using the MNIST CNN Model 00:14:00 Introduction to Image Augmentation using Keras Introduction to Image Augmentation using Keras 00:11:00 Augmentation using Sample Wise Standardization Augmentation using Sample Wise Standardization 00:10:00 Augmentation using Feature Wise Standardization & ZCA Whitening Augmentation using Feature Wise Standardization & ZCA Whitening 00:04:00 Augmentation using Rotation and Flipping Augmentation using Rotation and Flipping 00:04:00 Saving Augmentation Saving Augmentation 00:05:00 CIFAR-10 Object Recognition Dataset - Understanding and Loading CIFAR-10 Object Recognition Dataset - Understanding and Loading 00:12:00 Simple CNN using CIFAR-10 Dataset Simple CNN using CIFAR-10 Dataset - Part 1 00:09:00 Simple CNN using CIFAR-10 Dataset - Part 2 00:06:00 Simple CNN using CIFAR-10 Dataset - Part 3 00:08:00 Train and Save CIFAR-10 Model Train and Save CIFAR-10 Model 00:08:00 Load and Predict using CIFAR-10 CNN Model Load and Predict using CIFAR-10 CNN Model 00:16:00 RECOMENDED READINGS Recomended Readings 00:00:00

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