2261 Software Development courses in Birmingham delivered On Demand

Developed and delivered by industry experts, the course materials of this distance learning course will help you hone your game testing abilities. You will learn the procedures of bug testing, logging errors, the general day-to-day operations of working in quality assurance as well as hints and tips for your job search, interviews and putting together an enticing CV. By the end of the course you will be well poised to begin a career in game testing, with an expert diploma attesting to your lesson. Why choose this course Earn an e-certificate upon successful completion. Accessible, informative modules taught by expert instructors Study in your own time, at your own pace, through your computer tablet or mobile device Benefit from instant feedback through mock exams and multiple-choice assessments Get 24/7 help or advice from our email and live chat teams Full Tutor Support on Weekdays Course Design The course is delivered through our online learning platform, accessible through any internet-connected device. There are no formal deadlines or teaching schedules, meaning you are free to study the course at your own pace. You are taught through a combination of Video lessons Online study materials Mock exams Multiple-choice assessment 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 To successfully complete the course, students will have to take an automated multiple-choice exam. This exam will be online and you will need to score 60% or above to pass the course. After successfully passing the exam, you will be able to apply for Quality Licence Scheme endorsed certificate of achievement. To verify your enhanced skills in the subject, we recommend that you also complete the assignment questions. These can be completed at any time which is convenient for yourself and will be assessed by our in-house specialised tutors. Full feedback will then be given on your current performance, along with any further advice or support. Who is this course for? Game Testing is suitable for anyone who want to gain extensive knowledge, potential experience and expert skills in the related field. This is a great opportunity for all student from any academic backgrounds to learn more on this subject.

Master React and Redux with our comprehensive App Development Training course. Learn to build dynamic web applications, manage state, and integrate with backend services like Firebase. Ideal for aspiring UI/UX developers and frontend developers. Enroll now to start your journey in app development!

In this course, you will learn full-stack web development with React JS for the frontend and Python Django for the backend. You will learn and explore various databases such as Microsoft SQL Server, MySQL, MongoDB, PostgreSQL, and SQLite.

Explore the Whistleblowing Online Certification Course, designed to empower you with the knowledge and skills to effectively report misconduct and ensure organizational integrity.

Are you looking to enhance your Systems Engineering skills? If yes, then you have come to the right place. Our comprehensive course on Systems Engineering will assist you in producing the best possible outcome by mastering the Systems Engineering skills. The Systems Engineering course is for those who want to be successful. In the Systems Engineering course, you will learn the essential knowledge needed to become well versed in Systems Engineering. Our Systems Engineering course starts with the basics of Systems Engineering and gradually progresses towards advanced topics. Therefore, each lesson of this Systems Engineering course is intuitive and easy to understand. Systems Engineering Curriculum Breakdown of the Systems Engineering Course Course Outline: Software Hardware Security Networking Basic IT Literacy Why would you choose the Systems Engineering course from Compliance Central: Lifetime access to Systems Engineering course materials Full tutor support is available from Monday to Friday with the Systems Engineering course Learn Systems Engineering skills at your own pace from the comfort of your home Gain a complete understanding of Systems Engineering course Accessible, informative Systems Engineering learning modules designed by experts Get 24/7 help or advice from our email and live chat teams with the Systems Engineering Study Systems Engineering in your own time through your computer, tablet or mobile device. A 100% learning satisfaction guarantee with your Systems Engineering Course CPD 35 CPD hours / points Accredited by CPD Quality Standards Who is this course for? The Systems Engineering course helps aspiring professionals who want to obtain the knowledge and familiarise themselves with the skillsets to pursue a career in Systems Engineering. It is also great for professionals who are already working in Systems Engineering and want to get promoted at work. Requirements To enrol in this Systems Engineering course, all you need is a basic understanding of the English Language and an internet connection. Career path Systems Engineer: £40,000 to £70,000 per year Project Manager (Systems Engineering): £45,000 to £80,000 per year Systems Analyst: £35,000 to £60,000 per year Systems Integration Engineer: £40,000 to £70,000 per year Technical Consultant (Systems Engineering): £50,000 to £90,000 per year Systems Architect: £55,000 to £100,000 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

This course begins with a comprehensive introduction to RFID technology, focusing on both low and high-frequency cards. You'll explore the Proxmark3 RDV4 device, a powerful RFID testing tool, learning its installation and implementation to understand how RFID systems can be ethically analysed and tested.

Get ready for an exceptional online learning experience with the Coding (C++, Python, JavaScript, Networking & IT) bundle! This carefully curated collection of 20 premium courses is designed to cater to a variety of interests and disciplines. Dive into a sea of knowledge and skills, tailoring your learning journey to suit your unique aspirations. The Coding, C++ & Python package is dynamic, blending the expertise of industry professionals with the flexibility of digital learning. It offers the perfect balance of foundational understanding and advanced insights. Whether you're looking to break into a new field or deepen your existing knowledge, the Coding, C++ & Python package has something for everyone. As part of the Coding, C++ & Python, you will receive complimentary PDF certificates for all courses in this bundle at no extra cost. Equip yourself with the Coding (C++, Python, JavaScript, Networking & IT) bundle to confidently navigate your career path or personal development journey. Enrol today and start your career growth! This Bundle Comprises the Following Coding (C++, Python, JavaScript, Networking & IT) CPD-accredited courses: Course 01: Introduction to Coding With HTML, CSS, & Javascript Course 02: C++ Development: The Complete Coding Guide Course 03: C# Programming - Beginner to Advanced Course 04: Python Programming: Beginner To Expert Course 05: The Complete MySQL Server from Scratch: Bootcamp Course 06: Kotlin Programming: Android Coding Bible Course 07: Learn Web Development from Scratch Course 08: The Complete Front-End Web Development Course! Course 09: Secure Programming of Web Applications Course 10: JavaScript Project - Game Development with JS Course 11: Bash Scripting, Linux and Shell Programming Course 12: Advanced Diploma in PHP Web Development with MySQL, GitHub & Heroku Course 13: Data Analysis Course 14: R Programming for Data Science Course 15: Learn Ethical Hacking From A-Z: Beginner To Expert Course 16: Cyber Security Awareness Training Course 17: Cloud Computing / CompTIA Cloud+ (CV0-002) Course 18: CompTIA A+ (220-1001) Course 19: Computer Networks Security from Scratch to Advanced Course 20: Microsoft Excel Complete Course What will make you stand out? Upon completion of this online Coding (C++, Python, JavaScript, Networking & IT) bundle, you will gain the following: CPD QS Accredited Proficiency with this Coding, C++ & Python bundle After successfully completing the Coding, C++ & Python bundle, you will receive a FREE PDF Certificate from REED as evidence of your newly acquired abilities. Lifetime access to the whole collection of learning materials in this Coding, C++ & Python bundle The online test with immediate results You can study and complete the Coding, C++ & Python bundle at your own pace. Study for the Coding, C++ & Python bundle using any internet-connected device, such as a computer, tablet, or mobile device. Each course in this Coding (C++, Python, JavaScript, Networking & IT) bundle holds a prestigious CPD accreditation, symbolising exceptional quality. The materials, brimming with knowledge, are regularly updated, ensuring their relevance. This Coding, C++ & Python bundle promises not just education but an evolving learning experience. Engage with this extraordinary collection, and prepare to enrich your personal and professional development. Embrace the future of learning with Coding (C++, Python, JavaScript, Networking & IT), a rich anthology of 30 diverse courses. Our experts handpick each course in the Coding, C++ & Python bundle to ensure a wide spectrum of learning opportunities. This Coding, C++ & Python bundle will take you on a unique and enriching educational journey. The Coding (C++, Python, JavaScript, Networking & IT) bundle encapsulates our mission to provide quality, accessible education for all. Whether you are just starting your career, looking to switch industries, or hoping to enhance your professional skill set, the Coding, C++ & Python bundle offers you the flexibility and convenience to learn at your own pace. Make the Coding, C++ & Python package your trusted companion in your lifelong learning journey. CPD 200 CPD hours / points Accredited by CPD Quality Standards Who is this course for? The Coding (C++, Python, JavaScript, Networking & IT) bundle is perfect for: Aspiring Programmers: Individuals interested in learning to program and develop software using popular languages like C++, Python, and JavaScript. IT Professionals: Those working in IT who wish to enhance their programming and networking skills to improve job performance and career prospects. Students in Technology: University or college students pursuing degrees in computer science, information technology, or related fields looking to supplement their studies with practical skills. Career Changers: Professionals aiming to transition into the tech industry and seeking foundational knowledge in programming and network management. Hobbyists and Tech Enthusiasts: Individuals passionate about technology and keen on developing their own projects or improving their understanding of how different aspects of the internet and software work. Requirements You are warmly invited to register for this Coding (C++, Python, JavaScript, Networking & IT) bundle. Please be aware that no formal entry requirements or qualifications are necessary. This curriculum has been crafted to be open to everyone, regardless of previous experience or educational attainment. Career path Upon Coding (C++, Python, JavaScript, Networking & IT) course completion, you can expect to: Software Developer Web Developer Systems Programmer Network Administrator Database Administrator Cybersecurity Analyst Data Scientist AI and Machine Learning Engineer Freelance Programmer Tech Entrepreneur Certificates CPD Certificates Digital certificate - Included

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The course covers data science and machine learning with R.

Overview of Data Science & Machine Learning with Python Join our Data Science & Machine Learning with Python course and discover your hidden skills, setting you on a path to success in this area. Get ready to improve your skills and achieve your biggest goals. The Data Science & Machine Learning with Python course has everything you need to get a great start in this sector. Improving and moving forward is key to getting ahead personally. The Data Science & Machine Learning with Python course is designed to teach you the important stuff quickly and well, helping you to get off to a great start in the field. So, what are you looking for? Enrol now! This Data Science & Machine Learning with Python Course will help you to learn: Learn strategies to boost your workplace efficiency. Hone your skills to help you advance your career. Acquire a comprehensive understanding of various topics and tips. Learn in-demand skills that are in high demand among UK employers This course covers the topic you must know to stand against the tough competition. The future is truly yours to seize with this Data Science & Machine Learning with Python. Enrol today and complete the course to achieve a certificate that can change your career forever. Details Perks of Learning with IOMH One-To-One Support from a Dedicated Tutor Throughout Your Course. Study Online - Whenever and Wherever You Want. Instant Digital/ PDF Certificate. 100% Money Back Guarantee. 12 Months Access. Process of Evaluation After studying the course, an MCQ exam or assignment will test your skills and knowledge. You have to get a score of 60% to pass the test and get your certificate. Certificate of Achievement Certificate of Completion - Digital / PDF Certificate After completing the Data Science & Machine Learning with Python course, you can order your CPD Accredited Digital / PDF Certificate for £5.99.  Certificate of Completion - Hard copy Certificate You can get the CPD Accredited Hard Copy Certificate for £12.99. Shipping Charges: Inside the UK: £3.99 International: £10.99 Who Is This Course for? This Data Science & Machine Learning with Python is suitable for anyone aspiring to start a career in relevant field; even if you are new to this and have no prior knowledge, this course is going to be very easy for you to understand.  On the other hand, if you are already working in this sector, this course will be a great source of knowledge for you to improve your existing skills and take them to the next level.  This course has been developed with maximum flexibility and accessibility, making it ideal for people who don't have the time to devote to traditional education. Requirements You don't need any educational qualification or experience to enrol in the Data Science & Machine Learning with Python course. Do note: you must be at least 16 years old to enrol. Any internet-connected device, such as a computer, tablet, or smartphone, can access this online course. Career Path The certification and skills you get from this Data Science & Machine Learning with Python Course can help you advance your career and gain expertise in several fields, allowing you to apply for high-paying jobs in related sectors. Course Curriculum Course Overview & Table of Contents Course Overview & Table of Contents 00:09:00 Introduction to Machine Learning - Part 1 - Concepts , Definitions and Types Introduction to Machine Learning - Part 1 - Concepts , Definitions and Types 00:05:00 Introduction to Machine Learning - Part 2 - Classifications and Applications Introduction to Machine Learning - Part 2 - Classifications and Applications 00:06:00 System and Environment preparation - Part 1 System and Environment preparation - Part 1 00:04:00 System and Environment preparation - Part 2 System and Environment preparation - Part 2 00:06:00 Learn Basics of python - Assignment Learn Basics of python - Assignment 1 00:10:00 Learn Basics of python - Assignment Learn Basics of python - Assignment 2 00:09:00 Learn Basics of python - Functions Learn Basics of python - Functions 00:04:00 Learn Basics of python - Data Structures Learn Basics of python - Data Structures 00:12:00 Learn Basics of NumPy - NumPy Array Learn Basics of NumPy - NumPy Array 00:06:00 Learn Basics of NumPy - NumPy Data Learn Basics of NumPy - NumPy Data 00:08:00 Learn Basics of NumPy - NumPy Arithmetic Learn Basics of NumPy - NumPy Arithmetic 00:04:00 Learn Basics of Matplotlib Learn Basics of Matplotlib 00:07:00 Learn Basics of Pandas - Part 1 Learn Basics of Pandas - Part 1 00:06:00 Learn Basics of Pandas - Part 2 Learn Basics of Pandas - Part 2 00:07:00 Understanding the CSV data file Understanding the CSV data file 00:09:00 Load and Read CSV data file using Python Standard Library Load and Read CSV data file using Python Standard Library 00:09:00 Load and Read CSV data file using NumPy Load and Read CSV data file using NumPy 00:04:00 Load and Read CSV data file using Pandas Load and Read CSV data file using Pandas 00:05:00 Dataset Summary - Peek, Dimensions and Data Types Dataset Summary - Peek, Dimensions and Data Types 00:09:00 Dataset Summary - Class Distribution and Data Summary Dataset Summary - Class Distribution and Data Summary 00:09:00 Dataset Summary - Explaining Correlation Dataset Summary - Explaining Correlation 00:11:00 Dataset Summary - Explaining Skewness - Gaussian and Normal Curve Dataset Summary - Explaining Skewness - Gaussian and Normal Curve 00:07:00 Dataset Visualization - Using Histograms Dataset Visualization - Using Histograms 00:07:00 Dataset Visualization - Using Density Plots Dataset Visualization - Using Density Plots 00:06:00 Dataset Visualization - Box and Whisker Plots Dataset Visualization - Box and Whisker Plots 00:05:00 Multivariate Dataset Visualization - Correlation Plots Multivariate Dataset Visualization - Correlation Plots 00:08:00 Multivariate Dataset Visualization - Scatter Plots Multivariate Dataset Visualization - Scatter Plots 00:05:00 Data Preparation (Pre-Processing) - Introduction Data Preparation (Pre-Processing) - Introduction 00:09:00 Data Preparation - Re-scaling Data - Part 1 Data Preparation - Re-scaling Data - Part 1 00:09:00 Data Preparation - Re-scaling Data - Part 2 Data Preparation - Re-scaling Data - Part 2 00:09:00 Data Preparation - Standardizing Data - Part 1 Data Preparation - Standardizing Data - Part 1 00:07:00 Data Preparation - Standardizing Data - Part 2 Data Preparation - Standardizing Data - Part 2 00:04:00 Data Preparation - Normalizing Data Data Preparation - Normalizing Data 00:08:00 Data Preparation - Binarizing Data Data Preparation - Binarizing Data 00:06:00 Feature Selection - Introduction Feature Selection - Introduction 00:07:00 Feature Selection - Uni-variate Part 1 - Chi-Squared Test Feature Selection - Uni-variate Part 1 - Chi-Squared Test 00:09:00 Feature Selection - Uni-variate Part 2 - Chi-Squared Test Feature Selection - Uni-variate Part 2 - Chi-Squared Test 00:10:00 Feature Selection - Recursive Feature Elimination Feature Selection - Recursive Feature Elimination 00:11:00 Feature Selection - Principal Component Analysis (PCA) Feature Selection - Principal Component Analysis (PCA) 00:09:00 Feature Selection - Feature Importance Feature Selection - Feature Importance 00:06:00 Refresher Session - The Mechanism of Re-sampling, Training and Testing Refresher Session - The Mechanism of Re-sampling, Training and Testing 00:12:00 Algorithm Evaluation Techniques - Introduction Algorithm Evaluation Techniques - Introduction 00:07:00 Algorithm Evaluation Techniques - Train and Test Set Algorithm Evaluation Techniques - Train and Test Set 00:11:00 Algorithm Evaluation Techniques - K-Fold Cross Validation Algorithm Evaluation Techniques - K-Fold Cross Validation 00:09:00 Algorithm Evaluation Techniques - Leave One Out Cross Validation Algorithm Evaluation Techniques - Leave One Out Cross Validation 00:05:00 Algorithm Evaluation Techniques - Repeated Random Test-Train Splits Algorithm Evaluation Techniques - Repeated Random Test-Train Splits 00:07:00 Algorithm Evaluation Metrics - Introduction Algorithm Evaluation Metrics - Introduction 00:09:00 Algorithm Evaluation Metrics - Classification Accuracy Algorithm Evaluation Metrics - Classification Accuracy 00:08:00 Algorithm Evaluation Metrics - Log Loss Algorithm Evaluation Metrics - Log Loss 00:03:00 Algorithm Evaluation Metrics - Area Under ROC Curve Algorithm Evaluation Metrics - Area Under ROC Curve 00:06:00 Algorithm Evaluation Metrics - Confusion Matrix Algorithm Evaluation Metrics - Confusion Matrix 00:10:00 Algorithm Evaluation Metrics - Classification Report Algorithm Evaluation Metrics - Classification Report 00:04:00 Algorithm Evaluation Metrics - Mean Absolute Error - Dataset Introduction Algorithm Evaluation Metrics - Mean Absolute Error - Dataset Introduction 00:06:00 Algorithm Evaluation Metrics - Mean Absolute Error Algorithm Evaluation Metrics - Mean Absolute Error 00:07:00 Algorithm Evaluation Metrics - Mean Square Error Algorithm Evaluation Metrics - Mean Square Error 00:03:00 Algorithm Evaluation Metrics - R Squared Algorithm Evaluation Metrics - R Squared 00:04:00 Classification Algorithm Spot Check - Logistic Regression Classification Algorithm Spot Check - Logistic Regression 00:12:00 Classification Algorithm Spot Check - Linear Discriminant Analysis Classification Algorithm Spot Check - Linear Discriminant Analysis 00:04:00 Classification Algorithm Spot Check - K-Nearest Neighbors Classification Algorithm Spot Check - K-Nearest Neighbors 00:05:00 Classification Algorithm Spot Check - Naive Bayes Classification Algorithm Spot Check - Naive Bayes 00:04:00 Classification Algorithm Spot Check - CART Classification Algorithm Spot Check - CART 00:04:00 Classification Algorithm Spot Check - Support Vector Machines Classification Algorithm Spot Check - Support Vector Machines 00:05:00 Regression Algorithm Spot Check - Linear Regression Regression Algorithm Spot Check - Linear Regression 00:08:00 Regression Algorithm Spot Check - Ridge Regression Regression Algorithm Spot Check - Ridge Regression 00:03:00 Regression Algorithm Spot Check - Lasso Linear Regression Regression Algorithm Spot Check - Lasso Linear Regression 00:03:00 Regression Algorithm Spot Check - Elastic Net Regression Regression Algorithm Spot Check - Elastic Net Regression 00:02:00 Regression Algorithm Spot Check - K-Nearest Neighbors Regression Algorithm Spot Check - K-Nearest Neighbors 00:06:00 Regression Algorithm Spot Check - CART Regression Algorithm Spot Check - CART 00:04:00 Regression Algorithm Spot Check - Support Vector Machines (SVM) Regression Algorithm Spot Check - Support Vector Machines (SVM) 00:04:00 Compare Algorithms - Part 1 : Choosing the best Machine Learning Model Compare Algorithms - Part 1 : Choosing the best Machine Learning Model 00:09:00 Compare Algorithms - Part 2 : Choosing the best Machine Learning Model Compare Algorithms - Part 2 : Choosing the best Machine Learning Model 00:05:00 Pipelines : Data Preparation and Data Modelling Pipelines : Data Preparation and Data Modelling 00:11:00 Pipelines : Feature Selection and Data Modelling Pipelines : Feature Selection and Data Modelling 00:10:00 Performance Improvement: Ensembles - Voting Performance Improvement: Ensembles - Voting 00:07:00 Performance Improvement: Ensembles - Bagging Performance Improvement: Ensembles - Bagging 00:08:00 Performance Improvement: Ensembles - Boosting Performance Improvement: Ensembles - Boosting 00:05:00 Performance Improvement: Parameter Tuning using Grid Search Performance Improvement: Parameter Tuning using Grid Search 00:08:00 Performance Improvement: Parameter Tuning using Random Search Performance Improvement: Parameter Tuning using Random Search 00:06:00 Export, Save and Load Machine Learning Models : Pickle Export, Save and Load Machine Learning Models : Pickle 00:10:00 Export, Save and Load Machine Learning Models : Joblib Export, Save and Load Machine Learning Models : Joblib 00:06:00 Finalizing a Model - Introduction and Steps Finalizing a Model - Introduction and Steps 00:07:00 Finalizing a Classification Model - The Pima Indian Diabetes Dataset Finalizing a Classification Model - The Pima Indian Diabetes Dataset 00:07:00 Quick Session: Imbalanced Data Set - Issue Overview and Steps Quick Session: Imbalanced Data Set - Issue Overview and Steps 00:09:00 Iris Dataset : Finalizing Multi-Class Dataset Iris Dataset : Finalizing Multi-Class Dataset 00:09:00 Finalizing a Regression Model - The Boston Housing Price Dataset Finalizing a Regression Model - The Boston Housing Price Dataset 00:08:00 Real-time Predictions: Using the Pima Indian Diabetes Classification Model Real-time Predictions: Using the Pima Indian Diabetes Classification Model 00:07:00 Real-time Predictions: Using Iris Flowers Multi-Class Classification Dataset Real-time Predictions: Using Iris Flowers Multi-Class Classification Dataset 00:03:00 Real-time Predictions: Using the Boston Housing Regression Model Real-time Predictions: Using the Boston Housing Regression Model 00:08:00 Resources Resources - Data Science & Machine Learning with Python 00:00:00