43530 Learning courses in Sheffield delivered Online

In this course, you will quickly learn how to build DNNs (Deep Neural Networks) and how to train them. This learning-by-doing course will also help you master the elementary concepts and methodology with Python. You need to have a basic knowledge of python to get the best out of this course.

Dive into the fascinating world of deep learning with this expertly crafted course designed to unravel the mysteries of neural networks using R. This course guides you through the core principles of neural networks, illustrating how layers of algorithms mimic the human brain’s ability to identify patterns and make decisions. Whether you’re a data enthusiast or a professional seeking to enhance your analytical toolkit, this course offers a clear and engaging path to understanding deep learning concepts through the power of R programming. With a sharp focus on theory and application, you will explore how to build, train, and optimise neural networks effectively, while leveraging R’s rich ecosystem of libraries and tools. The course content is designed to maintain a perfect balance between depth and clarity, making complex topics accessible without oversimplification. By the end, you will be equipped with a strong conceptual foundation and the confidence to approach deep learning projects with R, all through an engaging online format that fits seamlessly into your schedule. Learning Outcomes: Understanding of single-layer and multi-layer neural networks Knowledge of R programming for neural network applications Implementation of neural networks in real-world projects Familiarity with agriculture and war datasets for neural network modelling Ability to evaluate neural network model accuracy and performance The Deep Learning Neural Network with R course is designed to provide learners with a comprehensive understanding of how to build and evaluate neural networks using R programming language. The course includes four modules that cover single-layer and multi-layer neural networks applied to agriculture and war datasets. Each module contains practical hands-on projects that allow learners to gain real-world experience in neural network development and evaluation. By the end of the course, learners will have a solid understanding of neural network concepts, R programming language, and practical experience with real-world datasets. Deep Learning Neural Network with R Course Curriculum Section 01: Single Layer Neural Networks Project - Agriculture (Part - 1) Section 02: Single Layer Neural Networks Project - Agriculture (Part - 2) Section 03: Multi-Layer Neural Networks Project - Deaths in wars (Part - 1) Section 04: Multi-Layer Neural Networks Project - Deaths in wars (Part - 2) 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? Data analysts and scientists seeking to expand their knowledge of neural networks and R programming Professionals interested in applying neural networks to agriculture or war datasets Students and researchers interested in deep learning and machine learning techniques Anyone looking to enhance their skills in data analysis and modelling using neural networks and R programming Requirements There are no formal entry requirements for the course, with enrollment open to anyone! Career path Data Analyst Machine Learning Engineer Data Scientist Artificial Intelligence Developer Research Scientist Entry-level positions such as Data Analysts can expect to earn between £25,000 to £35,000 per annum, whereas senior-level positions such as Machine Learning Engineers can earn upwards of £70,000 per annum. 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.

This is a gateway course for all further learning in FD&FA systems.

Are you looking to enhance your Learning Support Assistant (LSA) skills? If yes, then you have come to the right place. Our comprehensive course on Learning Support Assistant (LSA) will assist you in producing the best possible outcome by mastering the Learning Support Assistant (LSA) skills. The Learning Support Assistant (LSA) course is for those who want to be successful. In the Learning Support Assistant (LSA) course, you will learn the essential knowledge needed to become well versed in Learning Support Assistant (LSA). Our Learning Support Assistant (LSA) course starts with the basics of Learning Support Assistant (LSA) and gradually progresses towards advanced topics. Therefore, each lesson of this Learning Support Assistant (LSA) course is intuitive and easy to understand. Why would you choose the Learning Support Assistant (LSA) course from Compliance Central: Lifetime access to Learning Support Assistant (LSA) course materials Full tutor support is available from Monday to Friday with the Learning Support Assistant (LSA) course Learn Learning Support Assistant (LSA) skills at your own pace from the comfort of your home Gain a complete understanding of Learning Support Assistant (LSA) course Accessible, informative Learning Support Assistant (LSA) learning modules designed by experts Get 24/7 help or advice from our email and live chat teams with the Learning Support Assistant (LSA) Study Learning Support Assistant (LSA) in your own time through your computer, tablet or mobile device A 100% learning satisfaction guarantee with your Learning Support Assistant (LSA) Course Learning Support Assistant (LSA) Curriculum Breakdown of the Learning Support Assistant (LSA) Course Module 01: The Roles of a Learning Support Assistant (LSA) Module 02: Working with Children in a School Module 03: Assessing Students Module 04: Skills of a Learning Support Assistant Module 05: Providing for All Children Module 06: Safeguarding and Wellbeing of Children and Young People Module 07: Dealing with Emergencies Module 08: Special Educational Needs (SEN) Module 09: Professional Development Module 10: Time and Stress Management CPD 10 CPD hours / points Accredited by CPD Quality Standards Who is this course for? The Learning Support Assistant (LSA) course helps aspiring professionals who want to obtain the knowledge and familiarise themselves with the skillsets to pursue a career in Learning Support Assistant (LSA). It is also great for professionals who are already working in Learning Support Assistant (LSA) and want to get promoted at work. Requirements To enrol in this Learning Support Assistant (LSA) course, all you need is a basic understanding of the English Language and an internet connection. Career path The Learning Support Assistant (LSA) course will enhance your knowledge and improve your confidence in exploring opportunities in various sectors related to Learning Support Assistant (LSA). Learning Support Assistant (LSA): £17,000 to £22,000 per year Special Educational Needs (SEN) Teaching Assistant: £16,000 to £25,000 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

Artificial neural networks (ANNs) are the most powerful machine learning algorithms available today. They are capable of learning complex relationships in data, and they have been used to achieve state-of-the-art results in a wide variety of fields, including image recognition, natural language processing, and speech recognition. The Future of Machine Learning is Here! This Project on Deep Learning - Artificial Neural Network course will teach you how to build and train ANNs from scratch. You will learn about the different components of an ANN, such as the input layer, hidden layers, and output layer. You will also learn about the different activation functions that can be used in ANNs, and you will see how to optimise ANNs for different tasks. In addition to the theoretical concepts, you will also get experience with ANNs. You will work on a project where you will build an ANN to classify images. You will use the TensorFlow library to build your ANN, and you will see how to train your ANN on a dataset of images. By the end of this Project on Deep Learning - Artificial Neural Network course, you will have a deep understanding of ANNs and how to use them. You will be able to build your own ANNs to solve a variety of problems. You will also be able to use the TensorFlow library to build and train ANNs. So what are you waiting for? Enrol in this course today and start learning about the future of machine learning!   Learning Outcomes: Through this comprehensive course, you should be able to: Understand the fundamental concepts of deep learning and artificial neural networks. Install and configure an artificial neural network framework. Preprocess and structure data for optimal model performance. Encode data effectively for neural network training and predictions. Build and deploy artificial neural networks for real-world applications. Address data imbalance challenges and optimise model accuracy.   Who is this course for? This Project on Deep Learning - Artificial Neural Network course is ideal for: Data scientists and machine learning practitioners seeking to expand their knowledge. Software engineers interested in leveraging deep learning techniques. Students pursuing a career in artificial intelligence and machine learning. Professionals looking to enhance their skills in neural network development. Individuals with a passion for exploring advanced machine learning techniques.   Career Path  Our course will prepare you for a range of careers, including: Deep Learning Engineer: £40,000 - £100,000 per year. Machine Learning Researcher: £45,000 - £120,000 per year. Data Scientist: £50,000 - £110,000 per year. Artificial Intelligence Specialist: £55,000 - £130,000 per year. Software Engineer (specialising in AI): £45,000 - £100,000 per year. Research Scientist (Machine Learning): £50,000 - £120,000 per year. AI Consultant: £60,000 - £150,000 per year. Certification After studying the course materials of the Project on Deep Learning - Artificial Neural Network (ANNs) 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. Prerequisites This Project on Deep Learning - Artificial Neural Network (ANNs) does not require you to have any prior qualifications or experience. You can just enrol and start learning.This Project on Deep Learning - Artificial Neural Network (ANNs) 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.   Course Curriculum Section 01: Introduction Introduction of Project 00:03:00 Section 02: ANN Installation Setup Environment for ANN 00:11:00 ANN Installation 00:09:00 Section 03: Data Preprocessing Import Libraries and Data Preprocessing 00:11:00 Data Preprocessing 00:07:00 Data Preprocessing Continue 00:10:00 Section 04: Data Encoding Data Exploration 00:10:00 Encoding 00:07:00 Encoding Continue 00:06:00 Preparation of Dataset for Training 00:04:00 Section 05: Steps to Build ANN Steps to Build ANN Part 1 00:06:00 Steps to Build ANN Part 2 00:06:00 Steps to Build ANN Part 3 00:06:00 Steps to Build ANN Part 4 00:09:00 Section 06: Predictions and Imbalance-Learn Predictions 00:11:00 Predictions Continue 00:08:00 Resampling Data with Imbalance-Learn 00:09:00 Resampling Data with Imbalance-Learn Continue 00:08:00

Step into the intricate world of artificial neural networks with a course that sheds light on one of the most dynamic branches of deep learning. Designed for those keen to explore the structure, function and logic behind intelligent systems, this course blends academic insight with a clear, structured approach to the evolving digital frontier. From perceptrons to multilayer networks, it offers a layered understanding of how machines mimic the human brain’s decision-making process — minus the caffeine and existential crises. Whether you're sharpening your knowledge or stepping into the field with curiosity, this course provides a sharp focus on the core principles that power technologies like image recognition, voice synthesis and predictive modelling. Delivered in an accessible format, it caters to learners who want depth without the fluff, logic without the waffle, and progress without the guesswork. Neural networks may be artificial — but your understanding of them won’t be. Learning Outcomes: Gain a solid understanding of artificial neural networks and their applications in deep learning. Learn how to install the necessary packages and preprocess data for neural network training. Discover how to encode data and build your own artificial neural network using Python. Understand the steps involved in making predictions using your neural network model. Learn how to deal with imbalanced data in your neural network training. The Project on Deep Learning - Artificial Neural Network course is designed to provide you with the skills and knowledge you need to build your own neural network and perform complex tasks using deep learning. You'll learn how to install the necessary packages, preprocess data, and encode data for neural network training. You'll also gain a deeper understanding of artificial neural networks and learn how to build your own model using Python. By the end of the course, you'll be able to make predictions using your neural network model and understand how to deal with imbalanced data in your training. Project on Deep Learning - Artificial Neural Network Course Curriculum Section 01: Introduction Section 02: ANN Installation Section 03: Data Preprocessing Section 04: Data Encoding Section 05: Steps to Build ANN Section 06: Predictions and Imbalance-Learn 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? Data analysts who want to expand their skills in deep learning and artificial neural networks. Programmers who want to learn how to build their own neural network models for advanced tasks. Entrepreneurs who want to develop their own deep learning-based applications. Students who want to enhance their skills in deep learning and prepare for a career in the field. Anyone who wants to explore the world of artificial neural networks and deep learning projects. Career path Data Analyst: £24,000 - £45,000 Machine Learning Engineer: £28,000 - £65,000 Deep Learning Engineer: £30,000 - £75,000 Technical Lead: £40,000 - £90,000 Chief Technology Officer: £90,000 - £250,000 Certificates Certificate of completion Digital certificate - £9 You can apply for a CPD Accredited PDF Certificate at the cost of £9. Certificate of completion Hard copy certificate - £15 Hard copy can be sent to you via post at the expense of £15.

Use deep learning, Computer Vision, and machine learning techniques to build an autonomous car with Python

2 QLS Endorsed Course | CPD Certified | Free PDF + Hardcopy Certificates | 80 CPD Points | Lifetime Access

Discover the thrilling world of artificial intelligence with the 'Machine Learning Course with Python'. Immerse yourself in a voyage from foundational concepts, unveiling the mysteries behind algorithms, to diving deep into the cores of preprocessing, regression, and classification. Crafted meticulously, this course introduces Python as the catalyst, opening doors to data-driven decision-making and predictive analysis, empowering your journey in the ever-evolving field of machine learning. Learning Outcomes Grasp the foundational knowledge of various machine learning algorithms. Attain proficiency in preprocessing data for optimal outcomes. Master the nuances of regression analysis using Python. Delve into the intricacies of classification techniques. Enhance problem-solving abilities with practical Python-driven machine learning applications. Why choose this Machine Learning Course with Python course? 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 Machine Learning Course with Python 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 Machine Learning Course with Python course for? Aspiring data scientists eager to harness the power of machine learning. Python enthusiasts aiming to delve into its applications in AI. Professionals in the tech industry seeking a transition into data roles. Academics and researchers wanting to employ machine learning in their work. Business analysts aiming to leverage predictive analytics for better insights. Career path Data Scientist: £40,000 - £70,000 Machine Learning Engineer: £50,000 - £80,000 AI Researcher: £45,000 - £75,000 Data Analyst: £30,000 - £50,000 Python Developer: £35,000 - £65,000 Business Intelligence Developer: £40,000 - £60,000 Prerequisites This Machine Learning Course with Python does not require you to have any prior qualifications or experience. You can just enrol and start learning.This Machine Learning Course with Python was made by professionals and it is compatible with all PC's, Mac's, tablets and smartphones. You will be able to access the course from anywhere at any time as long as you have a good enough internet connection. Certification After studying the course materials, there will be a written assignment test which you can take at the end of the course. After successfully passing the test you will be able to claim the pdf certificate for £4.99 Original Hard Copy certificates need to be ordered at an additional cost of £8. Course Curriculum Module 01: Introduction to Machine Learning Algorithms Introduction to types of ML algorithm 00:02:00 Module 02: Preprocessing Importing a dataset in python 00:02:00 Resolving Missing Values 00:06:00 Managing Category Variables 00:04:00 Training and Testing Datasets 00:07:00 Normalizing Variables 00:02:00 Normalizing Variables - Python Code 00:03:00 Summary 00:01:00 Module 03: Regression Simple Linear Regression - How it works? 00:04:00 Simple Linear Regreesion - Python Implementation 00:07:00 Multiple Linear Regression - How it works? 00:01:00 Multiple Linear Regression - Python Implementation 00:09:00 Decision Trees - How it works? 00:05:00 Random Forest - How it works? 00:03:00 Decision Trees and Random Forest - Python Implementation 00:04:00 Module 04: Classification kNN - How it works? 00:02:00 kNN - Python Implementation 00:10:00 Decision Tree Classifier and Random Forest Classifier in Python 00:10:00 SVM - How it works? 00:04:00 SVM - Python Implementation 00:06:00 Assignment Assignment - Machine Learning Course with Python 00:00:00