133 Deep Learning courses in Birmingham delivered On Demand

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.

In this course, we will start with extremely basic concepts such as learning the programming language fundamentals and other supporting libraries. Then we will proceed with the core topics with the help of real-world datasets to gain a complete understanding of deep learning using Python and Keras.

Learn to apply sentiment analysis to your problems through a practical, real-world use case.

Step into the fascinating world of deep learning with our Deep Learning Projects - Handwritten Digit Recognition Using Neural Network course. This course takes you through the power of neural networks by using one of the most iconic machine learning challenges—digit recognition. Whether you're brushing up on your AI knowledge or taking your first step into neural networks, this course simplifies the complexity without watering it down. Expect clear, jargon-free explanations that give neural networks a human touch. Learn how digits are recognised, how machines learn from data, and what goes on inside those layers of artificial intelligence—without sounding like a maths textbook. From data input to prediction output, the entire pipeline is broken down in a logical, structured, and thoroughly digestible way. If you're into machine learning, this project will speak your language—digitally. Learning Outcomes: Gain a solid understanding of the principles of deep learning and neural networks. Learn how to use Google Collab to import and preprocess data for deep learning projects. Discover how to create your own neural network model to recognise handwritten digits. Understand how to train your model, make predictions, and evaluate its performance. Learn how to create your own convolutional neural network model for even more advanced recognition tasks. The Deep Learning Projects - Handwritten Digit Recognition Using Neural Network course is designed to provide you with the skills and knowledge you need to build your own neural network for handwritten digit recognition. Using Google Collab, you'll learn how to import and preprocess data for deep learning projects, create your own neural network model, and train it to recognize handwritten digits with high accuracy. You'll also discover how to evaluate the performance of your model and create a convolutional neural network model for even more advanced recognition tasks. Deep Learning Projects - Handwritten Digit Recognition Using Neural Network Course Curriculum Lesson 01: Introduction to Project Lesson 02: Google Collab Lesson 03: Importing Packages and Data Lesson 04: Preprocessing and Model Creation Lesson 05: Training the Model and Prediction Lesson 06: Model Creation using CNN Lesson 07: CNN Model Prediction 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 neural networks. Programmers who want to learn how to build their own neural network models for advanced recognition 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 deep learning and neural networks. Career path Data Analyst: £24,000 - £45,000 Machine Learning Engineer: £28,000 - £65,000 Software Engineer: £28,000 - £60,000 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.

Gain the solid skills and knowledge to kickstart a successful career and learn from the experts with this

The complete guide to creating your own Pose Estimation apps: Learn the full workflow and get up to speed with developing 5 AI apps

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.

Unleashing the Power of Deep Learning: Mastering Neural Network with R Dive into the fascinating realm of artificial intelligence with our course, 'Deep Learning Neural Network with R.' Imagine a world where machines learn and make decisions, mimicking the intricacies of the human brain. This course is your gateway to unlocking the secrets of deep learning, focusing on neural networks implemented using the versatile R programming language. Immerse yourself in hands-on projects, from creating single-layer neural networks for agriculture analysis to mastering multi-layer neural networks for predicting deaths in wars. The journey begins with reviewing datasets and creating dataframes, leading you through running neural network code and generating insightful output plots. Join us in this captivating exploration, where coding meets creativity, and algorithms come to life. Learning Outcomes Master the fundamentals of single-layer neural networks, gaining the skills to analyze agricultural datasets effectively. Acquire proficiency in implementing multi-layer neural networks, specifically tailored for predicting outcomes in complex scenarios like deaths in wars. Develop hands-on experience in creating and manipulating dataframes for enhanced data analysis. Gain a deep understanding of neural network syntax, commands, and code execution in the R programming language. Hone your ability to generate meaningful output plots, transforming raw data into visually compelling insights. Why choose this Deep Learning Neural Network with R course? Unlimited access to the course for a lifetime. Opportunity to earn a certificate accredited by the CPD Quality Standards and CIQ after completing this course. Structured lesson planning in line with industry standards. Immerse yourself in innovative and captivating course materials and activities. Assessments designed to evaluate advanced cognitive abilities and skill proficiency. Flexibility to complete the Course at your own pace, on your own schedule. Receive full tutor support throughout the week, from Monday to Friday, to enhance your learning experience. Unlock career resources for CV improvement, interview readiness, and job success. Who is this Deep Learning Neural Network with R course for? Aspiring data scientists and analysts eager to delve into the world of deep learning. R programming enthusiasts looking to enhance their skills with practical applications. Students and professionals in computer science, statistics, or related fields. Individuals seeking to understand the implementation of neural networks in real-world scenarios. Anyone fascinated by the intersection of coding, data analysis, and artificial intelligence. Career path Machine Learning Engineer: £40,000 - £70,000 Data Scientist: £35,000 - £60,000 Artificial Intelligence Researcher: £45,000 - £80,000 Research Scientist (Machine Learning): £50,000 - £90,000 Data Analyst (AI/ML): £30,000 - £55,000 Senior AI Developer: £60,000 - £100,000 Prerequisites This Deep Learning Neural Network with R does not require you to have any prior qualifications or experience. You can just enrol and start learning.This Deep Learning Neural Network with R 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 Section 01: Single Layer Neural Networks Project - Agriculture (Part - 1) Reviewing Dataset 00:14:00 Creating Dataframes 00:09:00 Generating Output 00:12:00 Section 02: Single Layer Neural Networks Project - Agriculture (Part - 2) Running Neural Network Code 00:11:00 Importing Dataset 00:09:00 Neural Network Plots for Hidden Layer 1 00:08:00 Section 03: Multi-Layer Neural Networks Project - Deaths in wars (Part - 1) Syntax and Commands for MLP 00:11:00 Running the Code 00:08:00 Testing for Dataframes 00:13:00 Predict Results 00:08:00 Section 04: Multi-Layer Neural Networks Project - Deaths in wars (Part - 2) Creating R Folder 00:14:00 Generating Output Plot 00:12:00 Testing and Predicting the Outputs 00:16:00

Description Register on the Deep Learning Neural Network with R today and build the experience, skills and knowledge you need to enhance your professional development and work towards your dream job. Study this course through online learning and take the first steps towards a long-term career. The course consists of a number of easy to digest, in-depth modules, designed to provide you with a detailed, expert level of knowledge. Learn through a mixture of instructional video lessons and online study materials. Receive online tutor support as you study the course, to ensure you are supported every step of the way. Get a certificate as proof of your course completion. The Deep Learning Neural Network with R course is incredibly great value and allows you to study at your own pace. Access the course modules from any internet-enabled device, including computers, tablets, and smartphones. The course is designed to increase your employability and equip you with everything you need to be a success. Enrol on the now and start learning instantly! What You Get With This Course Receive a digital certificate upon successful completion of the course Get taught by experienced, professional instructors Study at a time and pace that suits your learning style Get instant feedback on assessments 24/7 help and advice via email or live chat Get full tutor support on weekdays (Monday to Friday) Certificate of Achievement After the successful completion of the final assessment, you will receive a CPD-accredited certificate of achievement. The PDF certificate is for 9.99, and it will be sent to you immediately after through e-mail. You can get the hard copy for 15.99, which will reach your doorsteps by post.  Method of Assessment You need to attend an assessment right after the completion of this course to evaluate your progression. For passing the assessment, you need to score at least 60%. After submitting your assessment, you will get feedback from our experts immediately. Who Is This Course For The course is ideal for those who already work in this sector or are aspiring professionals. This course is designed to enhance your expertise and boost your CV. Learn key skills and gain a professional qualification to prove your newly-acquired knowledge.   Course Content Section 01: Single Layer Neural Networks Project - Agriculture (Part - 1) Reviewing Dataset 00:14:00 Creating Dataframes 00:09:00 Generating Output 00:12:00 Section 02: Single Layer Neural Networks Project - Agriculture (Part - 2) Running Neural Network Code 00:11:00 Importing Dataset 00:09:00 Neural Network Plots for Hidden Layer 1 00:08:00 Section 03: Multi-Layer Neural Networks Project - Deaths In Wars (Part - 1) Syntax and Commands for MLP 00:11:00 Running the Code 00:08:00 Testing for Dataframes 00:13:00 Predict Results 00:08:00 Section 04: Multi-Layer Neural Networks Project - Deaths In Wars (Part - 2) Creating R Folder 00:14:00 Generating Output Plot 00:12:00 Testing and Predicting the Outputs 00:16:00 Frequently Asked Questions Are there any prerequisites for taking the course? There are no specific prerequisites for this course, nor are there any formal entry requirements. All you need is an internet connection, a good understanding of English and a passion for learning for this course. Can I access the course at any time, or is there a set schedule? You have the flexibility to access the course at any time that suits your schedule. Our courses are self-paced, allowing you to study at your own pace and convenience. How long will I have access to the course? For this course, you will have access to the course materials for 1 year only. This means you can review the content as often as you like within the year, even after you've completed the course. However, if you buy Lifetime Access for the course, you will be able to access the course for a lifetime. Is there a certificate of completion provided after completing the course? Yes, upon successfully completing the course, you will receive a certificate of completion. This certificate can be a valuable addition to your professional portfolio and can be shared on your various social networks. Can I switch courses or get a refund if I'm not satisfied with the course? We want you to have a positive learning experience. If you're not satisfied with the course, you can request a course transfer or refund within 14 days of the initial purchase. How do I track my progress in the course? Our platform provides tracking tools and progress indicators for each course. You can monitor your progress, completed lessons, and assessments through your learner dashboard for the course. What if I have technical issues or difficulties with the course? If you encounter technical issues or content-related difficulties with the course, our support team is available to assist you. You can reach out to them for prompt resolution.

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