Curious about how to make the most of ChatGPT without getting lost in technical jargon? This Beginner Crash Course on ChatGPT offers a straightforward introduction to one of today’s most talked-about AI tools. Designed to familiarise you with the basics, it covers how to interact with ChatGPT effectively, crafting prompts that get you the best responses and understanding its capabilities and limitations. You’ll soon find yourself having conversations with AI that are surprisingly helpful — and perhaps even a little entertaining. Ideal for anyone interested in AI but unsure where to begin, this course guides you through the essentials with clarity and a touch of wit. Whether for personal curiosity, enhancing your work, or simply staying ahead of the digital curve, you’ll gain a practical grasp of how ChatGPT can assist in writing, research, brainstorming, and more. Delivered entirely online, it suits a variety of schedules and skill levels, offering a well-paced yet engaging journey into the world of conversational AI without any fuss. Learning Outcomes: Understand the capabilities of ChatGPT and its potential applications Learn how to sign up for an OpenAI account and set up ChatGPT Identify the benefits and limitations of using ChatGPT for business, teaching, and research Develop skills in using ChatGPT to improve customer engagement, personalised learning, and information retrieval Explore additional resources and videos to enhance your ChatGPT experience The Beginner Crash Course on ChatGPT is designed to provide learners with a comprehensive understanding of this cutting-edge technology and its potential applications. Through six modules, learners will gain an understanding of the capabilities of ChatGPT, how to sign up for an OpenAI account, and how to set up ChatGPT for business, teaching, and research purposes. Upon completing this course, learners will have the knowledge and skills to use ChatGPT to improve customer engagement, personalised learning, and information retrieval. With expert guidance and a comprehensive curriculum, this course is the key to unlocking the potential of ChatGPT and taking your interactions with technology to the next level. â±â± A Beginner Crash Course on ChatGPT Course Curriculum Sign up for an OpenAI Account What can ChatGPT do for you? ChatGPT for Business ChatGPT for Teaching ChatGPT for Research Limitations of ChatGPT 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 £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? Business owners seeking to improve customer engagement Teachers looking to provide personalised support to their students Researchers seeking answers to complex questions Anyone interested in learning about AI-powered chatbots Individuals seeking to enhance their technology skills Career path Customer service representative Online tutor or trainer Research analyst Content writer Data analyst £20,000 - £60,000+ (depending on career path and experience) 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.
Ever wondered how machines recognise faces, detect traffic signs, or even tag photos with uncanny accuracy? This course dives straight into the heart of Convolutional Neural Networks (CNNs) – the very engine behind image recognition and deep learning breakthroughs. With a clear focus on project-based learning, you’ll explore how CNNs work, how they’re built, and how they’re trained to see and interpret the world digitally. The content flows logically and stays rooted in clarity, making even the most complex architectures feel almost polite. This is not just a sequence of slides and jargon. It’s a well-structured digital journey tailored for learners who want to confidently grasp how deep learning models behave and evolve. Whether you're brushing up on your neural network knowledge or aiming to reinforce your AI expertise, the course serves up algorithms, code walkthroughs and layered insights with a tone that’s informative, direct, and occasionally dry-witted. If you fancy turning raw data into pixel-level predictions using nothing but code, logic, and neural layers — you’re exactly where you need to be. Learning Outcomes: Gain a solid understanding of convolutional neural networks and their applications in deep learning. Learn how to install the necessary packages and set up a dataset structure for deep learning projects. Discover how to create your own convolutional neural network model and layers using Python. Understand how to preprocess and augment data for advanced image recognition tasks. Learn how to evaluate the accuracy of your models and understand the different models available for deep learning projects. The Deep Learning Projects - Convolutional Neural Network course is designed to provide you with the skills and knowledge you need to build your own advanced deep learning projects. Using Python, you'll learn how to install the necessary packages, set up a dataset structure, and create your own convolutional neural network model and layers. You'll also learn how to preprocess and augment data to enhance the accuracy of your models and evaluate the performance of your models using data generators. Deep Learning Projects - Convolutional Neural Network Course Curriculum Section 01: Introduction Section 02: Installations Section 03: Getting Started Section 04: Accuracy 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 convolutional neural networks. Programmers who want to learn how to build advanced models for image recognition. Entrepreneurs who want to develop their own deep learning-based applications for image recognition. 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 convolutional neural networks and deep learning projects. Career path Data Analyst: £24,000 - £45,000 Machine Learning Engineer: £28,000 - £65,000 Computer Vision Engineer: £30,000 - £70,000 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.
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.
If you're fascinated by the mysteries of market movement and want to explore how machines attempt to predict tomorrow's numbers today, this Stock Price Prognostics Course will suit your curious streak perfectly. Built around deep learning models tailored for time series forecasting, the course takes a closer look at how algorithms can be trained to recognise patterns, spot trends, and occasionally raise an eyebrow at the randomness of stock data. It’s technical, structured, and surprisingly satisfying — no crystal ball involved, just code that tries its best. Focusing on stock price prognostics through real datasets, the course guides you through model building, evaluation metrics and common forecasting techniques using neural networks — all in plain English, with clear explanations and zero mystique. It’s suited to those who enjoy a challenge, appreciate a bit of data drama, and prefer graphs that actually say something. Whether you're brushing up on deep learning or building from the ground up, this course connects theory with application in a focused, jargon-light approach — and no need to wear a tie or trade a share. Learning Outcomes: Build a deep learning model using RNN that can accurately predict stock prices. Preprocess data and perform exploratory data analysis. Scale features and make predictions on test data. Gain real-world experience in deep learning development. Contribute to the development of cutting-edge technology in the finance industry. The Hands-on Deep Learning Projects - Stock Price Prognostics course is designed to provide you with the skills and knowledge needed to develop a deep learning model using RNN that can accurately predict stock prices. In this course, you'll learn how to preprocess data, perform exploratory data analysis, scale features, and make predictions on test data. The course is perfect for aspiring data scientists, machine learning engineers, and developers interested in deep learning development. By the end of this course, you'll have a deep understanding of how to build a deep learning model that can revolutionise the world of finance. With hands-on experience in developing cutting-edge technology, you'll be well-equipped to start a career in deep learning and contribute to the development of cutting-edge technology in the finance industry. â±â± Hands on Deep Learning Projects - Stock price Prognostics Course Curriculum Section 01: Introduction Section 02: Installation of Tools and Libraries Section 03: Dataset Section 04: EDA Section 05: Feature Scaling Section 06: Building RNN Section 07: Prediction on Test Data Section 08: Output 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 £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? Aspiring data scientists. Machine learning engineers. Developers interested in deep learning development. Anyone interested in the field of deep learning. Professionals looking to upskill in the latest technology. Career path Data Scientist: £40,000 to £80,000 per year. Machine Learning Engineer: £55,000 to £90,000 per year. Artificial Intelligence Developer: £40,000 to £80,000 per year. Quantitative Analyst: £30,000 to £80,000 per year. Financial Data Analyst: £25,000 to £60,000 per year. 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.
Embark on a journey into the world of technology with Spark Generation! Learn the fundamentals of computer science, coding languages, and algorithmic thinking. Discover the logic behind programs and explore the creative potential of digital innovation.
Embark on a journey into the world of technology with Spark Generation and our Cambridge self-paced courses! Learn the fundamentals of computer science, coding languages, and algorithmic thinking. Discover the logic behind programs and explore the creative potential of digital innovation.
This educational talk demonstrates how Queen Square Radiosurgery Centre has become a hub for cutting-edge research in Radiosurgery. Gain invaluable insights into the clinical benefits of Gamma Knife treatment and its impact on cases that might have otherwise been prescribed whole-brain radiation therapy (WBRT).