166 Courses

Are you looking to improve your current abilities or make a career move? Our unique SENCO Course might help you get there! Expand your expertise with high-quality training - study the course and get an expertly designed, great-value training experience. Learn from industry professionals and quickly equip yourself with the specific knowledge and skills you need to excel in your chosen career through this online training course. This online training course is accredited by CPDQS with 40 CPD points for professional development. Students can expect to complete this course in around 175 hours. You'll also get dedicated expert assistance from us to answer any queries you may have while studying our course. The course is broken down into several in-depth modules to provide you with the most convenient and rich learning experience possible. Upon successful completion of this course, you will receive an instant e-certificate as proof of comprehensive skill development and competency. Add these amazing new skills to your resume and boost your employability by simply enrolling in this course. With this comprehensive course, you can achieve your dreams and train for your ideal career. This course provides students with an in-depth learning experience that they can work through at their own pace to enhance their professional development. You'll get a Free Student ID card by enrolling in this course. This ID card entitles you to discounts on bus tickets, movie tickets, and library cards. Enrolling in the course will ensure that you land your dream career faster than you thought possible. Stand out from the crowd and train for the job you want with the program. Learning Outcomes: Instant access to verified and reliable information Participation in inventive and interactive training exercises Quick assessment and guidance for all subjects CPD accreditation for proof of acquired skills and knowledge Freedom to study in any location and at a pace that suits you Expert support from dedicated tutors committed to online learning Experts created the course to provide a rich and in-depth training experience for all students who enrol in it. Enrol in the course right now and you'll have immediate access to all of the course materials. Then, from any internet-enabled device, access the course materials and learn when it's convenient for you. Start your learning journey straight away with this course and take a step toward a brighter future! Why Prefer this Course? Opportunity to earn a certificate accredited by CPDQS after completing this course Student ID card with amazing discounts - completely for FREE! (£10 postal charge will be applicable for international delivery) Standards-aligned lesson planning Innovative and engaging content and activities Assessments that measure higher-level thinking and skills Complete the program in your own time, at your own pace *** Course Curriculum *** Here are the topics you will cover in the course. Module 01: Introduction to SEN Co-ordination Definition of special educational needs Relevant points of the Children and Families Act 2014 Key Principles The role of education providers in improving outcomes Module 02: The SENCO Role in Policy and Practice The beginnings of the SENCO role The SENCO role today: responsibilities as determined by the 2015 SEND Code of Practice Module 03: Roles and Responsibilities within Whole School SEN Co-ordination Duties of governing bodies & trust boards The role of the SENCO Decide to be operational, strategic or both Developing and understanding your ethos toward inclusion Developing your understanding of the definition of SEN Module 04: Supporting Teaching and Learning What is the curriculum? Learning to learn Important Theories of effective learning and Teaching The Influence of behavioural science on SEN Curriculum and pedagogy Cognitive development Module 05: The SENCO and the Senior Leadership Team The role of the SENCO and the Senior Leadership Team (SLT) If a SENCO should be on SLT The status of the SENCO role Leading without being part of SLT: leading with status Module 06: Supporting Colleagues and working with Professionals and Organisations beyond the School Importance of leading and supporting colleagues The SENCO role: leading and supporting colleagues Unpicking the Role of Teachers Leading and supporting colleagues: a whole-school approach Leading and supporting specific groups Module 07: Developing Relationships with Pupils and Parents Children and Families at the Centre: the policy context Pupil Relationships and Importance Family Relationships and Importance Meeting the SEND Code of Practice guidance An awareness of potential barriers Module 08: SENCO's Role in Leading and Managing SEND Administration Working with governors The management of SEN records Referral for an EHC assessment Annual review of EHC plans Dealing with complaints Module 09: Challenges and Opportunities Time and workload Resources Module 10:Developing Inclusive Practice and the Future SENCO Role The language of SEND and disability What is inclusive education? Parents' choice SENCO's role in training and developing others Support and training for SENCOs Assessment Process Once you have completed all the modules in the course, your skills and knowledge will be tested with an automated multiple-choice assessment. You will then receive instant results to let you know if you have successfully passed the course. CPD 40 CPD hours / points Accredited by CPD Quality Standards Who is this course for? Anyone interested in learning more about this subject should take this course. This will help you grasp the basic concepts as well as develop a thorough understanding of the subject. All are welcome to take this course. There are no prerequisites for enrolment, and you can access the course materials from any location in the world. Requirements The program does not require any prior knowledge; everyone may participate! This course is open to anyone interested in learning from anywhere in the world. Career path After completing this course, you are to start your career or begin the next phase of your career in this field. Our entire course will help you to gain a position of respect and dignity over your competitors. The certificate enhances your CV and helps you find work in the field concerned. Certificates CPD Accredited Certificate Digital certificate - £10 CPD Accredited Certificate Hard copy certificate - £29 If you are an international student, then you have to pay an additional 10 GBP as an international delivery charge.

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

Are you looking to enhance your Learning Disability Nursing skills? If yes, then you have come to the right place. Our comprehensive course on Learning Disability Nursing will assist you in producing the best possible outcome by mastering the Learning Disability Nursing skills. The Learning Disability Nursing course is for those who want to be successful. In the Learning Disability Nursing course, you will learn the essential knowledge needed to become well versed in Learning Disability Nursing. Our course starts with the basics of Learning Disability Nursing and gradually progresses towards advanced topics. Therefore, each lesson of this Learning Disability Nursing course is intuitive and easy to understand. Why would you choose the Learning Disability Nursing course from Compliance Central: Lifetime access to Learning Disability Nursing course materials Full tutor support is available from Monday to Friday with the Learning Disability Nursing course Learn Learning Disability Nursing skills at your own pace from the comfort of your home Gain a complete understanding of Learning Disability Nursing course Accessible, informative Learning Disability Nursing learning modules designed by experts Get 24/7 help or advice from our email and live chat teams with the Learning Disability Nursing Study Learning Disability Nursing in your own time through your computer, tablet or mobile device A 100% learning satisfaction guarantee with your Learning Disability Nursing Course Learning Disability Nursing Curriculum Breakdown of the Learning Disability Nursing Course Course Curriculum: Module 01: Learning Disability and Mental Health Module 02: Learning Disability Nursing Module 03: Psychosocial Interventions Module 04: Psychodynamic Approaches Module 05: Throughout the Lifespan Module 06: Role of the Learning Disability Nurse in Promoting Health and Well-Being Module 07: Care Planning in Mental Health Settings Module 08: Nursing Models and Behavioural Interventions Module 09: The Future of Learning Disability Nursing Module 10: Future Spheres of Practice Certification CPD Accredited (CPD QS) Certificate Digital (PDF) & Hardcopy certificates are available CPD 10 CPD hours / points Accredited by CPD Quality Standards Who is this course for? The Learning Disability Nursing course helps aspiring professionals who want to obtain the knowledge and familiarise themselves with the skillsets to pursue a career in Learning Disability Nursing. It is also great for professionals who are already working in Learning Disability Nursing and want to get promoted at work. Requirements To enrol in this Learning Disability Nursing course, all you need is a basic understanding of the English Language and an internet connection. Career path The Learning Disability Nursing course will enhance your knowledge and improve your confidence in exploring opportunities in various sectors related to Learning Disability Nursing. Learning Disability Nurse: £24,907 to £37,890 per year Senior Learning Disability Nurse: £35,000 to £48,000 per year Learning Disability Nurse Practitioner: £40,000 to £55,000 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

Machine Learning and other AI: Are You Ready? Machine Learning is the latest 'hot' title in computing and Artificial Intelligence. It sounds new but is influencing your life already. Machine Learning and AI will affect more and more of your life as they mature and more enabling technologies intersect with them. Machine Learning will change many disciplines and careers, overcoming scale issues, enabling better knowledge and insights, and augmenting many professions. Are you ready? This and other IIL Learning in Minutes presentations qualify for PDUs. Some titles, such as Agile-related topics may qualify for other continuing education credits such as SEUs, or CEUs. Each professional development activity yields one PDU for one hour spent engaged in the activity. Some limitations apply and can be found in the Ways to Earn PDUs section that discusses PDU activities and associated policies. Fractions of PDUs may also be reported. The smallest increment of a PDU that can be reported is 0.25. This means that if you spent 15 minutes participating in a qualifying PDU activity, you may report 0.25 PDU. If you spend 30 minutes in a qualifying PDU activity, you may report 0.50 PDU.

Duration 3 Days 18 CPD hours This course is intended for This course is geared for attendees with Intermediate IT skills who wish to learn Computer Vision with tensor flow 2 Overview This 'skills-centric' course is about 50% hands-on lab and 50% lecture, with extensive practical exercises designed to reinforce fundamental skills, concepts and best practices taught throughout the course. Working in a hands-on learning environment, led by our Computer Vision expert instructor, students will learn about and explore how to Build, train, and serve your own deep neural networks with TensorFlow 2 and Keras Apply modern solutions to a wide range of applications such as object detection and video analysis Run your models on mobile devices and web pages and improve their performance. Create your own neural networks from scratch Classify images with modern architectures including Inception and ResNet Detect and segment objects in images with YOLO, Mask R-CNN, and U-Net Tackle problems faced when developing self-driving cars and facial emotion recognition systems Boost your application's performance with transfer learning, GANs, and domain adaptation Use recurrent neural networks (RNNs) for video analysis Optimize and deploy your networks on mobile devices and in the browser Computer vision solutions are becoming increasingly common, making their way into fields such as health, automobile, social media, and robotics. Hands-On Computervision with TensorFlow 2 is a hands-on course that thoroughly explores TensorFlow 2, the brandnew version of Google's open source framework for machine learning. You will understand how to benefit from using convolutional neural networks (CNNs) for visual tasks. This course begins with the fundamentals of computer vision and deep learning, teaching you how to build a neural network from scratch. You will discover the features that have made TensorFlow the most widely used AI library, along with its intuitive Keras interface. You'll then move on to building, training, and deploying CNNs efficiently. Complete with concrete code examples, the course demonstrates how to classify images with modern solutions, such as Inception and ResNet, and extract specific content using You Only Look Once (YOLO), Mask R-CNN, and U-Net. You will also build generative dversarial networks (GANs) and variational autoencoders (VAEs) to create and edit images, and long short-term memory networks (LSTMs) to analyze videos. In the process, you will acquire advanced insights into transfer learning, data augmentation, domain adaptation, and mobile and web deployment, among other key concepts Computer Vision and Neural Networks Computer Vision and Neural Networks Technical requirements Computer vision in the wild A brief history of computer vision Getting started with neural networks TensorFlow Basics and Training a Model TensorFlow Basics and Training a Model Technical requirements Getting started with TensorFlow 2 and Keras TensorFlow 2 and Keras in detail The TensorFlow ecosystem Modern Neural Networks Modern Neural Networks Technical requirements Discovering convolutional neural networks Refining the training process Influential Classification Tools Influential Classification Tools Technical requirements Understanding advanced CNN architectures Leveraging transfer learning Object Detection Models Object Detection Models Technical requirements Introducing object detection A fast object detection algorithm YOLO Faster R-CNN ? a powerful object detection model Enhancing and Segmenting Images Enhancing and Segmenting Images Technical requirements Transforming images with encoders-decoders Understanding semantic segmentation Training on Complex and Scarce Datasets Training on Complex and Scarce Datasets Technical requirements Efficient data serving How to deal with data scarcity Video and Recurrent Neural Networks Video and Recurrent Neural Networks Technical requirements Introducing RNNs Classifying videos Optimizing Models and Deploying on Mobile Devices Optimizing Models and Deploying on Mobile Devices Technical requirements Optimizing computational and disk footprints On-device machine learning Example app ? recognizing facial expressions

Duration 3 Days 18 CPD hours This course is intended for This course is geared for experienced Scala developers who are new to the world of machine learning and are eager to expand their skillset. Professionals such as data engineers, data scientists, and software engineers who want to harness the power of machine learning in their Scala-based projects will greatly benefit from attending. Additionally, team leads and technical managers who oversee Scala development projects and want to integrate machine learning capabilities into their workflows can gain valuable insights from this course Overview Working in a hands-on learning environment led by our expert instructor you'll: Grasp the fundamentals of machine learning and its various categories, empowering you to make informed decisions about which techniques to apply in different situations. Master the use of Scala-specific tools and libraries, such as Breeze, Saddle, and DeepLearning.scala, allowing you to efficiently process, analyze, and visualize data for machine learning projects. Develop a strong understanding of supervised and unsupervised learning algorithms, enabling you to confidently choose the right approach for your data and effectively build predictive models Gain hands-on experience with neural networks and deep learning, equipping you with the know-how to create advanced applications in areas like natural language processing and image recognition. Explore the world of generative AI and learn how to utilize GPT-Scala for creative text generation tasks, broadening your skill set and making you a more versatile developer. Conquer the realm of scalable machine learning with Scala, learning the secrets to tackling large-scale data processing and analysis challenges with ease. Sharpen your skills in model evaluation, validation, and optimization, ensuring that your machine learning models perform reliably and effectively in any situation. Machine Learning Essentials for Scala Developers is a three-day course designed to provide a solid introduction to the world of machine learning using the Scala language. Throughout the hands-on course, you?ll explore a range of machine learning algorithms and techniques, from supervised and unsupervised learning to neural networks and deep learning, all specifically crafted for Scala developers. Our expert trainer will guide you through real-world, focused hands-on labs designed to help you apply the knowledge you gain in real-world scenarios, giving you the confidence to tackle machine learning challenges in your own projects. You'll dive into innovative tools and libraries such as Breeze, Saddle, DeepLearning.scala, GPT-Scala (and Generative AI with Scala), and TensorFlow-Scala. These cutting-edge resources will enable you to build and deploy machine learning models for a wide range of projects, including data analysis, natural language processing, image recognition and more. Upon completing this course, you'll have the skills required to tackle complex projects and confidently develop intelligent applications. You?ll be able to drive business outcomes, optimize processes, and contribute to innovative projects that leverage the power of data-driven insights and predictions. Introduction to Machine Learning and Scala Learning Outcome: Understand the fundamentals of machine learning and Scala's role in this domain. What is Machine Learning? Machine Learning with Scala: Advantages and Use Cases Supervised Learning in Scala Learn the basics of supervised learning and how to apply it using Scala. Supervised Learning: Regression and Classification Linear Regression in Scala Logistic Regression in Scala Unsupervised Learning in Scala Understand unsupervised learning and how to apply it using Scala. Unsupervised Learning:Clustering and Dimensionality Reduction K-means Clustering in Scala Principal Component Analysis in Scala Neural Networks and Deep Learning in Scala Learning Outcome: Learn the basics of neural networks and deep learning with a focus on implementing them in Scala. Introduction to Neural Networks Feedforward Neural Networks in Scala Deep Learning and Convolutional Neural Networks Introduction to Generative AI and GPT in Scala Gain a basic understanding of generative AI and GPT, and how to utilize GPT-Scala for natural language tasks. Generative AI: Overview and Use Cases Introduction to GPT (Generative Pre-trained Transformer) GPT-Scala: A Library for GPT in Scala Reinforcement Learning in Scala Understand the basics of reinforcement learning and its implementation in Scala. Introduction to Reinforcement Learning Q-learning and Value Iteration Reinforcement Learning with Scala Time Series Analysis using Scala Learn time series analysis techniques and how to apply them in Scala. Introduction to Time Series Analysis Autoregressive Integrated Moving Average (ARIMA) Models Time Series Analysis in Scala Natural Language Processing (NLP) with Scala Gain an understanding of natural language processing techniques and their application in Scala. Introduction to NLP: Techniques and Applications Text Processing and Feature Extraction NLP Libraries and Tools for Scala Image Processing and Computer Vision with Scala Learn image processing techniques and computer vision concepts with a focus on implementing them in Scala. Introduction to Image Processing and Computer Vision Feature Extraction and Image Classification Image Processing Libraries for Scala Model Evaluation and Validation Understand the importance of model evaluation and validation, and how to apply these concepts using Scala. Model Evaluation Metrics Cross-Validation Techniques Model Selection and Tuning in Scala Scalable Machine Learning with Scala Learn how to handle large-scale machine learning problems using Scala. Challenges of Large-Scale Machine Learning Data Partitioning and Parallelization Distributed Machine Learning with Scala Machine Learning Deployment and Production Understand the process of deploying machine learning models into production using Scala. Deployment Challenges and Best Practices Model Serialization and Deserialization Monitoring and Updating Models in Production Ensemble Learning Techniques in Scala Discover ensemble learning techniques and their implementation in Scala. Introduction to Ensemble Learning Bagging and Boosting Techniques Implementing Ensemble Models in Scala Feature Engineering for Machine Learning in Scala Learn advanced feature engineering techniques to improve machine learning model performance in Scala. Importance of Feature Engineering in Machine Learning Feature Scaling and Normalization Techniques Handling Missing Data and Categorical Features Advanced Optimization Techniques for Machine Learning Understand advanced optimization techniques for machine learning models and their application in Scala. Gradient Descent and Variants Regularization Techniques (L1 and L2) Hyperparameter Tuning Strategies