126 Learning To Learn courses

OVERVIEW This comprehensive course on Speed Learning Training will deepen your understanding on this topic. After successful completion of this course you can acquire the required skills in this sector. This Speed Learning Training comes with accredited certification from CPD, which will enhance your CV and make you worthy in the job market. So enrol in this course today to fast track your career ladder. HOW WILL I GET MY CERTIFICATE? You may have to take a quiz or a written test online during or after the course. After successfully completing the course, you will be eligible for the certificate. WHO IS THIS COURSE FOR? There is no experience or previous qualifications required for enrolment on this Speed Learning Training. It is available to all students, of all academic backgrounds. REQUIREMENTS Our Speed Learning Training is fully compatible with PC's, Mac's, Laptop, Tablet and Smartphone devices. This course has been designed to be fully compatible with tablets and smartphones so you can access your course on Wi-Fi, 3G or 4G. There is no time limit for completing this course, it can be studied in your own time at your own pace. CAREER PATH Learning this new skill will help you to advance in your career. It will diversify your job options and help you develop new techniques to keep up with the fast-changing world. This skillset will help you to- * Open doors of opportunities * Increase your adaptability * Keep you relevant * Boost confidence And much more! COURSE CURRICULUM 1 sections • 12 lectures • 00:52:00 total length •Course Promo: 00:03:00 •Lesson 01: Introduction: 00:02:00 •Lesson 02: Skill, Learning, and Acquisition: 00:09:00 •Lesson 03: Smart Learners and Efficient Learning: 00:04:00 •Lesson 04: 10 Remarkable Traits of Successful Learners: 00:04:00 •Lesson 05: Learning Styles to Help You Learn Faster and Smarter: 00:04:00 •Lesson 06: 10 Tactics on Increasing Brain Power, Memory, and Motivation to Learn Better: 00:08:00 •Lesson 07: 8 Powerful Learning Hacks to Boost Your Learning Ability: 00:05:00 •Lesson 08: 5 Hacks to Speed up the Learning Process: 00:03:00 •Lesson 09: 8 Ways to Train Your Brain to Learn Faster and Remember More: 00:04:00 •Lesson 10: Simple Brain Training Habits to Boost Your Brain Power: 00:05:00 •Lesson 11: Conclusion - Final Thoughts & Ideas: 00:01:00

OVERVIEW This comprehensive course on Machine Learning for Predictive Maps in Python and Leaflet will deepen your understanding on this topic. After successful completion of this course you can acquire the required skills in this sector. This Machine Learning for Predictive Maps in Python and Leaflet comes with accredited certification from CPD, which will enhance your CV and make you worthy in the job market. So enrol in this course today to fast track your career ladder. HOW WILL I GET MY CERTIFICATE? You may have to take a quiz or a written test online during or after the course. After successfully completing the course, you will be eligible for the certificate. WHO IS THIS COURSE FOR? There is no experience or previous qualifications required for enrolment on this Machine Learning for Predictive Maps in Python and Leaflet. It is available to all students, of all academic backgrounds. REQUIREMENTS Our Machine Learning for Predictive Maps in Python and Leaflet is fully compatible with PC's, Mac's, Laptop, Tablet and Smartphone devices. This course has been designed to be fully compatible with tablets and smartphones so you can access your course on Wi-Fi, 3G or 4G. There is no time limit for completing this course, it can be studied in your own time at your own pace. CAREER PATH Learning this new skill will help you to advance in your career. It will diversify your job options and help you develop new techniques to keep up with the fast-changing world. This skillset will help you to- * Open doors of opportunities * Increase your adaptability * Keep you relevant * Boost confidence And much more! COURSE CURRICULUM 9 sections • 33 lectures • 05:59:00 total length •Introduction: 00:10:00 •Python Installation: 00:04:00 •Creating a Python Virtual Environment: 00:07:00 •Installing Django: 00:09:00 •Installing Visual Studio Code IDE: 00:06:00 •Installing PostgreSQL Database Server Part 1: 00:03:00 •Installing PostgreSQL Database Server Part 2: 00:09:00 •Adding the settings.py Code: 00:07:00 •Creating a Django Model: 00:10:00 •Adding the admin.py Code: 00:21:00 •Creating Template Files: 00:10:00 •Creating Django Views: 00:10:00 •Creating URL Patterns for the REST API: 00:09:00 •Adding the index.html code: 00:04:00 •Adding the layout.html code: 00:19:00 •Creating our First Map: 00:10:00 •Adding Markers: 00:16:00 •Installing Jupyter Notebook: 00:07:00 •Data Pre-processing: 00:31:00 •Model Selection: 00:20:00 •Model Evaluation and Building a Prediction Dataset: 00:11:00 •Creating a Django Model: 00:04:00 •Embedding the Machine Learning Pipeline in the Application: 00:42:00 •Creating a URL Endpoint for our Prediction Dataset: 00:06:00 •Creating Multiple Basemaps: 00:09:00 •Creating the Marker Layer Group: 00:10:00 •Creating the Point Layer Group: 00:12:00 •Creating the Predicted Point Layer Group: 00:07:00 •Creating the Predicted High Risk Point Layer Group: 00:12:00 •Creating the Legend: 00:09:00 •Creating the Prediction Score Legend: 00:15:00 •Resource: 00:00:00 •Assignment - Machine Learning for Predictive Maps in Python and Leaflet: 00:00:00

OVERVIEW Learning difficulties can provide consistent obstacles for many individuals, but you can help them to overcome their challenges. This Understanding Learning Difficulties Level 3 course is a unique way to gain awareness and understanding of the conditions that hinder the education of people of all ages. When you complete the course, you will be able to identify disorders such as ADHD, Dyslexia, ADD, Dyscalculia, and more. This knowledge will enable you to recognise the issues that slow the learning process, thereby allowing you to adapt and support each person according to their specific needs. Give students a helping hand and enrol now. HOW WILL I GET MY CERTIFICATE? At the end of the course there will be a written assignment test which you can take either during or after the course. After successfully completing the test you will be able to order your certificate, these are included in the price. WHO IS THIS COURSE FOR? There is no experience or previous qualifications required for enrolment on this Understanding Learning Difficulties Level 3. It is available to all students, of all academic backgrounds. REQUIREMENTS Our Understanding Learning Difficulties Level 3 is fully compatible with PC's, Mac's, Laptop, Tablet and Smartphone devices. This course has been designed to be fully compatible on tablets and smartphones so you can access your course on wifi, 3G or 4G. There is no time limit for completing this course, it can be studied in your own time at your own pace. CAREER PATH Having these various qualifications will increase the value in your CV and open you up to multiple sectors such as Business & Management , Admin, Accountancy & Finance, Secretarial & PA, Teaching & Mentoring etc. COURSE CURRICULUM 9 sections • 9 lectures • 04:20:00 total length •Module 01: Learning Support Assistant: Workplace & Works: 00:30:00 •Module 02: Teaching Methodologies: 00:30:00 •Module 03: Skills of A Learning Support Assistant: 00:20:00 •Module 04: The Role and Responsibilities of the Learning Support Assistant: 00:20:00 •Module 05: SEN Teaching: 01:00:00 •Module 06: Supporting Pupils with Special Needs (Part 01): 00:30:00 •Module 07: How to Support Pupils with Special Needs Part-2: 00:50:00 •Module 08 Safeguarding Children and Young People: 00:20:00 •Assignment - Understanding Learning Difficulties Level 3: 00:00:00

Our extensive Learning & Development course is developed thoroughly for you to indulge and learn all the topics with utmost clarity and thorough explanation. Thiscourse includes not only one course but THREE courses within the bundle. So you are getting two extra courses for the price of one, no extra money! Our course aims to provide detailed insight into the Learning & Development with full support from our teachers. So if you are looking for a convenient way to boost your knowledge further of the Learning & Development topic but are too busy to go to a class, then enrol in this course and you are sorted! Our in-depth course has no time limit and can be accessed from anywhere in the world. You'll pick up a ton of fresh information, whether you're a novice or an advanced. The mega course's sheer size and breadth speak for itself! So, do not delay any further; we are excited and looking forward to letting you in our CPD Accredited course as much as you are! The following courses will not only fast-track your career but also make it even more rewarding: * Course 01: Learning Support Assistant * Course 02: Career Development and Passion * Course 03: Personal Development Coach with Positive Psychology Training Learning Outcome From this interactivecourse, you will be able to: * Deep dive into the basics of Learning & Development. * Learn how to improve your skills in general. * Increase your ability to reason and solve problems. * Utilise the Learning & Development to boost output. * Gain confidence and clarity in your communication. * Explore different career routes in this field. This comprehensive three-in-one Learning & Development course equips you with critical guidance, methods, and strategies for increasing both employee and professional development. The Learning & Development course from Next Generation's easy-to-digest and deliverable modules will provide you with the most essential and useful knowledge for growing your profession, from setting personal development goals to forming a cross-functional team. You may use the knowledge you've gained in this extensive course package in your everyday life. You may take this self-paced online course from the convenience of your home. Our courses are well-researched and created by trainers with exceptional skills. The program will enhance your competence in the field you choose to pursue. The interactive lessons in the course are straightforwardly designed, so understanding them won't be difficult. Show off your new skills with a certificate of completion Once you complete the Learning & Development course, you will be eligible to request a digital certificate for free. For Printed Transcript & Hardcopy Certificate- * 4.99 GBP (Inside the UK Postal Fee) * 8.99 GBP (International Delivery Fee) CPD 30 CPD hours / points Accredited by CPD Quality Standards WHO IS THIS COURSE FOR? This comprehensive three-in-one bundled Learning & Development course has no restrictions for people registering for it. Anyone between the age of above sixteen can apply for the course. So whether you are an eager learner to explore the deeper unknown facts of the subject or a skilled individual in this field who wishes to enhance their career prospects further can take this course. REQUIREMENTS No previous knowledge of the Learning & Development is required to enrol in this training. CAREER PATH The aim of this exclusive bundle Learning & Development course is to help you toward your dream career. So, complete this course and enhance your skills to explore opportunities in relevant areas.

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