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Quality Guarantee: Promising training excellence, satisfaction gurantee Accredited by: CPD UK & Quality License Scheme Tutor Support: Unlimited support via email, till you complete the course Recognised Certification: Accepted by thousands of professional bodies Start Anytime: With 1 year access to the course materials Online Learning: Learn from anywhere, whenever you want Why NLP Training Course right for you? Whether you are self-taught and you want to fill in the gaps for better efficiency and productivity, this NLP Training Course will set you up with a solid foundation to become a confident NLP Training and develop more advanced skills. This comprehensive course is the perfect way to kickstart your career in the field of NLP Training. This course will give you a competitive advantage in your career, making you stand out from all other applicants and employees. As one of the leading course providers and most renowned e-learning specialists online, we're dedicated to giving you the best educational experience possible. This course is crafted by industry expert, to enable you to learn quickly and efficiently, and at your own pace and convenience. NLP Training Course Details Accredited by International Practitioners of Holistic Medicine (IPHM) is a leading accredited organisation that certifies and regulates alternative therapists, healers, and training providers around the world. After completing the IPHM accredited course you will be eligible to apply for the insurance.   CPD certificates are accepted by thousands of professional bodies and government regulators here in the UK and around the world. Many organisations look for employees with CPD requirements, which means, that by doing this course, you would be a potential candidate in your respective field.   The Quality Licence Scheme is a brand of the Skills and Education Group, a leading national awarding organisation for providing high-quality vocational qualifications across a wide range of industries. Course Curriculum Module 01: Nlp Training Nlp Lesson 1 - Introduction, Cause and Effect Nlp Lesson 2 - the Map is Not the Territory Nlp Lesson 3 - Sensory Acuity Nlp Lesson 4 - Rapport Nlp Lesson 5 - Representational Systems Nlp Lesson 6 - Anchoring Nlp Lesson 7 - State Elicitation Nlp Lesson 8 - Language Patterns Nlp Lesson 9 - Language Patterns 2 Nlp Lesson 10 - Chunking Module 02: Nlp Training Nlp Lesson 11 - Frames & Reframing Nlp Lesson 12 - Reframing Nlp Lesson 13 - Strategies Nlp Lesson 14 - Meta Programs Nlp Lesson 15 - Timelines Nlp Lesson 16 - Values Nlp Lesson 17 - Goalsetting Nlp Lesson 18 - Goalsetting 2 Nlp Lesson 19 - Models _ Applications Nlp Lesson 20 - Satir Categories Nlp Lesson 21 - Emotional Intelligence Who should take this course? This comprehensive course is suitable for anyone looking to improve their job prospects or aspiring to accelerate their career in this sector and want to gain in-depth knowledge of NLP Training. Entry Requirements There are no academic entry requirements for this course, and it is open to students of all academic backgrounds. As long as you are aged seventeen or over and have a basic grasp of English, numeracy and ICT, you will be eligible to enrol. Assessment Method On successful completion of the course, you will be required to sit an online multiple-choice assessment. The assessment will be evaluated automatically and the results will be given to you immediately. Certification Endorsed Certificate from Quality Licence Scheme After successfully passing the MCQ exam you will be eligible to order the Endorsed Certificate by Quality Licence Scheme. The Quality Licence Scheme is a brand of the Skills and Education Group, a leading national awarding organisation for providing high-quality vocational qualifications across a wide range of industries. It will give you a competitive advantage in your career, making you stand out from all other applicants and employees. There is a Quality Licence Scheme endorsement fee to obtain an endorsed certificate which is £65. Certificate of Achievement from Lead Academy After successfully passing the MCQ exam you will be eligible to order your certificate of achievement as proof of your new skill. The certificate of achievement is an official credential that confirms that you successfully finished a course with Lead Academy. Certificate can be obtained in PDF version at a cost of £12, and there is an additional fee to obtain a printed copy certificate which is £35. FAQs Is CPD a recognised qualification in the UK? CPD is globally recognised by employers, professional organisations and academic intuitions, thus a certificate from CPD Certification Service creates value towards your professional goal and achievement. CPD-certified certificates are accepted by thousands of professional bodies and government regulators here in the UK and around the world. Are QLS courses recognised? Although QLS courses are not subject to Ofqual regulation, they must adhere to an extremely high level that is set and regulated independently across the globe. A course that has been approved by the Quality Licence Scheme simply indicates that it has been examined and evaluated in terms of quality and fulfils the predetermined quality standards. When will I receive my certificate? For CPD accredited PDF certificate it will take 24 hours, however for the hardcopy CPD certificate takes 5-7 business days and for the Quality License Scheme certificate it will take 7-9 business days. Can I pay by invoice? Yes, you can pay via Invoice or Purchase Order, please contact us at info@lead-academy.org for invoice payment. Can I pay via instalment? Yes, you can pay via instalments at checkout. How to take online classes from home? Our platform provides easy and comfortable access for all learners; all you need is a stable internet connection and a device such as a laptop, desktop PC, tablet, or mobile phone. The learning site is accessible 24/7, allowing you to take the course at your own pace while relaxing in the privacy of your home or workplace. Does age matter in online learning? No, there is no age limit for online learning. Online learning is accessible to people of all ages and requires no age-specific criteria to pursue a course of interest. As opposed to degrees pursued at university, online courses are designed to break the barriers of age limitation that aim to limit the learner's ability to learn new things, diversify their skills, and expand their horizons. When I will get the login details for my course? After successfully purchasing the course, you will receive an email within 24 hours with the login details of your course. Kindly check your inbox, junk or spam folder, or you can contact our client success team via info@lead-academy.org

Don't let your emotions rule your life- live like a proactive person. Learn 'What is Counselling & Psychotherapy', 'Treatment by DBT', 'DBT for Psychological Disorders'.

A comprehensive, simple, visual guide and a super-easy course using SAS with no installation on your computer necessary. This course uses the latest SAS Studio offered through SAS OnDemand and it's completely free. 12+ hours of knowledge-packed lectures, videos, quiz questions, followed by two practical and hands-on guided exercises and projects.

Dive into the heart of Big Data Infrastructure, exploring storage systems, distributed file frameworks, and processing paradigms. This course provides a comprehensive understanding of key components like HDFS, Apache Spark, and Cassandra, offering insights into their architecture, use cases, and real-world applications. This course is a deep dive into the complex landscape of Big Data Infrastructure. From unravelling the architecture of Apache Spark to dissecting the benefits of distributed file systems, participants gain expertise in assessing, comparing, and implementing various Big Data storage and processing systems. Scalability, fault-tolerance, and industry-specific case studies add practical depth to theoretical knowledge. After the successful completion of this course, you will be able to: Understand the Components of Big Data Infrastructure, Including Storage Systems, Distributed File Systems, and Processing Frameworks. Identify the Characteristics and Benefits of Distributed File Systems Such as Hadoop Distributed File System (H.D.F.S). Describe the Architecture and Capabilities of Apache Spark and its Role in Big Data Processing. Recognise the Use Cases and Benefits of Apache Cassandra as a Distributed N..O.S.Q.L Database. Compare and Contrast Different Big Data Storage and Processing Systems Such as Hadoop, Spark, and Cassandra. Understand the Scalability and Fault-tolerance Mechanisms Used in Big Data Infrastructure, Such as Sharding and Replication. Appreciate the Challenges Associated with Deploying and Managing Big Data Infrastructure, Such as Hardware and Software Configuration and Security Considerations. Explore the intricacies of Big Data Infrastructure, from understanding storage systems to unraveling the nuances of distributed file frameworks and processing engines. Gain a comprehensive view of scalability, fault-tolerance mechanisms, and industry-specific challenges through engaging case studies. Equip yourself to navigate the dynamic landscape of Big Data with confidence and expertise. VIDEO - Course Structure and Assessment Guidelines Watch this video to gain further insight. Navigating the MSBM Study Portal Watch this video to gain further insight. Interacting with Lectures/Learning Components Watch this video to gain further insight. Big Data Infrastructure Self-paced pre-recorded learning content on this topic. Big Data Infrastructure Put your knowledge to the test with this quiz. Read each question carefully and choose the response that you feel is correct. All MSBM courses are accredited by the relevant partners and awarding bodies. Please refer to MSBM accreditation in about us for more details. There are no strict entry requirements for this course. Work experience will be an added advantage to understanding the content of the course. The certificate is designed to enhance the learner's knowledge in the field. This certificate is for everyone who is eager to know more and get updated on current ideas in their respective field. We recommend this certificate for the following audience. Big Data Infrastructure Engineer Hadoop Administrator Spark Developer Cassandra Database Administrator Big Data Solutions Architect Data Infrastructure Manager NoSQL Database Analyst Big Data Consultant Average Completion Time 2 Weeks Accreditation 3 CPD Hours Level Advanced Start Time Anytime 100% Online Study online with ease. Unlimited Access 24/7 unlimited access with pre-recorded lectures. Low Fees Our fees are low and easy to pay online.

Understand how Docker works and learn its core features with this hands-on course. This is 90% practice without any useless demos! Learn how to create different containers such as Node.js, Python, WordPress, MongoDB, MySQL, Redis, Elasticsearch, and much more.

Overview This Deep Learning & Neural Networks Python - Keras: For Dummies course will unlock your full potential and will show you how to excel in a career in Deep Learning & Neural Networks Python - Keras: For Dummies. So upskill now and reach your full potential. Everything you need to get started in Deep Learning & Neural Networks Python - Keras: For Dummies is available in this course. Learning and progressing are the hallmarks of personal development. This Deep Learning & Neural Networks Python - Keras: For Dummies will quickly teach you the must-have skills needed to start in the relevant industry. In This Deep Learning & Neural Networks Python - Keras: For Dummies Course, You Will: Learn strategies to boost your workplace efficiency. Hone your Deep Learning & Neural Networks Python - Keras: For Dummies skills to help you advance your career. Acquire a comprehensive understanding of various Deep Learning & Neural Networks Python - Keras: For Dummies topics and tips from industry experts. Learn in-demand Deep Learning & Neural Networks Python - Keras: For Dummies skills that are in high demand among UK employers, which will help you to kickstart your career. This Deep Learning & Neural Networks Python - Keras: For Dummies course covers everything you must know to stand against the tough competition in the Deep Learning & Neural Networks Python - Keras: For Dummies field.  The future is truly yours to seize with this Deep Learning & Neural Networks Python - Keras: For Dummies. Enrol today and complete the course to achieve a Deep Learning & Neural Networks Python - Keras: For Dummies certificate that can change your professional career forever. Additional Perks of Buying a Course From Institute of Mental Health Study online - whenever and wherever you want. One-to-one support from a dedicated tutor throughout your course. Certificate immediately upon course completion 100% Money back guarantee Exclusive discounts on your next course purchase from Institute of Mental Health Enrolling in the Deep Learning & Neural Networks Python - Keras: For Dummies course can assist you in getting into your desired career quicker than you ever imagined. So without further ado, start now. Process of Evaluation After studying the Deep Learning & Neural Networks Python - Keras: For Dummies course, your skills and knowledge will be tested with a MCQ exam or assignment. You must get a score of 60% to pass the test and get your certificate.  Certificate of Achievement Upon successfully completing the Deep Learning & Neural Networks Python - Keras: For Dummies course, you will get your CPD accredited digital certificate immediately. And you can also claim the hardcopy certificate completely free of charge. All you have to do is pay a shipping charge of just £3.99. Who Is This Course for? This Deep Learning & Neural Networks Python - Keras: For Dummies is suitable for anyone aspiring to start a career in Deep Learning & Neural Networks Python - Keras: For Dummies; even if you are new to this and have no prior knowledge on Deep Learning & Neural Networks Python - Keras: For Dummies, this course is going to be very easy for you to understand.  And if you are already working in the Deep Learning & Neural Networks Python - Keras: For Dummies field, this course will be a great source of knowledge for you to improve your existing skills and take them to the next level.  Taking this Deep Learning & Neural Networks Python - Keras: For Dummies course is a win-win for you in all aspects.  This course has been developed with maximum flexibility and accessibility, making it ideal for people who don't have the time to devote to traditional education. Requirements This Deep Learning & Neural Networks Python - Keras: For Dummies course has no prerequisite.  You don't need any educational qualification or experience to enrol in the Deep Learning & Neural Networks Python - Keras: For Dummies course. Do note: you must be at least 16 years old to enrol. Any internet-connected device, such as a computer, tablet, or smartphone, can access this online Deep Learning & Neural Networks Python - Keras: For Dummies course. Moreover, this course allows you to learn at your own pace while developing transferable and marketable skills. Course Curriculum Course Introduction and Table of Contents Course Introduction and Table of Contents 00:11:00 Deep Learning Overview Deep Learning Overview - Theory Session - Part 1 00:06:00 Deep Learning Overview - Theory Session - Part 2 00:07:00 Choosing Between ML or DL for the next AI project - Quick Theory Session Choosing Between ML or DL for the next AI project - Quick Theory Session 00:09:00 Preparing Your Computer Preparing Your Computer - Part 1 00:07:00 Preparing Your Computer - Part 2 00:06:00 Python Basics Python Basics - Assignment 00:09:00 Python Basics - Flow Control 00:09:00 Python Basics - Functions 00:04:00 Python Basics - Data Structures 00:12:00 Theano Library Installation and Sample Program to Test Theano Library Installation and Sample Program to Test 00:11:00 TensorFlow library Installation and Sample Program to Test TensorFlow library Installation and Sample Program to Test 00:09:00 Keras Installation and Switching Theano and TensorFlow Backends Keras Installation and Switching Theano and TensorFlow Backends 00:10:00 Explaining Multi-Layer Perceptron Concepts Explaining Multi-Layer Perceptron Concepts 00:03:00 Explaining Neural Networks Steps and Terminology Explaining Neural Networks Steps and Terminology 00:10:00 First Neural Network with Keras - Understanding Pima Indian Diabetes Dataset First Neural Network with Keras - Understanding Pima Indian Diabetes Dataset 00:07:00 Explaining Training and Evaluation Concepts Explaining Training and Evaluation Concepts 00:11:00 Pima Indian Model - Steps Explained Pima Indian Model - Steps Explained - Part 1 00:09:00 Pima Indian Model - Steps Explained - Part 2 00:07:00 Coding the Pima Indian Model Coding the Pima Indian Model - Part 1 00:11:00 Coding the Pima Indian Model - Part 2 00:09:00 Pima Indian Model - Performance Evaluation Pima Indian Model - Performance Evaluation - Automatic Verification 00:06:00 Pima Indian Model - Performance Evaluation - Manual Verification 00:08:00 Pima Indian Model - Performance Evaluation - k-fold Validation - Keras Pima Indian Model - Performance Evaluation - k-fold Validation - Keras 00:10:00 Pima Indian Model - Performance Evaluation - Hyper Parameters Pima Indian Model - Performance Evaluation - Hyper Parameters 00:12:00 Understanding Iris Flower Multi-Class Dataset Understanding Iris Flower Multi-Class Dataset 00:08:00 Developing the Iris Flower Multi-Class Model Developing the Iris Flower Multi-Class Model - Part 1 00:09:00 Developing the Iris Flower Multi-Class Model - Part 2 00:06:00 Developing the Iris Flower Multi-Class Model - Part 3 00:09:00 Understanding the Sonar Returns Dataset Understanding the Sonar Returns Dataset 00:07:00 Developing the Sonar Returns Model Developing the Sonar Returns Model 00:10:00 Sonar Performance Improvement - Data Preparation - Standardization Sonar Performance Improvement - Data Preparation - Standardization 00:15:00 Sonar Performance Improvement - Layer Tuning for Smaller Network Sonar Performance Improvement - Layer Tuning for Smaller Network 00:07:00 Sonar Performance Improvement - Layer Tuning for Larger Network Sonar Performance Improvement - Layer Tuning for Larger Network 00:06:00 Understanding the Boston Housing Regression Dataset Understanding the Boston Housing Regression Dataset 00:07:00 Developing the Boston Housing Baseline Model Developing the Boston Housing Baseline Model 00:08:00 Boston Performance Improvement by Standardization Boston Performance Improvement by Standardization 00:07:00 Boston Performance Improvement by Deeper Network Tuning Boston Performance Improvement by Deeper Network Tuning 00:05:00 Boston Performance Improvement by Wider Network Tuning Boston Performance Improvement by Wider Network Tuning 00:04:00 Save & Load the Trained Model as JSON File (Pima Indian Dataset) Save & Load the Trained Model as JSON File (Pima Indian Dataset) - Part 1 00:09:00 Save & Load the Trained Model as JSON File (Pima Indian Dataset) - Part 2 00:08:00 Save and Load Model as YAML File - Pima Indian Dataset Save and Load Model as YAML File - Pima Indian Dataset 00:05:00 Load and Predict using the Pima Indian Diabetes Model Load and Predict using the Pima Indian Diabetes Model 00:09:00 Load and Predict using the Iris Flower Multi-Class Model Load and Predict using the Iris Flower Multi-Class Model 00:08:00 Load and Predict using the Sonar Returns Model Load and Predict using the Sonar Returns Model 00:10:00 Load and Predict using the Boston Housing Regression Model Load and Predict using the Boston Housing Regression Model 00:08:00 An Introduction to Checkpointing An Introduction to Checkpointing 00:06:00 Checkpoint Neural Network Model Improvements Checkpoint Neural Network Model Improvements 00:10:00 Checkpoint Neural Network Best Model Checkpoint Neural Network Best Model 00:04:00 Loading the Saved Checkpoint Loading the Saved Checkpoint 00:05:00 Plotting Model Behavior History Plotting Model Behavior History - Introduction 00:06:00 Plotting Model Behavior History - Coding 00:08:00 Dropout Regularization - Visible Layer Dropout Regularization - Visible Layer - Part 1 00:11:00 Dropout Regularization - Visible Layer - Part 2 00:06:00 Dropout Regularization - Hidden Layer Dropout Regularization - Hidden Layer 00:06:00 Learning Rate Schedule using Ionosphere Dataset - Intro Learning Rate Schedule using Ionosphere Dataset 00:06:00 Time Based Learning Rate Schedule Time Based Learning Rate Schedule - Part 1 00:07:00 Time Based Learning Rate Schedule - Part 2 00:12:00 Drop Based Learning Rate Schedule Drop Based Learning Rate Schedule - Part 1 00:07:00 Drop Based Learning Rate Schedule - Part 2 00:08:00 Convolutional Neural Networks - Introduction Convolutional Neural Networks - Part 1 00:11:00 Convolutional Neural Networks - Part 2 00:06:00 MNIST Handwritten Digit Recognition Dataset Introduction to MNIST Handwritten Digit Recognition Dataset 00:06:00 Downloading and Testing MNIST Handwritten Digit Recognition Dataset 00:10:00 MNIST Multi-Layer Perceptron Model Development MNIST Multi-Layer Perceptron Model Development - Part 1 00:11:00 MNIST Multi-Layer Perceptron Model Development - Part 2 00:06:00 Convolutional Neural Network Model using MNIST Convolutional Neural Network Model using MNIST - Part 1 00:13:00 Convolutional Neural Network Model using MNIST - Part 2 00:12:00 Large CNN using MNIST Large CNN using MNIST 00:09:00 Load and Predict using the MNIST CNN Model Load and Predict using the MNIST CNN Model 00:14:00 Introduction to Image Augmentation using Keras Introduction to Image Augmentation using Keras 00:11:00 Augmentation using Sample Wise Standardization Augmentation using Sample Wise Standardization 00:10:00 Augmentation using Feature Wise Standardization & ZCA Whitening Augmentation using Feature Wise Standardization & ZCA Whitening 00:04:00 Augmentation using Rotation and Flipping Augmentation using Rotation and Flipping 00:04:00 Saving Augmentation Saving Augmentation 00:05:00 CIFAR-10 Object Recognition Dataset - Understanding and Loading CIFAR-10 Object Recognition Dataset - Understanding and Loading 00:12:00 Simple CNN using CIFAR-10 Dataset Simple CNN using CIFAR-10 Dataset - Part 1 00:09:00 Simple CNN using CIFAR-10 Dataset - Part 2 00:06:00 Simple CNN using CIFAR-10 Dataset - Part 3 00:08:00 Train and Save CIFAR-10 Model Train and Save CIFAR-10 Model 00:08:00 Load and Predict using CIFAR-10 CNN Model Load and Predict using CIFAR-10 CNN Model 00:16:00 RECOMENDED READINGS Recomended Readings 00:00:00

[vc_row][vc_column][vc_column_text] Description: Dialectical Behaviour Therapy ( DBT) is a form of cognitive psychotherapy, designed to treat people with borderline personality disorders and mental health illnesses. DBT is often used to treat individuals who self-harm, abuse drugs or have suicidal tendencies. If you're considering a career in counselling, then you may want to consider this dialectical behaviour therapy training course. The Dialectical Behaviour Therapy (DBT) Diploma Course is an exploration of DBT theory and an introduction to the role of a DBT therapist. To begin with, you will explore the strategies of the DBT approach and DBT treatments, including interpersonal effectiveness and mindfulness practices. You will then move onto how to use psychotherapy, and DBT counselling approaches for solving common psychological disorders such as depression, anxiety and OCD. Finally, you will study the benefits and limitations of the DBT approach. Throughout this course, you will develop essential problem-solving and clinical skills to help you with your career advancement to becoming a fully qualified DBT practitioner. Who is the course for? Anyone who wants to work as a therapist or use therapy in work Anyone who is interested in counselling or psychotherapy Anyone who wants to learn DBT approach Entry Requirement: This course is available to all learners, of all academic backgrounds. Learners should be aged 16 or over to undertake the qualification. Good understanding of English language, numeracy and ICT are required to attend this course. Assessment: At the end of the course, you will be required to sit an online multiple-choice test. Your test will be assessed automatically and immediately so that you will instantly know whether you have been successful. Before sitting for your final exam, you will have the opportunity to test your proficiency with a mock exam. Certification: After completing and passing the course successfully, you will be able to obtain an Accredited Certificate of Achievement. Certificates can be obtained either in hard copy at a cost of £39 or in PDF format at a cost of £24. Why choose us? Affordable, engaging & high-quality e-learning study materials; Tutorial videos/materials from the industry leading experts; Study in a user-friendly, advanced online learning platform; Efficient exam systems for the assessment and instant result; The UK & internationally recognised accredited qualification; Access to course content on mobile, tablet or desktop from anywhere anytime; The benefit of career advancement opportunities; 24/7 student support via email. Career Path: After completing this course you will be able to build up accurate knowledge and skills with proper confidence to enrich yourself and brighten up your career in the relevant job market.[/vc_column_text][/vc_column][/vc_row] Introduction About the Instructor FREE 00:02:00 About the Course 00:06:00 What is Counselling & Psychotherapy Definition of Counselling 00:07:00 Counselling & Psychotherapy 00:07:00 Approaches in Counselling & Psychotherapy 00:12:00 About Dialectical Behaviour Therapy (DBT) What is DBT? 00:05:00 What is 'dialectical'? 00:06:00 History & Philosophy of DBT 00:06:00 DBT Strategies & 'Life Skills' What is 'Mindfulness' 00:08:00 What is 'Distress Tolerance' 00:10:00 What is 'Emotion regulation' 00:11:00 What is 'Interpersonal Effectiveness' 00:06:00 Treatment by DBT Multistage approach of DBT 00:11:00 The Stages of Treatment in DBT 00:06:00 Prioritising Treatments Targets 00:05:00 How to set up 'learning environment' for the client 00:07:00 How to conduct 'Behavioural Analysis' 00:11:00 DBT for Psychological Disorders Uses of DBT 00:03:00 DBT in the treatment of Borderline Personality Disorder 00:07:00 DBT in the treatment of Depression 00:09:00 DBT for treatment of Anxiety & OCD 00:08:00 DBT for treatment of 'Eating Disorders' 00:08:00 Effectiveness of DBT How effective is DBT? 00:07:00 Criticism and Limitations of DBT 00:05:00 Thank You and Good Bye! 00:04:00 Mock Exam Mock Exam - Dialectical Behaviour Therapy (DBT) Diploma 00:20:00 Final Exam Final Exam - Dialectical Behaviour Therapy (DBT) Diploma 00:20:00 Certificate and Transcript Order Your Certificates and Transcripts 00:00:00

Overview of Dialectical Behaviour Therapy (DBT) Course Many people suffer from extreme emotional pain and often hurt themselves on purpose. DBT is designed to help people cope with their mental suffering and self-injurious behaviour.  This Dialectical Behaviour Therapy (DBT) Course will teach you the DBT therapy techniques to help people with borderline personality disorders and other mental conditions. Training with us, you'll understand mindfulness in DBT and how to incorporate mindfulness in clinical settings. In addition, the modules will explain how emotions work and introduce you to the most essential tools in emotion regulation. You'll also learn about different communication types in DBT and the DBT interventions where people learn to manage distress in a healthy way. Finally, you'll discover the application of DBT in treating diverse patient populations. Course Preview Learning Outcomes Identify the core components of DBT Determine the role of mindfulness in DBT Understand what are emotion regulation skills in DBT Realise how DBT can improve communication outcomes Learn about the ethical and professional considerations in DBT practice Why Take This Course From John Academy? Affordable, well-structured and high-quality e-learning study materials Meticulously crafted engaging and informative tutorial videos and materials Efficient exam systems for the assessment and instant result Earn UK & internationally recognised accredited qualification Easily access the course content on mobile, tablet, or desktop from anywhere, anytime Excellent career advancement opportunities Get 24/7 student support via email Who Should Take this Dialectical Behaviour Therapy (DBT) Course? Whether you're an existing practitioner or an aspiring professional, this course is an ideal training opportunity. It will elevate your expertise and boost your CV with key skills and a recognised qualification attesting to your knowledge. Are There Any Entry Requirements? This Dialectical Behaviour Therapy (DBT) Course is available to all learners of all academic backgrounds. But learners should be aged 16 or over to undertake the qualification. And a good understanding of the English language, numeracy, and ICT will be helpful. Certificate of Achievement After completing this course successfully, you will be able to obtain an Accredited Certificate of Achievement. Certificates & Transcripts can be obtained either in Hardcopy at £14.99 or in PDF format at £11.99. Career Path​ Dialectical Behaviour Therapy (DBT) Course provides essential skills that will make you more effective in your role. It would be beneficial for any related profession in the industry, such as: Dialectal Behaviour Therapist Mental Health Assistant Human Service Caseworker Module 1: Introduction to DBT Introduction to DBT 00:19:00 Module 2: Mindfulness Skills Training Mindfulness Skills Training 00:20:00 Module 3: Emotion Regulation Skills Emotion Regulation Skills 00:19:00 Module 4: Interpersonal Effectiveness Skills Interpersonal Effectiveness Skills 00:16:00 Module 5: Distress Tolerance Skills Distress Tolerance Skills 00:26:00 Module 6: Application of DBT in Specific Populations Application of DBT in Specific Populations 00:27:00 Module 7: Implementation of DBT in Clinical Settings Implementation of DBT in Clinical Settings 00:28:00 Module 8: Ethical and Professional Considerations in DBT Practice Ethical and Professional Considerations in DBT Practice 00:19:00 Certificate and Transcript Order Your Certificates and Transcripts 00:00:00

AI in Project Management: The Next Generation of Project Decision Making Project managers need to make critical project decisions on a daily basis. They are confronted with increasing complexities, high ambiguity and the need to process an exponentially growing amount of data and information in order to make informed and good decisions. This leads to an increasing risk of project failure - meanwhile, the project management industry is already challenged with ongoing low project success rates, caused by often massive failures of projects. Project Data Analytics and Artificial Intelligence (AI) are expected to fill the gap by providing analytical and unbiased capabilities that go beyond human possibilities, towards a data-driven and fact-based decision-making approach. While there is little doubt that AI as a trending technology will disrupt the project management practice and augment today's project management capabilities, AI cannot be seen as just another new tool to make project management more effective. Rather, AI will act as a complement to human intelligence, requiring a collaborative approach and, accordingly, a significant change in project culture and peoples' mindset. Today's project decisions are usually driven by human intuition, experience, leadership, and often do not follow any rational logic. Project decision-makers will be required to abandon such an approach and shift to a data-driven, decision-making approach. This session will provide an overview of the expected changes from AI-driven project management, the resulting impact on project decision making and changes in project culture, and what actions can be taken by project professionals to match their beliefs and behaviours with the new project culture. Learning goals: Gain insights into how AI for project management will significantly change decision-making in projects Gain an understanding of how to transition to a new AI-powered project culture

Machine literacy in data wisdom is a fleetly expanding discipline and now is the crucial element. This groundbreaking field equips computers and systems with the capacity to learn from data and ameliorate their performance over time without unequivocal programming. Statistical ways are employed to train algorithms to produce groups or prognostications and to find significant findings in data mining systems. immaculately, the conclusions made from these perceptivity impact crucial growth pointers in operations and companies. What's Machine Learning? . Machine learning classes in pune The machine literacy term was chased by Arthur Samuel in 1959. It's the discipline solely concentrated on studying and erecting tools and ways that can let machines learn. These styles use data to enhance the computer performance of a particular set of tasks. Machine literacy algorithms induce prognostications or possibilities and produce a model grounded on data samples, also called training data. There's a need for machine literacy as these algorithms are applied in a broad range of operations, for illustration, computer vision, dispatch filtering, speech recognition, husbandry, and drugs, where it's a challenge to produce traditional algorithms that can negotiate the needed tasks. orders in Machine Learning Being such a vast and complicated field, machine literacy is divided into three different orders machine literacy orders Supervised literacy – In this system, the algorithm is trained using data that has been labeled and in which the target variable or asked result is known. Once trained, the algorithm may make prognostications grounded on unidentified information by learning how to associate input variables with the willed affair. Unsupervised literacy – In this case, the algorithm is trained on unlabeled data, and its thing is to discover structures or patterns within the data without having a specific target variable in mind. Common unsupervised literacy tasks include dimensionality reduction and clustering. underpinning literacy – An algorithm is trained via relations with the terrain in this type of literacy. The algorithm learns how to operate in order to maximize a price signal or negotiate a particular ideal. Through prices or penalties, it receives feedback that helps it upgrade its decision-making process. Artificial Intelligence and Machine Learning Artificial intelligence( AI) is divided into several subfields, and machine literacy( ML) is one of them. In order to produce intelligent machines that can pretend mortal intelligence, a variety of methodologies, approaches, and technologies are used. This notion is known as artificial intelligence( AI). The development of ways and models that allow computers to acquire knowledge from data and make recommendations or judgments without unequivocal programming is the focus of machine literacy( ML). Some academics were interested in the idea of having machines learn from data in the early stages of AI as an academic field. They tried to approach the issue using colorful emblematic ways and neural networks. They were primarily perceptrons, along with other models that were ultimately discovered to be reimaginings of the generalized direct models of statistics. For this case, you aim to make a system secerning cows and tykes. With the AI approach, you'll use ways to make a system that can understand the images with the help of specific features and rules you define. Machine literacy models will bear training using a particular dataset of pre-defined images. You need to give numerous farmlands of cows and tykes with corresponding markers. Why is Machine Learning Important? Machine literacy is an abecedarian subfield of artificial intelligence that focuses on assaying and interpreting patterns and structures in data. It enables logic, literacy, and decision-making outside of mortal commerce. The significance of machine literacy is expanding due to the extensively more expansive and more varied data sets, the availability and affordability of computational power, and the availability of high-speed internet. It facilitates the creation of new products and provides companies with a picture of trends in consumer geste and commercial functional patterns. Machine literacy is a high element of the business operations of numerous top enterprises, like Facebook, Google, and Uber. Prophetic Analytics Machine learning course in pune Machine literacy makes prophetic analytics possible by using data to read unborn results. It's salutary in the fields of finance, healthcare, marketing, and logistics. Associations may prognosticate customer growth, spot possible troubles, streamline operations, and take visionary action to ameliorate results using prophetic models. Personalization and recommendation systems Machine literacy makes recommendation systems and substantiated gests possible, impacting every aspect of our diurnal lives. Platforms like Netflix, Amazon, and Spotify use machine literacy algorithms to comprehend stoner preferences and offer substantiated recommendations. Personalization boosts stoner pleasure and engagement while promoting business expansion. Image and speech recognition Algorithms for machine literacy are particularly good at jobs like speech and picture recognition. Deep literacy, a branch of ML, has converted computer vision and natural language processing. It makes it possible for machines to comprehend, dissect, and produce visual and audio input. This technology is helpful for driverless vehicles, surveillance, medical imaging, and availability tools, among other effects. Machine learning training in pune