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Embark on a transformative journey into the realm of emotional mastery with our course, 'Dialectical Behaviour Therapy (DBT) for Emotional Well-being'. This enlightening voyage through the intricacies of DBT will not only illuminate the path to personal emotional regulation but also equip you with the skills to facilitate others in their journey towards emotional well-being. Your exploration begins with an in-depth introduction to DBT, guiding you through its foundational principles and establishing a robust platform upon which to build your therapeutic skills. As you traverse through the carefully crafted modules, you'll delve into the core skills of mindfulness, emotion regulation, interpersonal effectiveness, and distress tolerance, each a vital beacon in the DBT landscape. These pillars of DBT are not merely theoretical constructs but practical tools, designed to be applied in real-world scenarios, ensuring that individuals can navigate through the emotional tumult of life with grace and resilience. Your journey will also guide you through the application of DBT across various populations, ensuring a versatile and adaptable therapeutic skill set. Learning Outcomes Understand and apply the foundational principles and techniques of dialectical behaviour therapy. Utilise mindfulness, emotion regulation, interpersonal effectiveness, and distress tolerance skills in therapeutic contexts. Implement DBT strategies effectively across various populations and diverse emotional challenges. Apply DBT in clinical settings, ensuring therapeutic interventions are both relevant and impactful. Navigate through ethical and professional considerations, ensuring DBT practice is conducted with integrity and adheres to professional standards. Why buy this Dialectical Behaviour Therapy (DBT) for Emotional Well-being? Unlimited access to the course for a lifetime. Opportunity to earn a certificate accredited by the CPD Quality Standards and CIQ after completing this course. Structured lesson planning in line with industry standards. Immerse yourself in innovative and captivating course materials and activities. Assessments designed to evaluate advanced cognitive abilities and skill proficiency. Flexibility to complete the Course at your own pace, on your own schedule. Receive full tutor support throughout the week, from Monday to Friday, to enhance your learning experience. Unlock career resources for CV improvement, interview readiness, and job success Who is this Dialectical Behaviour Therapy (DBT) for Emotional Well-being for? Individuals seeking personal emotional mastery and well-being through DBT. Mental health professionals aspiring to expand their therapeutic toolkit with DBT. Social workers desiring to provide enhanced emotional support to their clients. Counsellors looking to diversify their therapeutic approaches with validated techniques. Psychology students wishing to deepen their understanding and application of therapeutic modalities. Career path DBT Therapist: £30,000 - £45,000 Mental Health Counsellor: £23,000 - £40,000 Clinical Psychologist: £39,000 - £82,000 Social Worker: £25,000 - £40,000 Psychotherapist: £26,000 - £48,000 Mental Health Nurse: £25,000 - £35,000 Prerequisites This Dialectical Behaviour Therapy (DBT) for Emotional Well-being does not require you to have any prior qualifications or experience. You can just enrol and start learning. This course 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 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 00:29:00 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

In an era awash with data, understanding it is the key to unlocking significant opportunities. Enter the realm of 'SQL For Data Analytics & Database Development'. Dive deep into the heart of data manipulation, exploration, and insight generation. This course unfurls the magic behind SQL, drawing back the curtain on the tools that empower businesses globally. Understanding SQL's profound capabilities opens doors to a world where data-driven decision-making is not just an advantage but an imperative. It isn't simply about data storage. This course unravels the art of analytics, shedding light on how to glean valuable insights from vast data lakes. The path of SQL isn't merely technical; it's the spine of transformative decisions in today's leading industries. Offering a systematic approach to database development, we invite you to embark on this illuminative journey, stitching the threads of raw data into the fabric of meaningful stories. Come harness the power of SQL. Whether your intent is data analytics or the intricate craft of database development, this is your gateway. Let us guide you, from the rudimentary steps to mastering advanced commands, constructing your data narrative, and informing the future. Learning Outcomes: Comprehend the fundamental architecture of SQL and its environment. Acquire proficiency in basic and advanced SQL statements. Understand and implement GROUP BY statements for data aggregation. Master the concepts and applications of JOINS in databases. Cultivate the ability to create and structure databases and tables. Delve into advanced SQL commands, enhancing data manipulation and querying capabilities. Construct efficient database models, fostering optimal data storage and retrieval.   Video Playerhttps://studyhub.org.uk/wp-content/uploads/2021/03/SQL-DATA-ANALYSIS.mp400:0000:0000:00Use Up/Down Arrow keys to increase or decrease volume. Why choose this SQL For Data Analytics & Database Development 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 SQL For Data Analytics & Database Development 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 SQL For Data Analytics & Database Development course for? Aspirants seeking to transition into data-driven roles in various industries. Database administrators aiming to broaden their analytical capabilities. Business analysts eager to enhance their data querying skills. Researchers in need of comprehensive data management tools. Tech enthusiasts wanting to grasp the underpinnings of database systems. Career path Data Analyst - Average salary: £35,000 - £50,000 Per Annum Database Developer - Average salary: £40,000 - £55,000 Per Annum Business Intelligence Analyst - Average salary: £38,000 - £52,000 Per Annum SQL Developer - Average salary: £42,000 - £58,000 Per Annum Database Administrator (DBA) - Average salary: £45,000 - £60,000 Per Annum Data Engineer - Average salary: £47,000 - £63,000 Per Annum Prerequisites This SQL For Data Analytics & Database Development 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 Course Introduction Introduction 00:04:00 Course Curriculum Overview 00:05:00 Overview of Databases 00:10:00 SQL Environment Setup MySQL Installation 00:16:00 MySQL Workbench Installation 00:09:00 Connecting to MySQL using Console 00:09:00 SQL Statement Basics Overview of Challenges 00:04:00 SQL Statement Basic 00:16:00 SELECT Statement 00:09:00 SELECT DISTINCT 00:05:00 Column AS Statement 00:12:00 COUNT built-in Method usage 00:11:00 SELECT WHERE Clause - Part One 00:05:00 SELECT WHERE Clause - Part Two 00:11:00 SQL Statement Basic 00:16:00 SQL Limit Clause Statement 00:09:00 SQL Using BETWEEN with Same Column Data 00:11:00 How to Apply IN Operator 00:11:00 Wildcard Characters with LIKE and ILIKE 00:11:00 GROUP BY Statements Overview of GROUP BY 00:06:00 Aggregation function SUM() 00:09:00 Aggregation MIN() and MAX() 00:05:00 GROUP BY - One 00:09:00 GROUP BY - Two 00:12:00 HAVING Clause 00:05:00 JOINS Overview of JOINS 00:04:00 Introduction to JOINS 00:04:00 AS Statement table 00:03:00 INNER Joins 00:14:00 FULL Outer Join 00:11:00 LEFT Outer JOIN 00:08:00 RIGHT JOIN 00:08:00 Union 00:07:00 Advanced SQL Commands / Statements Timestamps 00:12:00 EXTRACT from timestamp 00:10:00 Mathematical Functions 00:12:00 String Functions 00:22:00 SUBQUERY 00:13:00 Creating Database and Tables Basic of Database and Tables 00:06:00 DataTypes 00:10:00 Primarykey and Foreignkey 00:06:00 Create Table in SQL Script 00:13:00 Insert 00:11:00 Update 00:07:00 Delete 00:04:00 Alter Table 00:09:00 Drop Table 00:05:00 NOT NULL Constraint 00:08:00 UNIQUE Constraint 00:09:00 Databases and Tables Creating a Database backup 00:12:00 10a Overview of Databases and Tables 00:05:00 10c Restoring a Database 00:07:00

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This course teaches the fundamental concepts of DAX in Power BI. If you have the questions: How do I learn DAX? What is the best way to learn DAX fast?-then this is the best course for you. This course teaches fundamental concepts and does not cover visualization or various advanced DAX patterns for specific questions.

Duration 4 Days 24 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 brand-new 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 adversarial 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 1 Days 6 CPD hours This course is intended for This course is designed for data scientists with experience of Python who need to learn how to apply their data science and machine learning skills on Azure Databricks. Overview After completing this course, you will be able to: Provision an Azure Databricks workspace and cluster Use Azure Databricks to train a machine learning model Use MLflow to track experiments and manage machine learning models Integrate Azure Databricks with Azure Machine Learning Azure Databricks is a cloud-scale platform for data analytics and machine learning. In this course, students will learn how to use Azure Databricks to explore, prepare, and model data; and integrate Databricks machine learning processes with Azure Machine Learning. Introduction to Azure Databricks Getting Started with Azure Databricks Working with Data in Azure Databricks Training and Evaluating Machine Learning Models Preparing Data for Machine Learning Training a Machine Learning Model Managing Experiments and Models Using MLflow to Track Experiments Managing Models Managing Experiments and Models Using MLflow to Track Experiments Managing Models Integrating Azure Databricks and Azure Machine Learning Tracking Experiments with Azure Machine Learning Deploying Models

Recognised Accreditation This course is accredited by continuing professional development (CPD). CPD UK is globally recognised by employers, professional organisations, and academic institutions, thus a certificate from CPD Certification Service creates value towards your professional goal and achievement. 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. What is CPD? Employers, professional organisations, and academic institutions all recognise CPD, therefore a credential from CPD Certification Service adds value to your professional goals and achievements. Benefits of CPD Improve your employment prospects Boost your job satisfaction Promotes career advancement Enhances your CV Provides you with a competitive edge in the job market Demonstrate your dedication Showcases your professional capabilities What is IPHM? The IPHM is an Accreditation Board that provides Training Providers with international and global accreditation. The Practitioners of Holistic Medicine (IPHM) accreditation is a guarantee of quality and skill. Benefits of IPHM It will help you establish a positive reputation in your chosen field You can join a network and community of successful therapists that are dedicated to providing excellent care to their client You can flaunt this accreditation in your CV It is a worldwide recognised accreditation What is Quality Licence Scheme? This course is endorsed by the Quality Licence Scheme for its high-quality, non-regulated provision and training programmes. 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. Benefits of Quality License Scheme Certificate is valuable Provides a competitive edge in your career It will make your CV stand out Course Curriculum Welcome to the course Introduction 00:02:00 Setting up R Studio and R crash course Installing R and R studio 00:05:00 Basics of R and R studio 00:10:00 Packages in R 00:10:00 Inputting data part 1: Inbuilt datasets of R 00:04:00 Inputting data part 2: Manual data entry 00:03:00 Inputting data part 3: Importing from CSV or Text files 00:06:00 Creating Barplots in R 00:13:00 Creating Histograms in R 00:06:00 Basics of Statistics Types of Data 00:04:00 Types of Statistics 00:02:00 Describing the data graphically 00:11:00 Measures of Centers 00:07:00 Measures of Dispersion 00:04:00 Introduction to Machine Learning Introduction to Machine Learning 00:16:00 Building a Machine Learning Model 00:08:00 Data Preprocessing for Regression Analysis Gathering Business Knowledge 00:03:00 Data Exploration 00:03:00 The Data and the Data Dictionary 00:07:00 Importing the dataset into R 00:03:00 Univariate Analysis and EDD 00:03:00 EDD in R 00:12:00 Outlier Treatment 00:04:00 Outlier Treatment in R 00:04:00 Missing Value imputation 00:03:00 Missing Value imputation in R 00:03:00 Seasonality in Data 00:03:00 Bi-variate Analysis and Variable Transformation 00:16:00 Variable transformation in R 00:09:00 Non Usable Variables 00:04:00 Dummy variable creation: Handling qualitative data 00:04:00 Dummy variable creation in R 00:05:00 Correlation Matrix and cause-effect relationship 00:10:00 Correlation Matrix in R 00:08:00 Linear Regression Model The problem statement 00:01:00 Basic equations and Ordinary Least Squared (OLS) method 00:08:00 Assessing Accuracy of predicted coefficients 00:14:00 Assessing Model Accuracy - RSE and R squared 00:07:00 Simple Linear Regression in R 00:07:00 Multiple Linear Regression 00:05:00 The F - statistic 00:08:00 Interpreting result for categorical Variable 00:05:00 Multiple Linear Regression in R 00:07:00 Test-Train split 00:09:00 Bias Variance trade-off 00:06:00 Test-Train Split in R 00:08:00 Regression models other than OLS Linear models other than OLS 00:04:00 Subset Selection techniques 00:11:00 Subset selection in R 00:07:00 Shrinkage methods - Ridge Regression and The Lasso 00:07:00 Ridge regression and Lasso in R 00:12:00 Classification Models: Data Preparation The Data and the Data Dictionary 00:08:00 Importing the dataset into R 00:03:00 EDD in R 00:11:00 Outlier Treatment in R 00:04:00 Missing Value imputation in R 00:03:00 Variable transformation in R 00:06:00 Dummy variable creation in R 00:05:00 The Three classification models Three Classifiers and the problem statement 00:03:00 Why can't we use Linear Regression? 00:04:00 Logistic Regression Logistic Regression 00:08:00 Training a Simple Logistic model in R 00:03:00 Results of Simple Logistic Regression 00:05:00 Logistic with multiple predictors 00:02:00 Training multiple predictor Logistic model in R 00:01:00 Confusion Matrix 00:03:00 Evaluating Model performance 00:07:00 Predicting probabilities, assigning classes and making Confusion Matrix in R 00:06:00 Linear Discriminant Analysis Linear Discriminant Analysis 00:09:00 Linear Discriminant Analysis in R 00:09:00 K-Nearest Neighbors Test-Train Split 00:09:00 Test-Train Split in R 00:08:00 K-Nearest Neighbors classifier 00:08:00 K-Nearest Neighbors in R 00:08:00 Comparing results from 3 models Understanding the results of classification models 00:06:00 Summary of the three models 00:04:00 Simple Decision Trees Basics of Decision Trees 00:10:00 Understanding a Regression Tree 00:10:00 The stopping criteria for controlling tree growth 00:03:00 The Data set for this part 00:03:00 Importing the Data set into R 00:06:00 Splitting Data into Test and Train Set in R 00:05:00 Building a Regression Tree in R 00:14:00 Pruning a tree 00:04:00 Pruning a Tree in R 00:09:00 Simple Classification Tree Classification Trees 00:06:00 The Data set for Classification problem 00:01:00 Building a classification Tree in R 00:09:00 Advantages and Disadvantages of Decision Trees 00:01:00 Ensemble technique 1 - Bagging Bagging 00:06:00 Bagging in R 00:06:00 Ensemble technique 2 - Random Forest Random Forest technique 00:04:00 Random Forest in R 00:04:00 Ensemble technique 3 - GBM, AdaBoost and XGBoost Boosting techniques 00:07:00 Gradient Boosting in R 00:07:00 AdaBoosting in R 00:09:00 XGBoosting in R 00:16:00 Maximum Margin Classifier Content flow 00:01:00 The Concept of a Hyperplane 00:05:00 Maximum Margin Classifier 00:03:00 Limitations of Maximum Margin Classifier 00:02:00 Support Vector Classifier Support Vector classifiers 00:10:00 Limitations of Support Vector Classifiers 00:01:00 Support Vector Machines Kernel Based Support Vector Machines 00:06:00 Creating Support Vector Machine Model in R The Data set for the Classification problem 00:01:00 Importing Data into R 00:08:00 Test-Train Split 00:09:00 Classification SVM model using Linear Kernel 00:16:00 Hyperparameter Tuning for Linear Kernel 00:06:00 Polynomial Kernel with Hyperparameter Tuning 00:10:00 Radial Kernel with Hyperparameter Tuning 00:06:00 The Data set for the Regression problem 00:03:00 SVM based Regression Model in R 00:11:00 Assessment Assessment - Machine Learning Masterclass 00:10:00 Certificate of Achievement Certificate of Achievement 00:00:00 Get Your Insurance Now Get Your Insurance Now 00:00:00 Feedback Feedback 00:00:00

Duration 3 Days 18 CPD hours This course is intended for This in an intermediate and beyond-level course is geared for experienced Python developers looking to delve into the exciting field of Natural Language Processing. It is ideally suited for roles such as data analysts, data scientists, machine learning engineers, or anyone working with text data and seeking to extract valuable insights from it. If you're in a role where you're tasked with analyzing customer sentiment, building chatbots, or dealing with large volumes of text data, this course will provide you with practical, hands on skills that you can apply right away. Overview This course combines engaging instructor-led presentations and useful demonstrations with valuable hands-on labs and engaging group activities. Throughout the course you'll: Master the fundamentals of Natural Language Processing (NLP) and understand how it can help in making sense of text data for valuable insights. Develop the ability to transform raw text into a structured format that machines can understand and analyze. Discover how to collect data from the web and navigate through semi-structured data, opening up a wealth of data sources for your projects. Learn how to implement sentiment analysis and topic modeling to extract meaning from text data and identify trends. Gain proficiency in applying machine learning and deep learning techniques to text data for tasks such as classification and prediction. Learn to analyze text sentiment, train emotion detectors, and interpret the results, providing a way to gauge public opinion or understand customer feedback. The Hands-on Natural Language Processing (NLP) Boot Camp is an immersive, three-day course that serves as your guide to building machines that can read and interpret human language. NLP is a unique interdisciplinary field, blending computational linguistics with artificial intelligence to help machines understand, interpret, and generate human language. In an increasingly data-driven world, NLP skills provide a competitive edge, enabling the development of sophisticated projects such as voice assistants, text analyzers, chatbots, and so much more. Our comprehensive curriculum covers a broad spectrum of NLP topics. Beginning with an introduction to NLP and feature extraction, the course moves to the hands-on development of text classifiers, exploration of web scraping and APIs, before delving into topic modeling, vector representations, text manipulation, and sentiment analysis. Half of your time is dedicated to hands-on labs, where you'll experience the practical application of your knowledge, from creating pipelines and text classifiers to web scraping and analyzing sentiment. These labs serve as a microcosm of real-world scenarios, equipping you with the skills to efficiently process and analyze text data. Time permitting, you?ll also explore modern tools like Python libraries, the OpenAI GPT-3 API, and TensorFlow, using them in a series of engaging exercises. By the end of the course, you'll have a well-rounded understanding of NLP, and will leave equipped with the practical skills and insights that you can immediately put to use, helping your organization gain valuable insights from text data, streamline business processes, and improve user interactions with automated text-based systems. You?ll be able to process and analyze text data effectively, implement advanced text representations, apply machine learning algorithms for text data, and build simple chatbots. Launch into the Universe of Natural Language Processing The journey begins: Unravel the layers of NLP Navigating through the history of NLP Merging paths: Text Analytics and NLP Decoding language: Word Sense Disambiguation and Sentence Boundary Detection First steps towards an NLP Project Unleashing the Power of Feature Extraction Dive into the vast ocean of Data Types Purification process: Cleaning Text Data Excavating knowledge: Extracting features from Texts Drawing connections: Finding Text Similarity through Feature Extraction Engineer Your Text Classifier The new era of Machine Learning and Supervised Learning Architecting a Text Classifier Constructing efficient workflows: Building Pipelines for NLP Projects Ensuring continuity: Saving and Loading Models Master the Art of Web Scraping and API Usage Stepping into the digital world: Introduction to Web Scraping and APIs The great heist: Collecting Data by Scraping Web Pages Navigating through the maze of Semi-Structured Data Unearth Hidden Themes with Topic Modeling Embark on the path of Topic Discovery Decoding algorithms: Understanding Topic-Modeling Algorithms Dialing the right numbers: Key Input Parameters for LSA Topic Modeling Tackling complexity with Hierarchical Dirichlet Process (HDP) Delving Deep into Vector Representations The Geometry of Language: Introduction to Vectors in NLP Text Manipulation: Generation and Summarization Playing the creator: Generating Text with Markov Chains Distilling knowledge: Understanding Text Summarization and Key Input Parameters for TextRank Peering into the future: Recent Developments in Text Generation and Summarization Solving real-world problems: Addressing Challenges in Extractive Summarization Riding the Wave of Sentiment Analysis Unveiling emotions: Introduction to Sentiment Analysis Tools Demystifying the Textblob library Preparing the canvas: Understanding Data for Sentiment Analysis Training your own emotion detectors: Building Sentiment Models Optional: Capstone Project Apply the skills learned throughout the course. Define the problem and gather the data. Conduct exploratory data analysis for text data. Carry out preprocessing and feature extraction. Select and train a model. ? Evaluate the model and interpret the results. Bonus Chapter: Generative AI and NLP Introduction to Generative AI and its role in NLP. Overview of Generative Pretrained Transformer (GPT) models. Using GPT models for text generation and completion. Applying GPT models for improving autocomplete features. Use cases of GPT in question answering systems and chatbots. Bonus Chapter: Advanced Applications of NLP with GPT Fine-tuning GPT models for specific NLP tasks. Using GPT for sentiment analysis and text classification. Role of GPT in Named Entity Recognition (NER). Application of GPT in developing advanced chatbots. Ethics and limitations of GPT and generative AI technologies.

24-Hour Knowledge Knockdown! Prices Reduced Like Never Before Water is a precious resource, and its management is crucial in the UK. A recent study by the Environment Agency found that over half of England's rivers fail to meet good ecological status. Do you want to play a role in improving water management and protecting our environment? If so, then this ArcGIS for Hydrology bundle is for you! Our course delves into ArcGIS, the industry-standard GIS platform, teaching you to leverage spatial data for hydrological analysis. You'll master essential tools for tasks like watershed delineation, flow direction mapping, and floodplain modelling. Additionally, you'll gain valuable skills in spatial analysis, remote sensing for water resource monitoring, and professional cartographic techniques to effectively communicate your findings. This Diploma in ArcGIS for Hydrology at QLS Level 4 course is endorsed by The Quality Licence Scheme and accredited by CPDQS (with 120 CPD points). Our Bundle contains 5 of our premium courses for one discounted price: Course 01: Diploma in ArcGIS for Hydrology Course 02: Spatial Analysis in ArcGIS Course 03: Remote Sensing in ArcGIS Course 04: QGIS Cartography Course 05: Environmental Management Empower yourself with the knowledge and skills to become a water management expert. Enrol today and unlock a rewarding career path! Learning Outcomes of ArcGIS for Hydrology Apply core ArcGIS functions for spatial data management and analysis. Utilise hydrological tools for watershed delineation, flow modeling, and flood risk assessment. Leverage remote sensing data for water resource monitoring and change detection. Create professional and informative maps to communicate hydrological data. Automate workflows using ArcGIS scripting and geoprocessing tools. Integrate ArcGIS with other software for comprehensive water management solutions. Why Choose Us? Get a Free CPD Accredited Certificate upon completion of ArcGIS for Hydrology Get a free student ID card with ArcGIS for Hydrology Training program (£10 postal charge will be applicable for international delivery) The ArcGIS for Hydrology is affordable and simple to understand This course is entirely online, interactive lesson with voiceover audio Get Lifetime access to the ArcGIS for Hydrology course materials The ArcGIS for Hydrology comes with 24/7 tutor support Start your learning journey straightaway! *** Course Curriculum *** Course 01: Diploma in ArcGIS for Hydrology Section 01: Introduction To ArcGIS Software Introduction to ArcGIS software Selection by Location, attributes, clip features and tables to Excel Performing actions on the data: change the projections, dissolve, clip From .TXT and .DXF to shapefile Calculations with attribute table and KML files in ArcMap Export from ArcMap to PDF ArcScene 3D GIS Example Test AutoCAD fixing polygon coordinates Section 02: ArcGIS For Hydrology Download hydrological data Calculate flow direction and flow accumulation Watershed delineation Clip layers to watershed boundary Stream segments and catchments areas Stream order convert to vector Spatial join to catchments Join stream id to stream order Map data and initial layout Add and format map elements Course 02: Award in Spatial Analysis in ArcGIS Module 01: Point Density Analysis Module 02: Raster Calculator and Vector Isolation Module 03: Raster to Topography Module 04: Raster Reclassification Module 05: Raster Overlay Module 06: Slope Analysis and Hydrology tools Module 07: Introduction to TIFF Files Module 08: Introduction to 3D Surfaces Module 09: Satellite Images and TIN Surfaces Module 10: Exercise Course 03: Remote Sensing in ArcGIS Module 01: Remote sensing, satellite images, spectral bands introduction Module 02: Layers stacking satellite images Module 03: Georeferencing satellite images Module 04: Introduction to geoprocessing raster tools Module 05: Raster Analysis Functions Module 06: Georeferencing toposheet Module 07: Site suitability using weighted overlay analysis - part 1 Module 08 Site suitability using weighted overlay analysis - part 2 Module 09: Watershed Delineation from DEM Module 10: Unsupervised classification =========>>>>> And 2 More Courses <<<<<========= How will I get my Certificate? After successfully completing the course, you will be able to order your Certificates as proof of your achievement. PDF Certificate: Free (Previously it was £12.99*5 = £65) CPD Hard Copy Certificate: £29.99 CPD 50 CPD hours / points Accredited by CPD Quality Standards Who is this course for? Anyone interested in learning more about the topic is advised to take this bundle. This bundle is ideal for: Hydrologists Environmental Scientists Flood Risk Assessors GIS Analysts Water Resource Managers Requirements You will not need any prior background or expertise to enrol in this bundle. Career path After completing this bundle, you are to start your career or begin the next phase of your career. Water Management Environmental Consulting Flood Risk Management GIS Specialist Cartographer Researcher Certificates CPD Accredited Digital Certificate Digital certificate - Included Upon passing the Course, you need to order a Digital Certificate for each of the courses inside this bundle as proof of your new skills that are accredited by CPD QS for Free. CPD Accredited Hard Copy Certificate Hard copy certificate - Included Please note that International students have to pay an additional £10 as a shipment fee. Diploma in ArcGIS for Hydrology at QLS Level 4 Hard copy certificate - £99 Please note that International students have to pay an additional £10 as a shipment fee.

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