1302 Scientist courses delivered Online

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

Are you ready to embark on an enlightening journey of wisdom with the Learn C++ Fundamentals bundle, and pave your way to an enriched personal and professional future? If so, then Step into a world of knowledge with our bundle - Learn C++ Fundamentals: Coding for Absolute Beginners. Delve into eight immersive CPD Accredited courses, each a simple course: Course 1: C++ Development: The Complete Coding Guide Course 2: Computer Vision by Using C++ and OpenCV Course 3: Learn to Code with Python 3! Course 4: Coding with HTML, CSS, & Javascript Course 5: The Ultimate MySQL Course for Beginners Course 6: Ultimate PHP & MySQL Web Development Course & OOP Coding Course 7: Kotlin Masterclass Programming Course: Android Coding Bible Course 8: HTML Web Development Crash Course Traverse the vast landscapes of theory, unlocking new dimensions of understanding at every turn. Let the Learn C++ Fundamentals: Coding for Absolute Beginners bundle illuminate your path to wisdom. The Learn C++ Fundamentals: Coding for Absolute Beginners bundle offers a comprehensive exploration into a rich tapestry of vast knowledge across eight carefully curated courses. The journey is designed to enhance your understanding and critical thinking skills. Each course within the bundle provides a deep-dive into complex theories, principles, and frameworks, allowing you to delve into the nuances of the subject matter at your own pace. In the framework of the Learn C++ Fundamentals: Coding for Absolute Beginners package, you are bestowed with complimentary PDF certificates for all the courses included in this bundle, all without any additional charge. Adorn yourself with the Learn C++ Fundamentals bundle, empowering you to traverse your career trajectory or personal growth journey with self-assurance. Register today and ignite the spark of your professional advancement! So, don't wait further and join the Learn C++ Fundamentals: Coding for Absolute Beginners community today and let your voyage of discovery begin! Learning Outcomes: Upon completion of the Learn C++ Fundamentals: Coding for Absolute Beginners Bundle, you will be able to: Attain a holistic understanding in the designated areas of study with the Learn C++ Fundamentals bundle. Establish robust bases across each course nestled within the Learn C++ Fundamentals bundle. Decipher intricate concepts through the articulate content of the Learn C++ Fundamentals bundle. Amplify your prowess in interpreting, scrutinising, and implementing theories. Procure the capacity to engage with the course material on an intellectual and profound level. Become proficient in the art of problem-solving across various disciplines. Stepping into the Learn C++ Fundamentals: Coding for Absolute Beginners bundle is akin to entering a world overflowing with deep theoretical wisdom. Each course within this distinctive bundle is an individual journey, meticulously crafted to untangle the complex web of theories, principles, and frameworks. Learners are inspired to explore, question, and absorb, thus enhancing their understanding and honing their critical thinking skills. Each course invites a personal and profoundly enlightening interaction with knowledge. The Learn C++ Fundamentals bundle shines in its capacity to cater to a wide range of learning needs and lifestyles. It gives learners the freedom to learn at their own pace, forging a unique path of discovery. More than just an educational journey, the Learn C++ Fundamentals: Coding for Absolute Beginners bundle fosters personal growth, enabling learners to skillfully navigate the complexities of the world. The Learn C++ Fundamentals bundle also illuminates the route to a rewarding career. The theoretical insight acquired through this bundle forms a strong foundation for various career opportunities, from academia and research to consultancy and programme management. The profound understanding fostered by the Learn C++ Fundamentals bundle allows learners to make meaningful contributions to their chosen fields. Embark on the Learn C++ Fundamentals journey and let knowledge guide you towards a brighter future. CPD 90 CPD hours / points Accredited by CPD Quality Standards Who is this course for? Individuals keen on deepening their firm understanding in the respective fields. Students pursuing higher education looking for comprehensive theory modules. Professionals seeking to refresh or enhance their knowledge. Anyone with a thirst for knowledge and a passion for continuous learning. Requirements Without any formal requirements, you can delightfully enrol in this Learn C++ Fundamentals: Coding for Absolute Beginners Bundle. Career path Armed with the Learn C++ Fundamentals: Coding for Absolute Beginners bundle, your professional journey can reach new heights. The comprehensive theoretical knowledge from this bundle can unlock diverse career opportunities across several fields. Whether it's academic research, consultancy, or programme management, the Learn C++ Fundamentals bundle lays a solid groundwork. Certificates CPD Certificate Of Completion Digital certificate - Included 8 Digital Certificates Are Included With This Bundle CPD Quality Standard Hardcopy Certificate (FREE UK Delivery) Hard copy certificate - £9.99 Hardcopy Transcript: £9.99

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

Embark on a journey into the world of strategic analysis with this advanced course. Delve deep into risk management standards, the COSO framework for internal controls, competitive positioning strategies, BCG Matrix for portfolio analysis, pricing strategies, and the impact of economies of scale. Equip yourself with the tools and models essential for navigating complex business landscapes. This course is a comprehensive exploration of advanced tools and models crucial for strategic analysis. After the successful completion of this course, you will be able to: ⦁ Understand risk management standards' significance and application for organizational resilience and threat mitigation. ⦁ Identify components of the COSO framework for effective internal controls and risk assessment. ⦁ Analyze different types of competitive positions to strategize for market advantage. ⦁ Comprehend BCG Matrix for product/service portfolio analysis. ⦁ Explore pricing strategies and their impact on revenue and market position. ⦁ Understand economies of scale and their influence on cost efficiency and competitiveness. Elevate your risk analysis expertise with our advanced course, meticulously curated for professionals. Uncover sophisticated tools and models designed for strategic precision, empowering you to navigate complexities with confidence. Sharpen your analytical prowess and stay ahead in the dynamic business landscape. Enroll to master the art of strategic risk analysis. 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. Advanced Tools And Models For Strategic Analysis Self-paced pre-recorded learning content on this topic. Advanced Tools And Models For Strategic Analysis 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 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 eager to know more and get updated on current ideas in their respective field. We recommend this certificate for the following audience.  1. Risk Management Professionals 2. Financial Analysts3. Strategic Planners4. Business Intelligence Analysts5. Project Managers6. Compliance Officers7. Data Scientists8. Decision Analysts 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.

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

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.

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

Unlock the potential of AI-driven creative writing with our QuillBot AI Masterclass. Elevate your writing skills and explore advanced features for flawless content creation.

48-Hour Knowledge Knockdown! Prices Reduced Like Never Before. Healthcare GDPR is an essential course for professionals in the healthcare industry. Learn how to effectively comply with UK data protection laws, maintain the privacy and security of patient information, and stay up-to-date on the latest trends in healthcare data protection. Discover how to build a robust healthcare GDPR strategy to protect sensitive information, minimise the risk of breaches, and ensure the privacy of patients. This Certificate in Healthcare GDPR Training at QLS Level 3 course is endorsed by The Quality Licence Scheme and accredited by CPDQS (with 120 CPD points) to make your skill development & career progression more accessible than ever! In health and social care organisations, there are more stringent regulations governing the collection, processing, and storage of personal data. Additionally, a healthcare GDPR training makes sure that a company efficiently protects patient information. You will learn the foundations of maintaining the integrity of healthcare data with this Healthcare GDPR course for the healthcare industry. Take our Healthcare GDPR course and get ready for: Understanding the General Data Protection Regulation (GDPR) and its implications for healthcare professionals Knowing how to handle personal data in accordance with GDPR regulations Being able to implement appropriate security measures to protect patient data Understanding the rights of patients under GDPR and how to respond to requests for access to their data Knowing how to handle data breaches and report them in accordance with GDPR requirements. Why Prefer This Healthcare GDPR at QLS Level 3 Course? Opportunity to earn a certificate endorsed by the Quality Licence Scheme & another accredited by CPDQS which is completely free. Get a free student ID card! (£10 postal charge will be applicable for international delivery) Innovative and engaging content. Free assessments 24/7 tutor support. Our Healthcare GDPR course is designed specifically for helping the learners to understand and comply with the General Data Protection Regulation (GDPR). Through interactive lessons and practical examples, you will learn about the key principles of GDPR and how they apply to the healthcare sector. You will also learn about the rights of patients under GDPR and how to handle their personal data in a compliant manner. Additionally, you will learn about the importance of implementing appropriate security measures to protect patient data, as well as how to handle and report data breaches. By the end of this Healthcare GDPR Training course, you will have the knowledge and skills needed to ensure compliance with GDPR in your healthcare practice. *** Course Curriculum *** Here is the curriculum breakdown of the Healthcare GDPR at QLS Level 3 course: Module 01: Introduction to GDPR Module 02: GDPR and Healthcare Setting Module 03: General Data Protection Regulations Explained Module 04: Lawful Basis for Preparation Module 05: Responsibilities and Obligations Module 06: Electronic Medical Records Module 07: Rights and Breaches Assessment Process You have to complete the assignment questions given at the end of the course and score a minimum of 60% to pass each exam. Our expert trainers will assess your assignment and give you feedback after you submit the assignment. You will be entitled to claim a certificate endorsed by the Quality Licence Scheme after you have completed the Certificate in Healthcare GDPR Training at QLS Level 3 exam. CPD 120 CPD hours / points Accredited by CPD Quality Standards Who is this course for? Healthcare professionals, including doctors, nurses, and other healthcare staff Those working in healthcare administration or management roles Those responsible for handling patient data in a healthcare setting Those interested in understanding the legal requirements for handling personal data in the healthcare sector Those looking to ensure compliance with GDPR in their healthcare practice. Requirements No prior background or expertise is required. Career path Compliance Officer - Average Annual Income £35,686 Data Protection Officer (DPO) - Average Annual Income £44,557 Healthcare Administrator - Average Annual Income £23,526 Healthcare Consultant - Average Annual Income £42,500 Legal Professional - Average Annual Income £43712 Certificates Certificate in Healthcare GDPR Training at QLS Level 3 Hard copy certificate - Included After successfully completing the Certificate in Healthcare GDPR Training at QLS Level 3, you can order an original hardcopy certificate of achievement endorsed by the Quality Licence Scheme andalso you can order CPDQSAccredited Certificate that is recognised all over the UK and also internationally. The certificates will be home-delivered, completely free of cost. CPDQS Accredited Certificate Digital certificate - Included

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