1140 Courses

Experience the future of geographical analysis with our Machine Learning for Predictive Maps in Python and Leaflet course. Master the unique blend of programming, machine learning, and geographic information systems, all while honing your ability to predict and visualise spatial data in a powerful and effective way. This course offers you an unparalleled understanding of modern map creation, combined with the magic of prediction using machine learning models. Starting from the ground up, you'll be introduced to all the necessary setups and installations. After that, you will be diving into the depth of Django server-side code and front-end application code writing. The heart of the course lies in learning how to automate the machine learning pipeline, leading you to easily create predictive models.  Improve your maps with Leaflet programming, making your predictions accurate and also visually striking. By the end of this course, you will be armed with experience furnished by our comprehensive project source code and assignments, empowering you to drive data-driven decisions and insightful spatial analysis. Join us and map your way to success! Sign up today. Learning Outcomes:Upon completion of the Machine Learning course, you will be able to: Understand how to set up and install relevant software and libraries.Master Django server-side and application front-end code writing.Gain proficiency in the concepts and implementation of Machine Learning.Learn to automate Machine Learning pipelines for efficient workflows.Acquire skills in Leaflet programming for enhanced map visuals.Handle project source code effectively for real-world projects.Apply knowledge practically via assignments and gain experience. Who is this course for?This Machine Learning course is ideal for: Aspiring Data Scientists keen on harnessing geographical data.GIS professionals aiming to integrate Machine Learning into their skill set.Software Developers interested in creating geographically-focused applications.Analysts keen on enhancing their data visualisation skills with mapping. CertificationAfter studying the course materials of the Machine Learning for Predictive Maps in Python and Leaflet course, there will be a written assignment test which you can take either during or at the end of the course. After successfully passing the test, you have a range of certification options to choose from. You can claim a CPD Accredited PDF Certificate for £4.99, a CPD Accredited Hardcopy Certificate at £8.00, or you may choose to receive a PDF Transcript for £4.99 or a Hardcopy Transcript for £9.99. Select according to your needs, and we assure timely delivery of your chosen certificate. RequirementsThis professionally designed Machine Learning for Predictive Maps in Python and Leaflet course does not require you to have any prior qualifications or experience. It is open to everyone. You will be able to access the course from anywhere at any time. Just enrol and start learning! Career Path:Our Machine Learning course will help you to pursue a range of career paths, such as: Junior Data Analyst: £25,000 - £35,000 annually.Data Scientist: £40,000 - £60,000 annually.GIS Analyst: £30,000 - £45,000 annually.Geospatial Software Developer: £35,000 - £55,000 annually.Machine Learning Engineer: £50,000 - £80,000 annually.Lead Data Scientist (GIS speciality): £70,000 - £100,000+ annually. Course Curriculum Section 01: Introduction Introduction 00:10:00 Section 02: Setup and Installations 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 Section 03: Writing the Django Server-Side Code Adding the settings.py Code 00:07:00 Creating a Django Model 00:10:00 Adding the admin.py Code 00:21:00 Section 04: Writing the Application Front-end Code 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 Section 05: Machine Learning 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 Section 06: Automating the Machine Learning Pipeline 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 Section 07: Leaflet Programming 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 Section 08: Project Source Code Resource 00:00:00 Assignment Assignment - Machine Learning for Predictive Maps in Python and Leaflet 00:00:00

The digital landscape is brimming with opportunities. As our reliance on technology continues to burgeon, so does the demand for rigorous data protection, cyber security, and the legal frameworks surrounding them. At the epicentre of this evolution stands GDPR. Seize the opportunity to lead this thriving industry with our "GDPR Compliance, Data Protection & Cyber Security" bundle. This 8-course bundle seamlessly integrates key areas from GDPR to AML. Tailored for the digital age, it offers a comprehensive grasp of data protection, cyber security, and relevant laws, ensuring professionals are equipped for modern challenges. The CPD Accredited Eight Courses Are: Course 1: GDPR Course 2: Data Protection Course 3: Paralegal Training Course 4: Commercial Law Course 5: Cyber Law Online Course Course 6: Business Law Course 7: Cyber Security Awareness Training Course 8: Anti-Money Laundering (AML) Training Learning Outcomes of the GDPR Compliance, Data Protection & Cyber Security Bundle: Understand GDPR's core principles, compliance needs, and business implications. Implement best practices for safeguarding sensitive information. Grasp essential concepts in paralegal, commercial, cyber, and business law. Recognise and prevent potential money laundering activities in line with global regulations. Understand the interplay between commercial law and GDPR within business operations. Navigate GDPR, data protection, and related legal landscapes with confidence. Course 1: GDPR Dive deep into the core principles of the General Data Protection Regulation (GDPR). Understand its purpose, implications, and the necessary compliance mechanisms for businesses. Course 2: Data Protection Beyond just GDPR, explore the broader landscape of data protection. Equip yourself with the tools and strategies to safeguard sensitive information in various contexts. Course 3: Paralegal Training A cornerstone for those keen to step into the legal world, this course lays down the groundwork for legal principles, processes, and professional responsibilities. Course 4: Commercial Law Engage with the intricacies of commercial law. Gain insights into business contracts, trade, and the legal framework that governs commercial operations. Course 5: Cyber Law Online Course The digital realm is rife with its own set of legal challenges. This course delves into the regulations, rights, and responsibilities of online activities and digital interactions. Course 6: Business Law A comprehensive look into the rules, regulations, and laws that dictate how a business should operate. Ideal for professionals, entrepreneurs, and those interested in the legal side of business. Course 7: Cyber Security Awareness Training With cyber threats escalating, this course heightens awareness about the importance of cybersecurity. Learn the best practices to keep data safe and recognise potential cyber threats. Course 8: Anti-Money Laundering (AML) Training Tackle the dark side of finance. Grasp the essential principles behind AML, the mechanisms to detect suspicious activities, and the protocols to prevent illegal money movements. CPD 45 CPD hours / points Accredited by CPD Quality Standards Who is this course for? This GDPR Compliance, Data Protection & Cyber Security Course are suitable for: Business Professionals: Understand GDPR's impact on operations. Legal Enthusiasts: Deepen knowledge in data and cyber law. IT Experts: Enhance cybersecurity and data protection strategies. Entrepreneurs: Navigate legal and compliance landscapes. Finance Experts: Grasp anti-money laundering protocols. DPOs: Master GDPR implementation and related areas. After Completing this bundle, anyone can later enroll in this following course: NCFE Level 2 Certificate in the Principles of Cyber Security Certified Governance & Compliance Audit Professional Association of Governance, Risk and Compliance Highfield Awarding Body for Compliance Exam SC-900: Microsoft Security, Compliance, and Identity Fundamentals Level 7 Diploma in International Business Law Requirements Without any formal requirements, you can delightfully enrol in this GDPR Compliance, Data Protection & Cyber Security course. Just get a device with internet connectivity, and you are ready to start your learning journey. Thus, complete this GDPR course at your own pace. Career path Our GDPR Compliance, Data Protection & Cyber Security course will prepare you for a range of careers, including: Paralegal GDPR Consultant Data Protection Officer (DPO) Cybersecurity Specialist Legal Consultant in Cyber Law Compliance Officer AML Analyst Business Law Advisor The Combined Salary Range for this bundle is approximately £35,000 to £135,000+ per annum. Certificates Certificate of Completion Digital certificate - Included Certificate of Completion Hard copy certificate - £9.99

In this course, we'll learn how to visualize data with real weather data downloaded from the US National Weather Service using the R programming language and RStudio. We recommend that you have some background in HTML, CSS, and JavaScript. You don't need to be an expert by any means, but you should have experience building web pages with HTML and CSS, and you should have basic programming skills with JavaScript.

Duration 4 Days 24 CPD hours This course is intended for This course is best suited to developers, engineers, and architects who want to use use Hadoop and related tools to solve real-world problems. Overview Skills learned in this course include:Creating a data set with Kite SDKDeveloping custom Flume components for data ingestionManaging a multi-stage workflow with OozieAnalyzing data with CrunchWriting user-defined functions for Hive and ImpalaWriting user-defined functions for Hive and ImpalaIndexing data with Cloudera Search Cloudera University?s four-day course for designing and building Big Data applications prepares you to analyze and solve real-world problems using Apache Hadoop and associated tools in the enterprise data hub (EDH). IntroductionApplication Architecture Scenario Explanation Understanding the Development Environment Identifying and Collecting Input Data Selecting Tools for Data Processing and Analysis Presenting Results to the Use Defining & Using Datasets Metadata Management What is Apache Avro? Avro Schemas Avro Schema Evolution Selecting a File Format Performance Considerations Using the Kite SDK Data Module What is the Kite SDK? Fundamental Data Module Concepts Creating New Data Sets Using the Kite SDK Loading, Accessing, and Deleting a Data Set Importing Relational Data with Apache Sqoop What is Apache Sqoop? Basic Imports Limiting Results Improving Sqoop?s Performance Sqoop 2 Capturing Data with Apache Flume What is Apache Flume? Basic Flume Architecture Flume Sources Flume Sinks Flume Configuration Logging Application Events to Hadoop Developing Custom Flume Components Flume Data Flow and Common Extension Points Custom Flume Sources Developing a Flume Pollable Source Developing a Flume Event-Driven Source Custom Flume Interceptors Developing a Header-Modifying Flume Interceptor Developing a Filtering Flume Interceptor Writing Avro Objects with a Custom Flume Interceptor Managing Workflows with Apache Oozie The Need for Workflow Management What is Apache Oozie? Defining an Oozie Workflow Validation, Packaging, and Deployment Running and Tracking Workflows Using the CLI Hue UI for Oozie Processing Data Pipelines with Apache Crunch What is Apache Crunch? Understanding the Crunch Pipeline Comparing Crunch to Java MapReduce Working with Crunch Projects Reading and Writing Data in Crunch Data Collection API Functions Utility Classes in the Crunch API Working with Tables in Apache Hive What is Apache Hive? Accessing Hive Basic Query Syntax Creating and Populating Hive Tables How Hive Reads Data Using the RegexSerDe in Hive Developing User-Defined Functions What are User-Defined Functions? Implementing a User-Defined Function Deploying Custom Libraries in Hive Registering a User-Defined Function in Hive Executing Interactive Queries with Impala What is Impala? Comparing Hive to Impala Running Queries in Impala Support for User-Defined Functions Data and Metadata Management Understanding Cloudera Search What is Cloudera Search? Search Architecture Supported Document Formats Indexing Data with Cloudera Search Collection and Schema Management Morphlines Indexing Data in Batch Mode Indexing Data in Near Real Time Presenting Results to Users Solr Query Syntax Building a Search UI with Hue Accessing Impala through JDBC Powering a Custom Web Application with Impala and Search

Duration 3 Days 18 CPD hours This course is intended for This course is aimed at anyone who wants to harness the power of data analytics in their organization. Overview After completing this course delegates will be capable of writing effective R code to manipulate, analyse and visualise data to enable their organisations make better, data-driven decisions. This course teaches delegates with no prior programming or data analytics experience how to perform data manipulation, data analysis and data visualisation in R. Course Outline Becoming a world class data analytics practitioner requires mastery of the most sophisticated data analytics tools. The R programming language is one of the most powerful and flexible tools in the data analytics toolkit. This course teaches delegates with no prior programming or data analytics experience how to perform data manipulation, data analysis and data visualisation in R. Mastery of these techniques will allow delegates to immediately add value in their work place by extracting valuable insight from company data to allow better, data-driven decisions. The course will explore the following topics through a series of interactive workshop sessions: What is R? Basic R programming conventions Data structures in R Accessing data in R Descriptive statistics in R Statistical analysis in R Data manipulation in R Data visualisation in R Additional course details: Nexus Humans Beginning Data Analytics With R training program is a workshop that presents an invigorating mix of sessions, lessons, and masterclasses meticulously crafted to propel your learning expedition forward. This immersive bootcamp-style experience boasts interactive lectures, hands-on labs, and collaborative hackathons, all strategically designed to fortify fundamental concepts. Guided by seasoned coaches, each session offers priceless insights and practical skills crucial for honing your expertise. Whether you're stepping into the realm of professional skills or a seasoned professional, this comprehensive course ensures you're equipped with the knowledge and prowess necessary for success. While we feel this is the best course for the Beginning Data Analytics With R course and one of our Top 10 we encourage you to read the course outline to make sure it is the right content for you. Additionally, private sessions, closed classes or dedicated events are available both live online and at our training centres in Dublin and London, as well as at your offices anywhere in the UK, Ireland or across EMEA.

Duration 3 Days 18 CPD hours This course is intended for This course is aimed at anyone who wants to harness the power of data analytics in their organization including: Business Analysts, Data Analysts, Reporting and BI professionals Analytics professionals and Data Scientists who would like to learn Python Overview This course teaches delegates with no prior programming or data analytics experience how to perform data manipulation, data analysis and data visualization in Python. Mastery of these techniques and how to apply them to business problems will allow delegates to immediately add value in their workplace by extracting valuable insight from company data to allow better, data-driven decisions. Outcome: After attending this course, delegates will: Be able to write effective Python code Know how to access their data from a variety of sources using Python Know how to identify and fix data quality using Python Know how to manipulate data to create analysis ready data Know how to analyze and visualize data to drive data driven decisioning across your organization Becoming a world class data analytics practitioner requires mastery of the most sophisticated data analytics tools. These programming languages are some of the most powerful and flexible tools in the data analytics toolkit. From business questions to data analytics, and beyond For data analytics tasks to affect business decisions they must be driven by a business question. This section will formally outline how to move an analytics project through key phases of development from business question to business solution. Delegates will be able: to describe and understand the general analytics process. to describe and understand the different types of analytics can be used to derive data driven solutions to business to apply that knowledge to their business context Basic Python Programming Conventions This section will cover the basics of writing R programs. Topics covered will include: What is Python? Using Anaconda Writing Python programs Expressions and objects Functions and arguments Basic Python programming conventions Data Structures in Python This section will look at the basic data structures that Python uses and accessing data in Python. Topics covered will include: Vectors Arrays and matrices Factors Lists Data frames Loading .csv files into Python Connecting to External Data This section will look at loading data from other sources into Python. Topics covered will include: Loading .csv files into a pandas data frame Connecting to and loading data from a database into a panda data frame Data Manipulation in Python This section will look at how Python can be used to perform data manipulation operations to prepare datasets for analytics projects. Topics covered will include: Filtering data Deriving new fields Aggregating data Joining data sources Connecting to external data sources Descriptive Analytics and Basic Reporting in Python This section will explain how Python can be used to perform basic descriptive. Topics covered will include: Summary statistics Grouped summary statistics Using descriptive analytics to assess data quality Using descriptive analytics to created business report Using descriptive analytics to conduct exploratory analysis Statistical Analysis in Python This section will explain how Python can be used to created more interesting statistical analysis. Topics covered will include: Significance tests Correlation Linear regressions Using statistical output to create better business decisions. Data Visualisation in Python This section will explain how Python can be used to create effective charts and visualizations. Topics covered will include: Creating different chart types such as bar charts, box plots, histograms and line plots Formatting charts Best Practices Hints and Tips This section will go through some best practice considerations that should be adopted of you are applying Python in a business context.

Overview This comprehensive course on Machine Learning with Python 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 with Python comes with accredited certification, 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 with Python. It is available to all students, of all academic backgrounds. Requirements Our Machine Learning with Python 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 Having these various qualifications will increase the value in your CV and open you up to multiple sectors such as Business & Management, Admin, Accountancy & Finance, Secretarial & PA, Teaching & Mentoring etc. Course Curriculum 4 sections • 21 lectures • 01:34:00 total length •Introduction to types of ML algorithm: 00:02:00 •SVM - Python Implementation: 00:06:00 •Introduction to types of ML algorithm: 00:02:00 •Importing a dataset in python: 00:02:00 •Resolving Missing Values: 00:06:00 •Managing Category Variables: 00:04:00 •Training and Testing Datasets: 00:07:00 •Normalizing Variables: 00:02:00 •Normalizing Variables - Python Code: 00:03:00 •Summary: 00:01:00 •Simple Linear Regression - How it works?: 00:04:00 •Simple Linear Regreesion - Python Implementation: 00:07:00 •Multiple Linear Regression - How it works?: 00:01:00 •Multiple Linear Regression - Python Implementation: 00:09:00 •Decision Trees - How it works?: 00:05:00 •Random Forest - How it works?: 00:03:00 •Decision Trees and Random Forest - Python Implementation: 00:04:00 •kNN - How it works?: 00:02:00 •kNN - Python Implementation: 00:10:00 •Decision Tree Classifier and Random Forest Classifier in Python: 00:10:00 •SVM - How it works?: 00:04:00

Overview This comprehensive course on Dialectal Behaviour Therapy (DBT) will deepen your understanding on this topic.After successful completion of this course you can acquire the required skills in this sector. This Dialectal Behaviour Therapy (DBT) comes with accredited certification 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 Dialectal Behaviour Therapy (DBT). It is available to all students, of all academic backgrounds. Requirements Our Dialectal Behaviour Therapy (DBT) is fully compatible with PC's, Mac's, Laptop,Tablet and Smartphone devices. This course has been designed to be fully compatible on tablets and smartphones so you can access your course on wifi, 3G or 4G.There is no time limit for completing this course, it can be studied in your own time at your own pace. Career path Having these various qualifications will increase the value in your CV and open you up to multiple sectors such as Business & Management, Admin, Accountancy & Finance, Secretarial & PA, Teaching & Mentoring etc. Course Curriculum 7 sections • 25 lectures • 02:47:00 total length •About the Instructor: 00:02:00 •About the Course: 00:06:00 •Definition of Counselling: 00:07:00 •Counselling & Psychotherapy: 00:07:00 •Approaches in Counselling & Psychotherapy: 00:12:00 •What is DBT?: 00:05:00 •What is 'dialectical'?: 00:06:00 •History & Philosophy of DBT: 00:06:00 •What is 'Mindfulness': 00:08:00 •What is 'Distress Tolerance': 00:00:00 •What is 'Emotion regulation': 00:11:00 •What is 'Interpersonal Effectiveness': 00:06:00 •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 •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 •How effective is DBT?: 00:07:00 •Criticism and Limitations of DBT: 00:05:00 •Thank You and Good Bye!: 00:04:00

This comprehensive course on AWS Certified Cloud Practitioner (CLF-C01) empowers you to fast-track your IT career. Gain in-depth knowledge of cloud computing, AWS services, and architectural concepts. With hands-on labs, quizzes, and real practice exams, you will confidently build cost-effective, fault-tolerant IT solutions on the AWS Cloud.

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.