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Duration 1 Days 6 CPD hours This course is intended for This course is designed for professionals in a variety of job roles who receive Tableau data visualizations from data analysts or from data visualization engineers. These data report recipients want to take advantage of the many Tableau features and capabilities that enable them to explore the data behind the initial analysis, perform additional analysis to ask next-level questions of the data, and to customize visualizations and dashboards to share new insights and create compelling reports. Overview Explore Tableau reports. Analyze data to get answers and insights. Sort and group data for analysis and reporting. Filter views. Prepare reports. Troubleshoot, collaborate, and share views and analysis As data acquisition, access, analysis, and reporting are interwoven with our businesses and lives, more and more data is collected about business and personal activities. This abundance of data and the computing power to analyze it has increased the use of data analysis and data visualization across a broad range of job roles. Decision makers of all types, including managers and executives, must interact with, interpret, and develop reports based on data and analysis provided to them. Tableau© software is designed for data analysis and the creation of visualizations. Data analysts prepare data, perform initial analysis, and create visualizations that are then passed on to business data-driven decision makers. These decision makers can use Tableau's tools to explore the data, perform further analysis to find new insights, make decisions, and create customized reports to share their findings. Prerequisites To ensure your success in this course, you should have experience managing data with Microsoft© Excel© or Google Sheets? Lesson 1: Exploring Tableau Reports Topic A: Data Analysis Workflow with Tableau Topic B: Explore Views Topic C: Edit Workbooks Lesson 2: Analyzing Data to Get Answers and Insights Topic A: Configure Marks with the Marks Card Topic B: Ask New Questions by Changing Aggregation Topic C: Find Answers with Calculations Topic D: Answer Questions with Table Calculations Lesson 3: Sorting and Grouping Data for Analysis and Reporting Topic A: Sort Data Topic B: Group Data Lesson 4: Filtering Views Topic A: Filter Data to Refine Analysis Topic B: Create Interactive Filters for Reports Lesson 5: Preparing Reports Topic A: Format and Annotate Views to Tell Your Story Topic B: Emphasize Data in Reports Topic C: Animate Visualizations for Clarity Lesson 6: Troubleshooting, Sharing, and Collaborating Topic A: Troubleshoot Data Issues Topic B: Collaborate in Tableau Online Topic C: Collaborate with Non-Tableau Users

Overview Construction management is vast, and the global construction market is forecasted to grow by 85% to $15.5 TRILLION worldwide by 2030. The Diploma in Construction Management becomes an essential learning tool for those aspiring to spearhead this growth. This comprehensive course covers all the critical facts of construction management, equipping students with the essential knowledge and in-demand skills to oversee complex Construction projects seamlessly. This Construction diploma covers everything from the project life cycle to the legal aspects of contracting, giving you a complete understanding of construction management. Key Features of the Course: FREE Construction Management CPD-accredited certificate Get a free student ID card with Construction Management training (£10 applicable for international delivery) Lifetime access to the Construction Management course materials The Construction Management program comes with 24/7 tutor support Get instant access to this Construction Management course Learn Construction Management training from anywhere in the world The Construction Management training is affordable and simple to understand The Construction Management training is an entirely online Description This course provides essential knowledge and skills for managing construction projects effectively. Learn about project planning, budgeting, team coordination, and legal requirements to confidently oversee construction projects from start to finish. Course Curriculum: 1 sections • 18 lectures • 06:43:00 hours total •Module 01: Introduction to Construction Management •Module 02: Project Life Cycle and Success •Module 03: Cost Management •Module 04: Preliminary Site Investigation and Site Organization •Module 05: Site Management •Module 06: Planning and Management of Equipment •Module 07: Construction Materials Management •Module 08: Vendor Analysis in Construction Management •Module 09: Construction Procurement •Module 10: Stock Control •Module 11: Supply Chain Management •Module 12: The Main Participators •Module 13: Quality Assurance and Customer Care •Module 14: Legal Aspects of Contracting •Module 15: Human Resources Management •Module 16: Risk and Value Management •Module 17: Communications, Information and Documentation of Construction •Module 18: Health and Safety in Construction Management Career path Having these various qualifications will increase the value of your CV and open you up to multiple sectors such as: Construction Manager Site Manager Project Manager Quantity Surveyor Estimator Site Engineer Building Surveyor Health and Safety Manager Sustainability Manager General Foreman

Learners will be introduced to the design, installation, commissioning, and maintenance of intruder and hold-up alarm systems.

This practitioner-level 4 award encourages individuals in IT and technical roles to explore the many teams, ideas, and functions within an organisation and maximise their contribution. You will achieve this by learning the key concepts and considering behaviour and response in different scenarios.

This Level 4 course encourages individuals in digital and technical roles to enhance their skills by exploring different techniques, formats, and tools to communicate and understand the impact of their communication choices.

This Level 4 practitioner award encourages individuals in or working towards a leadership role (this could be an IT or technical based-role), and you want to demonstrate modern leadership behaviours to nurture a high-performing team, especially during a time of organisational change.

Do you want to prepare for your dream job but strive hard to find the right courses? Then, stop worrying, for our strategically modified HVAC Engineering bundle will keep you up to date with the relevant knowledge and most recent matters of this emerging field. So, invest your money and effort in our 30 course mega bundle that will exceed your expectations within your budget. The HVAC Engineering related fields are thriving across the UK, and recruiters are hiring the most knowledgeable and proficient candidates. It's a demanding field with magnitudes of lucrative choices. If you need more guidance to specialise in this area and need help knowing where to start, then StudyHub proposes a preparatory bundle. This comprehensive HVAC Engineering bundle will help you build a solid foundation to become a proficient worker in the sector. This HVAC Engineering Bundle consists of the following 25 CPD Accredited Premium courses - Course 01 :Level 3 Heating, Ventilation & Air Conditioning (HVAC) Technician Course 02 :Heat Exchanger Course 03 :PAT Level 4 Course 04 :Smart Meter Installer Training Course 05 :Domestic Appliance Repairing Course Course 06 :Electronic & Electrical Devices Maintenance Course 07 :Electrician Course 08 :Digital Electric Circuits & Intelligent Electrical Devices Course 09 :Electric Power Metering for Single and Three Phase Systems Course 10 :Light Current Systems for Electrical Engineering Course 11 :Basic AC Circuit Analysis Course 12 :Electrical 3 Phase Power Transformers Fundamentals Course 13 :Electrical Power System and High Voltage Engineering Course 14 :Electrical Engineering for Electrical Substations Course 15 :Essential Hydro Electric Power Plant Training Course 16 :Energy Saving in Electric Motors Course 17 :MATLAB Simulink for Electrical Power Engineering Course 18 :MATLAB/Simulink for Power Electronics Simulations Course 19 :Solar Energy Course 20 :Protection and Control of High Voltage Power Circuits Course 21 :Distribution Station & Feeder Protection Course 22 :Electrical and Fire Safety Training - Level 2 Course 23 :Advanced Electrical Safety Course 24 :Workplace Safety Course Course 25 :First Aid at Work 5 Extraordinary Career Oriented courses that will assist you in reimagining your thriving techniques- Course 01 :Business English Perfection Course Course 02 :Networking Skills for Personal Success Course 03 :Boost Your Confidence and Self-Esteem Course 04 :Public Speaking Training Course 05 :Learn to Fight Procrastination Learning Outcome This tailor-made HVAC Engineering bundle will allow you to- Uncover your skills and aptitudes to break new ground in the related fields Deep dive into the fundamental knowledge Acquire some hard and soft skills in this area Gain some transferable skills to elevate your performance Maintain good report with your clients and staff Gain necessary office skills and be tech savvy utilising relevant software Keep records of your work and make a report Know the regulations around this area Reinforce your career with specific knowledge of this field Know your legal and ethical responsibility as a professional in the related field This HVAC Engineering Bundle resources were created with the help of industry experts, and all subject-related information is kept updated on a regular basis to avoid learners from falling behind on the latest developments. Certification After studying the complete training you will be able to take the MCQ test that will assess your knowledge. After successfully passing the test you will be able to claim all courses pdf certificates and 1 hardcopy certificate for the Title Course for free. Other Hard Copy certificates need to be ordered at an additional cost of •8. CPD 300 CPD hours / points Accredited by CPD Quality Standards Who is this course for? Ambitious learners who want to strengthen their CV for their desired job should take advantage of the HVAC Engineering bundle! This bundle is also ideal for professionals looking for career advancement. Requirements To participate in this course, all you need is - A smart device A secure internet connection And a keen interest in HVAC Engineering Career path Upon completing this essential Bundle, you will discover a new world of endless possibilities. These courses will help you to get a cut above the rest and allow you to be more efficient in the relevant fields.

Level 2 NVQ Certificate in Highways Maintenance - Excavation and Reinstatement Operations

Are you ready to be at the helm, steering the ship into a realm where data is the new gold? In the infinite world of data, where information spirals at breakneck speed, lies a universe rich in potential and discovery: the domain of Data Science and Visualisation. This 'Certificate in Data Science and Visualisation with Machine Learning at QLS Level 3' course unravels the wonders of extracting meaningful insights using Python, the worldwide leading language of data experts. Harnessing the strength of Python, you'll delve deep into data analysis, experience the finesse of visualisation tools, and master the art of Machine Learning. The need to understand, interpret, and act on this data has become paramount, with vast amounts of data increasing the digital sphere. Envision a canvas where raw numbers are transformed into visually compelling stories, and machine learning models foretell future trends. This course provides a meticulous pathway for anyone eager to learn the data representation paradigms backed by Python's robust libraries. Dive into a curriculum rich with analytical explorations, visual artistry, and machine learning predictions. Learning Outcomes Understanding the foundations and functionalities of Python, focusing on its application in data science. Applying various Python libraries like NumPy and Pandas for effective data analysis. Demonstrating proficiency in creating detailed visual narratives using tools like matplotlib, Seaborn, and Plotly. Implementing Machine Learning algorithms in Python using scikit-learn, ranging from regression models to clustering techniques. Designing and executing a holistic data analysis and visualisation project, encapsulating all learned techniques. Exploring advanced topics, encompassing recommender systems and natural language processing with Python. Attaining the confidence to independently analyse complex data sets and translate them into actionable insights.   Video Playerhttps://studyhub.org.uk/wp-content/uploads/2021/03/Data-Science-and-Visualisation-with-Machine-Learning.mp400:0000:0000:00Use Up/Down Arrow keys to increase or decrease volume. Why buy this Certificate in Data Science and Visualisation with Machine Learning at QLS Level 3? 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 Certificate in Data Science and Visualisation with Machine Learning at QLS Level 3 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 Certificate in Data Science and Visualisation with Machine Learning at QLS Level 3 course for? Aspiring data scientists aiming to harness the power of Python. Researchers keen to enrich their analytical and visualisation skills. Analysts aiming to add machine learning to their toolkit. Developers striving to integrate data analytics into applications. Business professionals desiring data-driven decision-making capabilities. Career path Data Scientist: £55,000 - £85,000 Per Annum Machine Learning Engineer: £60,000 - £90,000 Per Annum Data Analyst: £30,000 - £50,000 Per Annum Data Visualisation Specialist: £45,000 - £70,000 Per Annum Natural Language Processing Specialist: £65,000 - £95,000 Per Annum Business Intelligence Developer: £40,000 - £65,000 Per Annum Prerequisites This Certificate in Data Science and Visualisation with Machine Learning at QLS Level 3 does not require you to have any prior qualifications or experience. You can just enrol and start learning. This Certificate in Data Science and Visualisation with Machine Learning at QLS Level 3 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. Endorsed Certificate of Achievement from the Quality Licence Scheme Learners will be able to achieve an endorsed certificate after completing the course as proof of their achievement. You can order the endorsed certificate for only £85 to be delivered to your home by post. For international students, there is an additional postage charge of £10. Endorsement The Quality Licence Scheme (QLS) has endorsed this course for its high-quality, non-regulated provision and training programmes. The QLS is a UK-based organisation that sets standards for non-regulated training and learning. This endorsement means that the course has been reviewed and approved by the QLS and meets the highest quality standards. Please Note: Studyhub is a Compliance Central approved resale partner for Quality Licence Scheme Endorsed courses. Course Curriculum Welcome, Course Introduction & overview, and Environment set-up Welcome & Course Overview 00:07:00 Set-up the Environment for the Course (lecture 1) 00:09:00 Set-up the Environment for the Course (lecture 2) 00:25:00 Two other options to setup environment 00:04:00 Python Essentials Python data types Part 1 00:21:00 Python Data Types Part 2 00:15:00 Loops, List Comprehension, Functions, Lambda Expression, Map and Filter (Part 1) 00:16:00 Loops, List Comprehension, Functions, Lambda Expression, Map and Filter (Part 2) 00:20:00 Python Essentials Exercises Overview 00:02:00 Python Essentials Exercises Solutions 00:22:00 Python for Data Analysis using NumPy What is Numpy? A brief introduction and installation instructions. 00:03:00 NumPy Essentials - NumPy arrays, built-in methods, array methods and attributes. 00:28:00 NumPy Essentials - Indexing, slicing, broadcasting & boolean masking 00:26:00 NumPy Essentials - Arithmetic Operations & Universal Functions 00:07:00 NumPy Essentials Exercises Overview 00:02:00 NumPy Essentials Exercises Solutions 00:25:00 Python for Data Analysis using Pandas What is pandas? A brief introduction and installation instructions. 00:02:00 Pandas Introduction 00:02:00 Pandas Essentials - Pandas Data Structures - Series 00:20:00 Pandas Essentials - Pandas Data Structures - DataFrame 00:30:00 Pandas Essentials - Handling Missing Data 00:12:00 Pandas Essentials - Data Wrangling - Combining, merging, joining 00:20:00 Pandas Essentials - Groupby 00:10:00 Pandas Essentials - Useful Methods and Operations 00:26:00 Pandas Essentials - Project 1 (Overview) Customer Purchases Data 00:08:00 Pandas Essentials - Project 1 (Solutions) Customer Purchases Data 00:31:00 Pandas Essentials - Project 2 (Overview) Chicago Payroll Data 00:04:00 Pandas Essentials - Project 2 (Solutions Part 1) Chicago Payroll Data 00:18:00 Python for Data Visualization using matplotlib Matplotlib Essentials (Part 1) - Basic Plotting & Object Oriented Approach 00:13:00 Matplotlib Essentials (Part 2) - Basic Plotting & Object Oriented Approach 00:22:00 Matplotlib Essentials (Part 3) - Basic Plotting & Object Oriented Approach 00:22:00 Matplotlib Essentials - Exercises Overview 00:06:00 Matplotlib Essentials - Exercises Solutions 00:21:00 Python for Data Visualization using Seaborn Seaborn - Introduction & Installation 00:04:00 Seaborn - Distribution Plots 00:25:00 Seaborn - Categorical Plots (Part 1) 00:21:00 Seaborn - Categorical Plots (Part 2) 00:16:00 Seborn-Axis Grids 00:25:00 Seaborn - Matrix Plots 00:13:00 Seaborn - Regression Plots 00:11:00 Seaborn - Controlling Figure Aesthetics 00:10:00 Seaborn - Exercises Overview 00:04:00 Seaborn - Exercise Solutions 00:19:00 Python for Data Visualization using pandas Pandas Built-in Data Visualization 00:34:00 Pandas Data Visualization Exercises Overview 00:03:00 Panda Data Visualization Exercises Solutions 00:13:00 Python for interactive & geographical plotting using Plotly and Cufflinks Plotly & Cufflinks - Interactive & Geographical Plotting (Part 1) 00:19:00 Plotly & Cufflinks - Interactive & Geographical Plotting (Part 2) 00:14:00 Plotly & Cufflinks - Interactive & Geographical Plotting Exercises (Overview) 00:11:00 Plotly & Cufflinks - Interactive & Geographical Plotting Exercises (Solutions) 00:37:00 Capstone Project - Python for Data Analysis & Visualization Project 1 - Oil vs Banks Stock Price during recession (Overview) 00:15:00 Project 1 - Oil vs Banks Stock Price during recession (Solutions Part 1) 00:18:00 Project 1 - Oil vs Banks Stock Price during recession (Solutions Part 2) 00:18:00 Project 1 - Oil vs Banks Stock Price during recession (Solutions Part 3) 00:17:00 Project 2 (Optional) - Emergency Calls from Montgomery County, PA (Overview) 00:03:00 Python for Machine Learning (ML) - scikit-learn - Linear Regression Model Introduction to ML - What, Why and Types.. 00:15:00 Theory Lecture on Linear Regression Model, No Free Lunch, Bias Variance Tradeoff 00:15:00 scikit-learn - Linear Regression Model - Hands-on (Part 1) 00:17:00 scikit-learn - Linear Regression Model Hands-on (Part 2) 00:19:00 Good to know! How to save and load your trained Machine Learning Model! 00:01:00 scikit-learn - Linear Regression Model (Insurance Data Project Overview) 00:08:00 scikit-learn - Linear Regression Model (Insurance Data Project Solutions) 00:30:00 Python for Machine Learning - scikit-learn - Logistic Regression Model Theory: Logistic Regression, conf. mat., TP, TN, Accuracy, Specificityetc. 00:10:00 scikit-learn - Logistic Regression Model - Hands-on (Part 1) 00:17:00 scikit-learn - Logistic Regression Model - Hands-on (Part 2) 00:20:00 scikit-learn - Logistic Regression Model - Hands-on (Part 3) 00:11:00 scikit-learn - Logistic Regression Model - Hands-on (Project Overview) 00:05:00 scikit-learn - Logistic Regression Model - Hands-on (Project Solutions) 00:15:00 Python for Machine Learning - scikit-learn - K Nearest Neighbors Theory: K Nearest Neighbors, Curse of dimensionality . 00:08:00 scikit-learn - K Nearest Neighbors - Hands-on 00:25:00 scikt-learn - K Nearest Neighbors (Project Overview) 00:04:00 scikit-learn - K Nearest Neighbors (Project Solutions) 00:14:00 Python for Machine Learning - scikit-learn - Decision Tree and Random Forests Theory: D-Tree & Random Forests, splitting, Entropy, IG, Bootstrap, Bagging. 00:18:00 scikit-learn - Decision Tree and Random Forests - Hands-on (Part 1) 00:19:00 scikit-learn - Decision Tree and Random Forests (Project Overview) 00:05:00 scikit-learn - Decision Tree and Random Forests (Project Solutions) 00:15:00 Python for Machine Learning - scikit-learn -Support Vector Machines (SVMs) Support Vector Machines (SVMs) - (Theory Lecture) 00:07:00 scikit-learn - Support Vector Machines - Hands-on (SVMs) 00:30:00 scikit-learn - Support Vector Machines (Project 1 Overview) 00:07:00 scikit-learn - Support Vector Machines (Project 1 Solutions) 00:20:00 scikit-learn - Support Vector Machines (Optional Project 2 - Overview) 00:02:00 Python for Machine Learning - scikit-learn - K Means Clustering Theory: K Means Clustering, Elbow method .. 00:11:00 scikit-learn - K Means Clustering - Hands-on 00:23:00 scikit-learn - K Means Clustering (Project Overview) 00:07:00 scikit-learn - K Means Clustering (Project Solutions) 00:22:00 Python for Machine Learning - scikit-learn - Principal Component Analysis (PCA) Theory: Principal Component Analysis (PCA) 00:09:00 scikit-learn - Principal Component Analysis (PCA) - Hands-on 00:22:00 scikit-learn - Principal Component Analysis (PCA) - (Project Overview) 00:02:00 scikit-learn - Principal Component Analysis (PCA) - (Project Solutions) 00:17:00 Recommender Systems with Python - (Additional Topic) Theory: Recommender Systems their Types and Importance 00:06:00 Python for Recommender Systems - Hands-on (Part 1) 00:18:00 Python for Recommender Systems - - Hands-on (Part 2) 00:19:00 Python for Natural Language Processing (NLP) - NLTK - (Additional Topic) Natural Language Processing (NLP) - (Theory Lecture) 00:13:00 NLTK - NLP-Challenges, Data Sources, Data Processing .. 00:13:00 NLTK - Feature Engineering and Text Preprocessing in Natural Language Processing 00:19:00 NLTK - NLP - Tokenization, Text Normalization, Vectorization, BoW. 00:19:00 NLTK - BoW, TF-IDF, Machine Learning, Training & Evaluation, Naive Bayes 00:13:00 NLTK - NLP - Pipeline feature to assemble several steps for cross-validation 00:09:00 Resources Resources - Data Science and Visualisation with Machine Learning 00:00:00 Order your QLS Endorsed Certificate Order your QLS Endorsed Certificate 00:00:00