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
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Overview of Maintenance Manager The Maintenance Manager course is designed to help you become a skilled professional in the growing field of facilities management. With the UK facilities management sector contributing over £120 billion each year, Maintenance Managers are in high demand. This course covers everything you need to know, from basic handyperson tasks to advanced electrical work and risk assessments. Whether you’re fixing plumbing issues, troubleshooting appliances, or learning carpentry, this course gives you the practical skills to succeed. As buildings become more complex, the role of a Maintenance Manager becomes even more important. You’ll learn how to handle a wide variety of maintenance tasks, including electrical work, construction projects, and health and safety protocols. This knowledge ensures that you are ready to take on challenges in both residential and commercial properties. You will be able to carry out repairs and improvements that meet the latest regulations and safety standards. Qualified Maintenance Managers are highly valued, and with the knowledge and skills you develop in this course, you will be prepared to manage maintenance tasks efficiently and effectively. With training in essential areas like plumbing, electrical systems, and safety compliance, this course positions you for success in a fast-growing industry where the demand for qualified professionals is rising. By the end of the Maintenance Manager course, you will be able to: Master practical plumbing and carpentry techniques for effective maintenance. Apply health and safety standards to all maintenance tasks. Perform basic electrical repairs while adhering to safety regulations. Gain skills in painting, decorating, and floor installations. Carry out risk assessments for maintenance activities accurately. Install and repair common household appliances and fixtures. Who is this course for Property managers looking to enhance their maintenance skills and save on outsourcing costs. Facilities supervisors who want to improve their technical knowledge of building systems and repairs. Building caretakers aiming to expand their abilities and take on more responsibilities. DIY enthusiasts interested in formalising their knowledge and transitioning to a professional maintenance career. Career changers seeking a solid foundation in maintenance management to enter the field. Process of Evaluation After studying the Maintenance Manager Course, your skills and knowledge will be tested with an MCQ exam or assignment. You have to get a score of 60% to pass the test and get your certificate. Certificate of Achievement Certificate of Completion - Digital / PDF Certificate After completing the Maintenance Manager Course, you can order your CPD Accredited Digital / PDF Certificate for £5.99. (Each) Certificate of Completion - Hard copy Certificate You can get the CPD Accredited Hard Copy Certificate for £12.99. (Each) Shipping Charges: Inside the UK: £3.99 International: £10.99 Requirements You don't need any educational qualification or experience to enrol in the Maintenance Manager course. Career Path After completing the Maintenance Manager course, you can explore roles such as: Maintenance Manager - £35K to £50K/year Facilities Coordinator - £25K to £38K/year Building Services Supervisor - £30K to £45K/year Estate Maintenance Officer - £28K to £42K/year Property Maintenance Manager - £32K to £48K/year Course Curriculum Module 01: Introduction To Handyperson 00:20:00 Module 02: Basic Tools And Equipment 00:22:00 Module 03: Plumbing Skills 00:19:00 Module 04: Appliances 00:18:00 Module 05: General Carpentry 00:26:00 Module 06: Basic Maintenance Skills 00:14:00 Module 07: Walls And Floors 00:19:00 Module 08: Painting And Decorating 00:17:00 Module 09: Drilling, Tiling And Welding 00:22:00 Module 10: Construction Projects 00:15:00 Module 11: Health and Safety at Work 00:27:00 Module 12: Electrical Work 00:23:00 Module 13: Working Safely With Electrical Equipment 00:17:00 Module 14: Electrical Incidents 00:10:00 Module 15: Risk Assessment 00:23:00 Module 16: Reducing And Controlling Risks 00:21:00 Module 17: Combined Inspection And Testing 00:37:00
Diploma in Employment Law will assist you in producing the best possible outcome by mastering the skills. Those who want to succeed must enrol in the course Diploma in Employment Law. By completing this course, you will acquire the skills required to become an expert in a comparable field. The basics of our Diploma in Employment Law course are covered first, and then we move on to more advanced material. The lessons in this Diploma in Employment Law course are therefore clear and easy to understand. Diploma in Employment Law Course Basic Learning Outcomes: After completing this highly appreciated Diploma in Employment Law course, you'll be a competent expert, besides- You can give assistance related to the Diploma in Employment Law with complete knowledge and confidence. You'll be competent and proficient enough to explore Diploma in Employment Law related job fields on your own. Furthermore, you can train up others and grow an efficient peer community in your locality and serve people. It will enhance your portfolio, you can use the certificate as proof of your efficiency to the employer. It will boost up your productivity, you can use the skill and credentials, and become more competent in your vocation with increased earning! Key Highlights of Diploma in Employment Law Course: CPD Accredited Course Unlimited Retake Exam & Tutor Support Easy Accessibility to the Course Materials 100% Learning Satisfaction Guarantee Lifetime Access & 24/7 Support Self-paced Course Modules Covers to Explore Multiple Job Positions Curriculum Breakdown of the Course:- Module 01: Basic of Employment Law Module 02: Legal Recruitment Process Module 03: Employment Contracts Module 04: Employee Handbook Module 05: Disciplinary Procedure Module 06: National Minimum Wage & National Living Wage Module 07: Parental Right, Sick Pay & Pension Scheme Module 08: Discrimination in the Workplace Module 09: Health & Safety at Work Module 10: Dismissal, Grievances and Employment Tribunals Module 11: Workplace Monitoring & Data Protection Certification: CPD Accredited (CPD QS) Certificate Digital (PDF) & Hardcopy certificates are available CPD 60 CPD hours / points Accredited by CPD Quality Standards Who is this course for? Anyone from any background can enrol in this Diploma in Employment Law course. This course particularly recommended for- Students Recent graduates Job Seekers Anyone interested in this topic People already working in the relevant fields and want to polish their knowledge and skill. Requirements Students seeking to enrol for Diploma in Employment Law course should meet the following requirements; Basic knowledge of English Language Be age 16 years or above Basic Knowledge of Information & Communication Technologies for studying online or digital platforms. Stable Internet or Data connection in your learning devices. Career path After completing this course, you can explore trendy and in-demand jobs related to Diploma in Employment Law. Explore each of the roles available and how you can start your career in this platform. Certificates Certificate of completion Digital certificate - Included After successfully completing this course, you can get CPD accredited digital PDF certificate for free. Certificate of completion Hard copy certificate - £9.99 After successfully completing this course, you can get CPD accredited hardcopy certificate for free. The delivery charge of the hardcopy certificate inside the UK is £3.99 and international students need to pay £9.99 to get their hardcopy certificate.
Take your first step toward Natural Language Processing with this beginner-to-pro course. Gain an in-depth understanding of deep learning models for NLP with the help of examples. Learn the essential concepts from the absolute beginning with complete unraveling along with examples in Python.