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464 Machine Learning (ML) courses in Glasgow delivered On Demand
Complete Data Analysis Course
By Wise Campus
Data Analysis: Data Analysis Course Would you like to acquire the skills and self-assurance necessary to make wise choices and successfully traverse the intricate and ever-changing realm of data analysis? Enrol in our Data Analysis Course. The fundamentals of data, statistics, and an introduction to data analysis are all covered in this data analysis course. The how-to of data collection and its sources are explained in the Data Analysis Course. This Data Analysis Course teaches preprocessing, data cleansing, and exploratory data analysis (EDA). An overview of Excel and Python for data analysis is explained in this Data Analysis Course. This extensive Data Analysis course includes lessons on data wrangling with Pandas (Python) and data visualisation using Matplotlib and Seaborn (Python). So, quickly join our Data Analysis Course to learn the fundamentals of machine learning and statistical analysis! Special Offers with free gifts for this Data Analysis: Data Analysis Course This Data Analysis Course course includes a FREE PDF Certificate. Lifetime access to this Data Analysis Course course Instant access to this Data Analysis Course course Get FREE Tutor Support to this Data Analysis Course Course Learning Outcome of Data Analysis Course This Data Analysis Course will help you learn about: Introduction to data analysis, basics of data, and statistics. Data Analysis Course explains how to collect data and its sources. Data cleaning, processing, and exploratory data analysis (EDA) are included in this Data Analysis Course. This Data Analysis Course describes an introduction to Excel for Data Analysis and Python for Data Analysis. Data Wrangling with Pandas (Python) and Data Visualisation with Matplotlib and Seaborn (Python) are parts of this comprehensive Data Analysis Course. With the help of this Data Analysis Course, you will learn the basics of statistical analysis and machine learning. Data Analysis: Data Analysis Course Embark on a transformative journey with our Data Analysis course, designed for beginners. Dive deep into the world of data analysis, mastering essential techniques and tools. Gain practical skills in Data Analysis, empowering you to unlock insights and drive informed decisions. Start your Data Analysis journey today! Who is this course for? Data Analysis: Data Analysis Course Anyone looking to have a thorough grasp of data analysis in a commercial setting should take this Data Analysis: Data Analysis Course. Requirements Data Analysis: Data Analysis Course To enrol in this Data Analysis: Data Analysis Course, students must fulfil the following requirements. To join in our Data Analysis: Data Analysis Course, you must have a strong command of the English language. To successfully complete our Data Analysis: Data Analysis Course, you must be vivacious and self driven. To complete our Data Analysis: Data Analysis Course, you must have a basic understanding of computers. A minimum age limit of 15 is required to enrol in this Data Analysis: Data Analysis Course. Career path Data Analysis: Data Analysis Course With the assistance of this Data Analysis Course, you can obtain work as a data analyst, business analyst, marketing analyst, or in related fields.
Let’s face it—no one enjoys spending hours battling stubborn weeds that just keep coming back. Whether you're managing a garden, farm, or green space, knowing your enemy is half the battle. This Weed Recognition and Management Course gives you the upper hand, helping you spot the troublemakers before they spread and take over. You'll learn how to identify common (and not-so-common) weeds by their features, growth habits, and seasonal patterns—saving you time, effort, and a good bit of frustration. This course goes beyond pulling up dandelions and hoping for the best. It offers smart strategies for weed control, covering chemical, biological, and cultural methods used across the UK. Whether you're new to plant care or already knee-deep in the gardening game, the course is clear, informative, and easy to follow. Everything is online, meaning you can learn at your own pace without muddy boots or sunburn. Key Features CPD Accredited FREE PDF + Hardcopy certificate Fully online, interactive course Self-paced learning and laptop, tablet and smartphone-friendly 24/7 Learning Assistance Discounts on bulk purchases Course Curriculum Module 01: Introduction to Weeds and Their Impact Module 02: Weed Identification Module 03: Weed Biology and Ecology Module 04: Physical and Cultural Weed Control Methods Module 05: Chemical Weed Control Methods Module 06: Integrated Weed Management Learning Outcomes Recognize diverse weed species through advanced identification techniques. Understand the intricate biology and ecology of weeds for effective management. Apply physical and cultural methods to control weeds in various environments. Implement chemical weed control strategies with precision and environmental consciousness. Master integrated weed management for a holistic and sustainable approach. Develop expertise in weed recognition and management for practical application. Accreditation This course is CPD Quality Standards (CPD QS) accredited, providing you with up-to-date skills and knowledge and helping you to become more competent and effective in your chosen field. Certificate After completing this course, you will get a FREE Digital Certificate from Training Express. CPD 10 CPD hours / points Accredited by CPD Quality Standards Who is this course for? Agriculture professionals seeking advanced weed management knowledge. Environmentalists aiming to contribute to ecosystem preservation. Farmers looking to enhance crop yield through effective weed control. Horticulturists interested in sustainable and integrated weed management. Landscapers desiring in-depth knowledge of weed dynamics. Conservationists striving to protect native flora and fauna. Botanists keen on understanding the ecological impact of different weed species. Individuals passionate about sustainable agriculture and environmental stewardship. Career path Agricultural Consultant Environmental Scientist Crop Protection Specialist Ecological Restoration Technician Horticulture Manager Conservation Officer Certificates Digital certificate Digital certificate - Included Once you've successfully completed your course, you will immediately be sent a FREE digital certificate. Hard copy certificate Hard copy certificate - Included Also, you can have your FREE printed certificate delivered by post (shipping cost £3.99 in the UK). For all international addresses outside of the United Kingdom, the delivery fee for a hardcopy certificate will be only £10. Our certifications have no expiry dates, although we do recommend that you renew them every 12 months.
Fraud isn’t just a threat—it’s a costly nuisance that keeps evolving. The Fraud Detection and Prevention Insights Course offers a sharp and timely perspective into how fraud manifests across various sectors, and what can be done to stop it in its tracks. Learners are guided through emerging patterns, warning signs, and the strategic thinking used to analyse suspicious activity with precision. It’s not about ticking off tasks—it’s about understanding the game fraudsters play. Whether you’re responsible for protecting sensitive data or you're simply tired of second-guessing red flags, this course delivers clarity without fluff. With focused insights into fraudulent tactics, digital security weaknesses, and decision-making techniques, you’ll build confidence in identifying problems before they snowball. No drama, no jargon—just straight-talking knowledge from experts who’ve seen it all. Key Features CPD Accredited FREE PDF + Hardcopy certificate Fully online, interactive course Self-paced learning and laptop, tablet and smartphone-friendly 24/7 Learning Assistance Discounts on bulk purchases Course Curriculum Module 01: An Overview of Fraud Module 02: Types of Fraud Module 03: Banking Frauds Module 04: Fraud Prevention Module 05: Fraud Detection Module 06: Fraud Evidence Module 07: Fraud Response Module 08: Fraud Investigations Module 09: Bribery Module 10: Laws & Legislation and Court Room Learning Outcomes: Identify various fraud types for proactive prevention. Implement effective strategies to detect and investigate banking frauds. Analyse and present compelling fraud evidence in legal contexts. Develop a robust response plan to mitigate the impact of fraud. Navigate bribery challenges through informed decision-making. Demonstrate a comprehensive understanding of relevant laws and legislation. Accreditation This course is CPD Quality Standards (CPD QS) accredited, providing you with up-to-date skills and knowledge and helping you to become more competent and effective in your chosen field. Certificate After completing this course, you will get a FREE Digital Certificate from Training Express. CPD 10 CPD hours / points Accredited by CPD Quality Standards Who is this course for? Finance professionals seeking fraud expertise. Law enforcement personnel focusing on financial crimes. Risk management specialists enhancing fraud prevention skills. Legal professionals involved in fraud-related cases. Auditors aiming to strengthen fraud detection capabilities. Compliance officers ensuring adherence to anti-fraud measures. Corporate investigators tackling internal fraud challenges. Students pursuing a career in fraud detection and prevention. Career path Fraud Analyst Financial Investigator Compliance Officer Forensic Accountant Risk Management Specialist Banking Security Consultant Certificates Digital certificate Digital certificate - Included Once you've successfully completed your course, you will immediately be sent a FREE digital certificate. Hard copy certificate Hard copy certificate - Included Also, you can have your FREE printed certificate delivered by post (shipping cost £3.99 in the UK). For all international addresses outside of the United Kingdom, the delivery fee for a hardcopy certificate will be only £10. Our certifications have no expiry dates, although we do recommend that you renew them every 12 months.
HOW TO USE A SEWING MACHINE
By Fashion Rebellion
Do you want to learn to use a sewing machine but don’t know where to start? YOUR SEWING JOURNEY STARTS HERE I’ve been teaching complete beginners to sew since 2009 LEARN A LIFE-SKILL, SAVE MONEY & BOOST FEELINGS OF WELLBEING I’ve created an online video course based on my successful classes running since 2009 using the easiest-to-follow methods. It’s been tried & tested by children as young as 8 years old for a whole year….They LOVED it & we guarantee you will too! THIS COURSE IS FOR ANYONE AGED 10-100 YEARS If you’re a beginner your age doesn’t matter! Both children & adults have used this course with ease. In fact the kids are often quicker learners! ✂️ THINKING ABOUT BUYING A SEWING MACHINE? My advice is to buy BASIC. No whistles & bells! As long as the machine can do a straight stitch & a zig zag stitch that’s all you’ll need. Most machines have a few embroidery stitches too. Avoid toy machines & go for the most basic version of a good brand. USING OUR HANDS CREATIVELY IS PROVEN TO MAKE US 🖐✂️🧵😃 FEEL HAPPY 😃🧵✂️🖐 You can do everything you need on a basic machine including free style embroyery Amanda Recommends… WHAT YOU’LL LEARN BLOCK 1 - FIRST THINGS FIRST ✔️Let’s look at a sewing machine ✔️Speed control & turning corners ✔️How to sew a seam ✔️How to pin, cut & place a template BLOCK 2 - THREADING UP ✔️Winding a bobbin ✔️The top thread-up ✔️Inserting a bobbin on top loaders ✔️Inserting a bobbin on front loaders BLOCK 3 - SEW A SUNGLASSES CASE ✔️Practise what you’ve learned & achieve your first little project make ✔️Learn all about backstitch & why it’s important BLOCK 4 - ALL THE HELP YOU'LL NEED ✔️How to solve stitching issues ✔️Choosing & changing needles ✔️Getting unstuck ✔️Looking after your machine LEARNING TO SEW HAS COUNTLESS BENEFITS….. Sewing helps to extend focus & concentration. As we must concentrate for longer periods of time. It’s great for those who struggle to stay focused. It reduces time spent on social media. Instead of scrolling we use our hands creatively making. Sewing promotes good mental health. It increases self-esteem through empowerment & creativity. It makes us happy! Dexterity & hand strength improve. Cutting, pinning & making are ways of strengthening hands our tools for life! We help to save the planet by extending the life of clothes. Clothing won’t end up in landfill if we upcycle it. Extending the life of clothes by 9 months reduces their carbon footprint by 20-30% It teaches us how to save money. It’s a useful life-skill we can use to alter, update, customise, remake or repair instead of buying new things. It’s such a great feeling to be able to say “ I made it myself” WHAT DO I NEED? Not that much! You’ve probably got most things at home already. ✂️🧵📍✏️🎧👖📄📏 You can learn at your own speed at home or sew with your friends It’s much cheaper than attending classes MEET YOUR INSTRUCTOR…..AMANDA RILEY Amanda Riley is a Fashion Designer & environmentalist. She has been teaching complete beginners the art of diy fashion and eco-sewing since 2009. After realising the horrendous environmental impact of fashion she started her masterclass workshops at The Fashion Factory, for 8-16 year olds as an antidote to fast fashion. “ I saw an increase in social media use & the reduction of practical & creative subjects in schools. Many children are missing out on life skills, creativity, dexterity & the ability to focus. I felt I had to do something” “My eco-sewing programme focuses on learning via upcycling unwanted textiles into cool new stuff. The products & video lessons are designed to keep young people engaged and coming back for more. I’ve ripped up the sewing rule books and introduced a new way of learning this hugely rewarding life skill.” Her students have appeared in Vogue, in the Fashion Factory book (Amazon) & many have gone on to study for creative careers. She was selected as a top 100 changemaker in 2021 by the Big Issue.
Online Options
Show all 551Machine Learning for Absolute Beginners - Level 1
By Packt
This course will take you through the fundamental concepts of machine learning (ML) and artificial intelligence (AI). By the end of this course, you will be ready to dive into the advanced concepts of ML.
Projects in Machine Learning: From Beginner to Professional
By Packt
This course covers the basic concepts of machine learning (ML) that are crucial for getting started on the journey of becoming a skilled ML developer. You will become familiar with different algorithms and networks, such as supervised, unsupervised, neural networks, Convolutional Neural Network (CNN), and Super-Resolution Convolutional Neural Network (SRCNN), needed to develop effective ML solutions.
Certified Artificial Intelligence Practitioner
By Mpi Learning - Professional Learning And Development Provider
This course shows you how to apply various approaches and algorithms to solve business problems through AI and ML, follow a methodical workflow to develop sound solutions, use open-source, off-the-shelf tools to develop, test, and deploy those solutions, and ensure that they protect the privacy of users. This course includes hands-on activities for each topic area.
EXIN BCS Artificial Intelligence Foundation
By Nexus Human
Duration 3 Days 18 CPD hours This course is intended for The EXIN BCS Artificial Intelligence Foundation certification is focused on individuals with an interest in, (or need to implement) AI in an organization, especially those working in areas such as science, engineering, knowledge engineering, finance, education or IT services. Overview You will be able to Describe how Artificial (AI) is Part of 'Universal Design', and 'The Fourth Industrial Revolution' Demonstrate Understanding of the Artificial Intelligence (AI) Intelligen Agent Description Explain the Benefits of Artificial Intelligence (AI) Describe how we Learn from Data - Functionality, Software and Hardware Demonstrate an Understanding that Artificial Intelligence (AI) (in Particular, Machine Learning (ML)) will Drive Humans and Machines to Work Together Describe a ''Learning from Experience'' Agile Approach to Projects Candidates should be able to demonstrate a knowledge and understanding in the application of ethical and sustainable Artificial Intelligence (AI):- Human-centric Ethical and Sustainable Human and Artificial Intelligence (AI) Ethical and Sustainable Human and Artificial Intelligence (AI) Recall the General Definition of Human and Artificial Intelligence (AI) Describe what are Ethics and Trustworthy Artificial Intelligence (AI) Describe the Three Fundamental Areas of Sustainability and the United Nationïs Seventeen Sustainability Goals Describe how Artificial Intelligence (AI) is Part of 'Universal Design', and 'The Fourth Industrial Revolution' Understand that Machine Learning (ML) is a Significant Contribution to the Growth of Artificial Intelligence (AI) Artificial Intelligence (AI) and Robotics Demonstrate Understanding of the Artificial Intelligence (AI) Intelligent Agent Description Describe what a Robot is Describe what an intelligent Robot is Applying the Benefits of Artificial Intelligence (AI) ? Challenges and Risks Describe how Sustainability Relates to Human-Centric Ethical Artificial Intelligence (AI) and how our Values will Drive our use of Artificial Intelligence (AI) and will Change Humans, Society and Organizations Explain the Benefits of Artifical Intelligence (AI) Describe the Challenges of Artificial Intelligence (AI) Projects Demonstrate Understanding of the Risks of Artificial Intelligence (AI) Projects List Opportunities for Artificial Intelligence (AI) Identify a Typical Funding Source for Artificial Intelligence (AI) Projects and Relate to the NASA Technology Readiness Levels (TRLs) Starting Artificial Intelligence (AI): how to Build a Machine Learning (ML) Toolbox ? Theory and Practice Describe how we Learn from Data - Functionality, Software and Hardware Recall which Rypical, Narrow Artificial Intelligence (AI) Capability is Useful in Machine Learning (ML9 and Artificial Intelligence (AI) AgentsïFunctionality The Management, Roles and Responsibilities of Humans and Machines Demonstrate an Understanding that Artificial Intelligence (AI) (in Particular, Machine Learning (ML)) will Drive Humans and Machines to Work Together List Future Directions of Humans and Machines Working Together Describe a ''Learning from Experience'' Agile Approach to Projects
CertNexus Certified Artificial Intelligence Practitioner CAIP (AIP-210)
By Nexus Human
Duration 5 Days 30 CPD hours This course is intended for The skills covered in this course converge on four areas-software development, IT operations, applied math and statistics, and business analysis. Target students for this course should be looking to build upon their knowledge of the data science process so that they can apply AI systems, particularly machine learning models, to business problems. So, the target student is likely a data science practitioner, software developer, or business analyst looking to expand their knowledge of machine learning algorithms and how they can help create intelligent decisionmaking products that bring value to the business. A typical student in this course should have several years of experience with computing technology, including some aptitude in computer programming. This course is also designed to assist students in preparing for the CertNexus Certified Artificial Intelligence (AI) Practitioner (Exam AIP-210) certification Overview In this course, you will develop AI solutions for business problems. You will: Solve a given business problem using AI and ML. Prepare data for use in machine learning. Train, evaluate, and tune a machine learning model. Build linear regression models. Build forecasting models. Build classification models using logistic regression and k -nearest neighbor. Build clustering models. Build classification and regression models using decision trees and random forests. Build classification and regression models using support-vector machines (SVMs). Build artificial neural networks for deep learning. Put machine learning models into operation using automated processes. Maintain machine learning pipelines and models while they are in production Artificial intelligence (AI) and machine learning (ML) have become essential parts of the toolset for many organizations. When used effectively, these tools provide actionable insights that drive critical decisions and enable organizations to create exciting, new, and innovative products and services. This course shows you how to apply various approaches and algorithms to solve business problems through AI and ML, all while following a methodical workflow for developing data-driven solutions. Solving Business Problems Using AI and ML Topic A: Identify AI and ML Solutions for Business Problems Topic B: Formulate a Machine Learning Problem Topic C: Select Approaches to Machine Learning Preparing Data Topic A: Collect Data Topic B: Transform Data Topic C: Engineer Features Topic D: Work with Unstructured Data Training, Evaluating, and Tuning a Machine Learning Model Topic A: Train a Machine Learning Model Topic B: Evaluate and Tune a Machine Learning Model Building Linear Regression Models Topic A: Build Regression Models Using Linear Algebra Topic B: Build Regularized Linear Regression Models Topic C: Build Iterative Linear Regression Models Building Forecasting Models Topic A: Build Univariate Time Series Models Topic B: Build Multivariate Time Series Models Building Classification Models Using Logistic Regression and k-Nearest Neighbor Topic A: Train Binary Classification Models Using Logistic Regression Topic B: Train Binary Classification Models Using k-Nearest Neighbor Topic C: Train Multi-Class Classification Models Topic D: Evaluate Classification Models Topic E: Tune Classification Models Building Clustering Models Topic A: Build k-Means Clustering Models Topic B: Build Hierarchical Clustering Models Building Decision Trees and Random Forests Topic A: Build Decision Tree Models Topic B: Build Random Forest Models Building Support-Vector Machines Topic A: Build SVM Models for Classification Topic B: Build SVM Models for Regression Building Artificial Neural Networks Topic A: Build Multi-Layer Perceptrons (MLP) Topic B: Build Convolutional Neural Networks (CNN) Topic C: Build Recurrent Neural Networks (RNN) Operationalizing Machine Learning Models Topic A: Deploy Machine Learning Models Topic B: Automate the Machine Learning Process with MLOps Topic C: Integrate Models into Machine Learning Systems Maintaining Machine Learning Operations Topic A: Secure Machine Learning Pipelines Topic B: Maintain Models in Production
Thinking about learning more about Artificial Intelligence? The BCS Foundation Certificate in Artificial Intelligence is the advanced version of our Essentials Course Artificial Intelligence and includes more detail and insights about algebraic equations, vector calculus and schematics used in artificial intelligence and machine learning for you to learn how this new technology works.
Machine Learning for Predictive Maps in Python and Leaflet - Level 5 (QLS Endorsed)
By Kingston Open College
QLS Endorsed + CPD QS Accredited - Dual Certification | Instant Access | 24/7 Tutor Support
The Comprehensive Android Developer Bootcamp
By Packt
Learn new Android APIs such as RoomDatabase, ML Kit for face recognition, Cloud Firestore, Firebase, Maps, and the Android Studio IDE (integrated development environment)
The Complete Machine Learning Course with Python
By Packt
Build a Portfolio of 12 Machine Learning Projects with Python, SVM, Regression, Unsupervised Machine Learning & More!
The Machine Learning Pipeline on AWS
By Nexus Human
Duration 4 Days 24 CPD hours This course is intended for This course is intended for: Developers Solutions Architects Data Engineers Anyone with little to no experience with ML and wants to learn about the ML pipeline using Amazon SageMaker Overview In this course, you will learn to: Select and justify the appropriate ML approach for a given business problem Use the ML pipeline to solve a specific business problem Train, evaluate, deploy, and tune an ML model using Amazon SageMaker Describe some of the best practices for designing scalable, cost-optimized, and secure ML pipelines in AWS Apply machine learning to a real-life business problem after the course is complete This course explores how to use the machine learning (ML) pipeline to solve a real business problem in a project-based learning environment. Students will learn about each phase of the pipeline from instructor presentations and demonstrations and then apply that knowledge to complete a project solving one of three business problems: fraud detection, recommendation engines, or flight delays. By the end of the course, students will have successfully built, trained, evaluated, tuned, and deployed an ML model using Amazon SageMaker that solves their selected business problem. Module 0: Introduction Pre-assessment Module 1: Introduction to Machine Learning and the ML Pipeline Overview of machine learning, including use cases, types of machine learning, and key concepts Overview of the ML pipeline Introduction to course projects and approach Module 2: Introduction to Amazon SageMaker Introduction to Amazon SageMaker Demo: Amazon SageMaker and Jupyter notebooks Hands-on: Amazon SageMaker and Jupyter notebooks Module 3: Problem Formulation Overview of problem formulation and deciding if ML is the right solution Converting a business problem into an ML problem Demo: Amazon SageMaker Ground Truth Hands-on: Amazon SageMaker Ground Truth Practice problem formulation Formulate problems for projects Module 4: Preprocessing Overview of data collection and integration, and techniques for data preprocessing and visualization Practice preprocessing Preprocess project data Class discussion about projects Module 5: Model Training Choosing the right algorithm Formatting and splitting your data for training Loss functions and gradient descent for improving your model Demo: Create a training job in Amazon SageMaker Module 6: Model Evaluation How to evaluate classification models How to evaluate regression models Practice model training and evaluation Train and evaluate project models Initial project presentations Module 7: Feature Engineering and Model Tuning Feature extraction, selection, creation, and transformation Hyperparameter tuning Demo: SageMaker hyperparameter optimization Practice feature engineering and model tuning Apply feature engineering and model tuning to projects Final project presentations Module 8: Deployment How to deploy, inference, and monitor your model on Amazon SageMaker Deploying ML at the edge Demo: Creating an Amazon SageMaker endpoint Post-assessment Course wrap-up Additional course details: Nexus Humans The Machine Learning Pipeline on AWS 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 The Machine Learning Pipeline on AWS 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.