173 Managed Learning Programme (MLP) courses in Bristol delivered Online

24 Hours Left! Don't Let Year-End Deals Slip Away - Enrol Now! Are you fascinated by the mysteries of Marine Biology that lie beneath the ocean's surface? Do you dream of exploring vibrant coral reefs, studying majestic marine creatures, and understanding the delicate balance of aquatic ecosystems? If so, then our Marine Biology Advanced Diploma is the perfect opportunity for you to turn your passion for the ocean into a fulfilling career. This Diploma in Marine Biology at QLS Level 5 course is endorsed by The Quality Licence Scheme and accredited by CPDQS (with 150 CPD points). Learning Outcome of Marine Biology Course: Understand Marine ecosystems and their dynamics. Identify and describe Marine organisms, from microbes to vertebrates. Recognise the significance of the Marine Biology & Marine environment as a habitat. Comprehend key ecological concepts, such as food chains and webs in Marine Biology. Acknowledge the negative impact of human activities on marine life. Acquire knowledge about marine conservation efforts and strategies. Why Choose Our Marine Biology Course: Opportunity to earn a certificate endorsed by the Quality Licence Scheme & another accredited by CPDQS which is completely free. Get instant access to this Marine Biology course. Learn Marine Biology from anywhere in the world Marine Biology is affordable and simple to understand Marine Biology is entirely online, interactive lesson with voiceover audio Lifetime access to the Marine Biology course materials Marine Biology comes with 24/7 tutor support Marine Biology Advance Diploma Start your learning journey straight away with this Marine Biology course and take a step toward a brighter future! *** Course Curriculum of Marine Biology*** Here is the curriculum breakdown of the Marine Biology course: Module 01: Introduction to Marine Biology Module 02: The Ocean Module 03: The Ocean as a Habitat Module 04: Characteristics of the Marine Environment Module 05: Marine Life Module 06: Marine Microbes Module 07: Marine Invertebrates Module 08: Marine Vertebrates Module 09:Marine Populations and Communities Module 10: Marine Ecology Module 11: Food Chains and Food Webs Module 12: Damaging Impact of Human Activities on Marine Life Module 13: Marine Conservation Assessment Process of Marine Biology You have to complete the assignment questions given at the end of the course and score a minimum of 60% to pass each exam. After passing the Diploma in Marine Biology at QLS Level 5 course exam, you will be able to request a certificate at an additional cost that has been endorsed by the Quality Licence Scheme. CPD 150 CPD hours / points Accredited by CPD Quality Standards Who is this course for? Is this Marine Biology Course Right for You? Anyone interested in learning more about this subject should take this Marine Biology course. This course will help you grasp the basic concepts as well as develop a thorough understanding of the subject. Requirements Marine Biology Anyone from any background can enrol in this Marine Biology Diploma. There are no requirements to enrol in this Marine Biology Diploma Career path Marine Biology After completing this Marine Biology course, you are to start your career or begin the next phase of your career in this field. Certificates Certificate of completion Digital certificate - £10 Diploma in Marine Biology at QLS Level 5 Hard copy certificate - £119 Show off Your New Skills with a Certificate of Completion After successfully completing the Diploma in Marine Biology at QLS Level 5, you can order an original hardcopy certificate of achievement endorsed by the Quality Licence Scheme. The certificate will be home-delivered, with a pricing scheme of - 119 GBP inside the UK 129 GBP (including postal fees) for International Delivery Certificate Accredited by CPDQS 29 GBP for Printed Hardcopy Certificate inside the UK 39 GBP for Printed Hardcopy Certificate outside the UK (International Delivery)

Level 5 QLS Endorsed Course | CPD & CiQ Accredited | Audio Visual Training | Free PDF Certificate | Lifetime Access

Step into the future of machine learning with the Machine Learning Model Using AWS SageMaker Canvas Course, designed to make predictive modelling approachable, even if you haven’t written a single line of code. This course takes you through the streamlined world of AWS SageMaker Canvas—Amazon’s no-code solution for machine learning—allowing you to build, train, and deploy models using intuitive drag-and-drop functionality. Whether you're analysing business trends, forecasting sales, or making sense of complex data, this course provides a smart entry point into machine learning logic through a cloud-based platform trusted across industries. You’ll explore the fundamentals of data preparation, model creation, and evaluation—all while using a secure and scalable AWS environment. The course is tailored for analysts, business professionals, and data-curious individuals who want to make informed decisions with the support of AI-driven insights. With engaging lessons and smartly structured modules, this course delivers a smooth and intelligent introduction to machine learning concepts—without the noise. Dive into predictive analytics with confidence, and let AWS SageMaker Canvas guide your journey into data-driven forecasting. Expert Support Dedicated tutor support and 24/7 customer support are available to all students with this premium quality course. Key Benefits Learning materials of the Design course contain engaging voiceover and visual elements for your comfort. Get 24/7 access to all content for a full year. Each of our students gets full tutor support on weekdays (Monday to Friday) Key Features CPD Accredited Quality License Endorsed Certificate Available Upon Course Completion Course Curriculum: Introduction to Machine Learning What is Machine Learning? Introduction to AWS What is Amazon Web Services (AWS)? Signing into AWS Console Introduction to SageMaker What is SageMaker, and how it is used for Machine Learning? What is SageMaker Canvas? Setup SageMaker Domain and User Setup Setup Data in S3 Buckets for use in SageMaker SageMaker Canvas Interface Walkthrough Navigating in SageMaker Canvas Project 1: Banknote Authentication Adding Training Data Building and Using Model for Prediction Predict Single & Batch Dataset Validating Accuracy of Batch Predictions Project 2: Spam SMS Detection Adding Train & Test Data Building and Using Model for Prediction Predicting Data and Validating Accuracy Project 3: Customer Churn Prediction Adding Data Building Model Performing & Validating Predictions Project 4: Wine Quality Prediction Adding & Joining Datasets Building Model Predicting Test Data Assignment White Wine Quality Prediction Other Important Features in SageMaker Canvas Versioning Congratulations & Next Steps Getting Datasets for Practice Getting Help on SageMaker Canvas Congratulations & Thankyou Exam and Assessment MCQ based test 60% Marks to pass Instant Assessment and Feedback Certification CPD Accredited PDF and Hardcopy Certificate Level 2 QLS Endorsed Hardcopy Certificate for Award in Machine Learning Model Using AWS SageMaker Canvas at QLS Level 2 CPD 120 CPD hours / points Accredited by CPD Quality Standards Who is this course for? This Machine Learning Model Using AWS SageMaker Canvas course is designed to enhance your expertise and boost your CV. Learn key skills and gain a certificate of achievement to prove your newly-acquired knowledge. Requirements This Machine Learning Model Using AWS SageMaker Canvas course is open to all, with no formal entry requirements. Career path Upon successful completion of the Machine Learning Model Using AWS SageMaker Canvas Course, learners will be equipped with many indispensable skills and have the opportunity to grab. Certificates Certificate of completion Digital certificate - £9 Certificate of completion Hard copy certificate - £69 QLS Endorsed Certificate Hardcopy of this certificate of achievement endorsed by the Quality Licence Scheme can be ordered and received straight to your home by post, by paying - Within the UK: £69 International: £69 + £10 (postal charge) = £79 CPD Accredited Certification from One Education Hardcopy Certificate (within the UK): £15 Hardcopy Certificate (international): £15 + £10 (postal charge) = £25

The Machine Learning Model Using AWS SageMaker Canvas Course is designed for those who want to build smart solutions without diving nose-first into endless lines of code. With AWS SageMaker Canvas, you can develop machine learning models through an intuitive, no-code interface—perfect for users who prefer their data science with a touch less drama and a bit more drag-and-drop. This course walks you through the finer points of model creation, training, evaluation, and prediction, all through a clear and structured approach. Ideal for professionals who need results without wrestling with complex syntax, this course offers a neat introduction to the powerful capabilities of SageMaker Canvas. You’ll explore everything from dataset preparation to visualising outputs, learning how to navigate the platform efficiently while keeping things organised and clean. If your goal is to work smarter with machine learning—without turning it into a hobby—this is your chance to do just that, guided with a touch of wit and a sharp focus on what matters. Course Curriculum: Introduction to Machine Learning What is Machine Learning? Introduction to AWS What is Amazon Web Services (AWS)? Signing into AWS Console Introduction to SageMaker What is SageMaker, and how it is used for Machine Learning? What is SageMaker Canvas? Setup SageMaker Domain and User Setup Setup Data in S3 Buckets for use in SageMaker SageMaker Canvas Interface Walkthrough Navigating in SageMaker Canvas Project 1: Banknote Authentication Adding Training Data Building and Using Model for Prediction Predict Single & Batch Dataset Validating Accuracy of Batch Predictions Project 2: Spam SMS Detection Adding Train & Test Data Building and Using Model for Prediction Predicting Data and Validating Accuracy Project 3: Customer Churn Prediction Adding Data Building Model Performing & Validating Predictions Project 4: Wine Quality Prediction Adding & Joining Datasets Building Model Predicting Test Data Assignment White Wine Quality Prediction Other Important Features in SageMaker Canvas Versioning Congratulations & Next Steps Getting Datasets for Practice Getting Help on SageMaker Canvas Congratulations & Thankyou Exam and Assessment MCQ based test 60% Marks to pass Instant Assessment and Feedback Certification CPD Accredited PDF and Hardcopy Certificate Level 2 QLS Endorsed Hardcopy Certificate for Award in Machine Learning Model Using AWS SageMaker Canvas at QLS Level 2 CPD 120 CPD hours / points Accredited by CPD Quality Standards Who is this course for? This Machine Learning Model Using AWS SageMaker Canvas course is designed to enhance your expertise and boost your CV. Learn key skills and gain a certificate of achievement to prove your newly-acquired knowledge. Requirements This Machine Learning Model Using AWS SageMaker Canvas course is open to all, with no formal entry requirements. Career path Upon successful completion of the Machine Learning Model Using AWS SageMaker Canvas Course, learners will be equipped with many indispensable skills and have the opportunity to grab. Certificates Certificate of completion Digital certificate - £9 Certificate of completion Hard copy certificate - £69 QLS Endorsed Certificate Hardcopy of this certificate of achievement endorsed by the Quality Licence Scheme can be ordered and received straight to your home by post, by paying - Within the UK: £69 International: £69 + £10 (postal charge) = £79 CPD Accredited Certification from One Education Hardcopy Certificate (within the UK): £15 Hardcopy Certificate (international): £15 + £10 (postal charge) = £25

🚀 Unlock the Power of Data with Our Machine Learning Course! 🤖 Are you ready to dive into the revolutionary world of Machine Learning? Welcome to our comprehensive course designed to equip you with the skills and knowledge needed to harness the potential of data-driven decision-making. 🎓 Machine Learning has rapidly emerged as one of the most transformative technologies of the 21st century. From powering intelligent virtual assistants to revolutionizing healthcare diagnostics, its applications are boundless. With our expertly crafted course, you'll embark on a journey that will demystify the complexities of Machine Learning and empower you to leverage its capabilities for diverse purposes. 💡 Why Machine Learning? In today's data-driven world, organizations across industries are seeking professionals who can extract actionable insights from vast amounts of data. Machine Learning offers the tools and techniques necessary to analyze complex datasets, identify patterns, and make predictions with unprecedented accuracy. By mastering Machine Learning, you'll gain a competitive edge in the job market and position yourself as a valuable asset to any organization. 📈 What You'll Learn: Our Machine Learning course covers a wide array of topics, including: Fundamentals of Machine Learning algorithms Supervised, unsupervised, and reinforcement learning techniques Data preprocessing and feature engineering Model evaluation and validation Deep learning and neural networks Practical applications and case studies With hands-on projects and real-world examples, you'll not only understand the theory behind Machine Learning but also gain practical experience in implementing algorithms and solving complex problems. Whether you're a beginner or an experienced data professional, our course is tailored to accommodate learners of all levels. 📊 Who is this for? Our Machine Learning course is ideal for: Aspiring data scientists and analysts Software engineers looking to transition into Machine Learning roles Business professionals seeking to leverage data for strategic decision-making Students and academics interested in exploring the forefront of technology No matter your background or experience level, our course provides a solid foundation in Machine Learning principles and techniques, setting you on the path to success in this rapidly evolving field. 🌟 Career Path: By mastering Machine Learning, you'll open doors to a myriad of exciting career opportunities, including: Data Scientist Machine Learning Engineer AI Researcher Business Intelligence Analyst Data Engineer With the demand for Machine Learning professionals on the rise, employers are actively seeking individuals with the skills and expertise to drive innovation and deliver impactful solutions. Whether you're looking to advance your current career or embark on a new professional journey, our course will equip you with the tools and knowledge needed to thrive in today's competitive job market. 💼 FAQ: Q: Is prior programming experience required to enroll in the course? A: While prior programming experience can be beneficial, our course is designed to accommodate learners of all backgrounds. We provide comprehensive tutorials and resources to help you grasp the fundamentals of programming and get started with Machine Learning. Q: How long does it take to complete the course? A: The duration of the course varies depending on your pace and level of commitment. On average, most learners complete the course within 3 to 6 months. However, you have the flexibility to study at your own pace and revisit materials as needed. Q: Are there any prerequisites for enrolling in the course? A: While there are no strict prerequisites, familiarity with basic mathematics, statistics, and programming concepts can be advantageous. We provide supplementary materials and support to help you build the necessary foundation for success in the course. Q: Will I receive a certificate upon completion of the course? A: Yes, upon successfully completing the course requirements, you'll receive a certificate of completion that validates your proficiency in Machine Learning concepts and techniques. This certificate can enhance your credentials and demonstrate your expertise to potential employers. Q: How does the course structure accommodate working professionals? A: Our course offers flexible scheduling options, allowing you to balance your studies with your professional and personal commitments. With on-demand access to course materials and resources, you can learn at your own convenience and progress at a pace that suits your lifestyle. Don't miss out on the opportunity to unlock your full potential with our Machine Learning course! Enroll today and embark on a transformative journey that will shape the future of your career. 🌐✨ Course Curriculum Module 1_ Introduction to Machine Learning Introduction to Machine Learning 00:00 Module 2_ Linear Regression Linear Regression 00:00 Module 3_ Logistic Regression Logistic Regression 00:00 Module 4_ Decision Trees and Random Forests Decision Trees and Random Forests 00:00 Module 5_ Support Vector Machines (SVMs) Support Vector Machines (SVMs) 00:00 Module 6_ k-Nearest Neighbors (k-NN) k-Nearest Neighbors (k-NN) 00:00 Module 7_ Naive Bayes Naive Bayes 00:00 Module 8_ Clustering Clustering 00:00 Module 9_ Dimensionality Reduction Dimensionality Reduction 00:00 Module 10_ Neural Networks Neural Networks 00:00

Duration 1 Days 6 CPD hours Additional course details: Nexus Humans MicroKnowledge Training 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 MicroKnowledge Training 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 1 Days 6 CPD hours This course is intended for This course is intended for managers and supervisors engaged in working with the Millennial generation workforce. Overview Upon successful completion of this course, participants will be able to define onboarding, discuss the characteristics of Millennials, and develop action plans for working with them. In this course, participants will learn to build an onboarding process that recognizes the challenges and strengths of the Millennial workforce. Getting Started Workshop Objectives Action Plan Purpose of Onboarding Start Up Costs Employee Anxiety Employee Turnover Realistic Expectations Practical Illustration Introduction Why Onboarding? Importance of Onboarding Making Employees Feel Welcome First Day Checklist Practical Illustration Millennials and Onboarding Who are Millennials? How Do Millennials Differ from Other Workers? Investiture Socialization ? Let Them Be Themselves! Informal Rather than Formal Onboarding Processes Practical Illustration Onboarding Checklist Pre-Arrival Arrival First Day First Week First Month Practical Illustration Engaging the Millennial Employee Create an Informal Program Engage Employees One-on-one The Role of Human Resources The Role of Managers Practical Illustration Following Up with the Millennial Employee Initial Check-In ? One-on-one Following up ? Regular, Informal Follow Ups Setting Schedules ? Millennials and Work-Life Mentoring and the Millennial Practical Illustration Setting Expectations with the Millennial Employee Define Requirements ? Provide Specific Instructions Identify Opportunities for Improvement and Growth Set Verbal Expectations Put It in Writing Practical Illustration Mentoring the Millennial Be Hands-On and Involved Serial Mentoring Be a Mentor, Not an Authority Figure Focus Millennia?s Exploratory Drive on Work Practical Illustration Assigning Work to the Millennial Employee Provide Clear Structure and Guidelines Provide Specific Benchmarks Set Boundaries and Provide Reality Checks Practical Illustration Providing Feedback Millennials Thrive on Feedback! Characteristics of Quality Feedback Informal Feedback Formal Feedback Practical Illustration Wrapping Up Words From the Wise Additional course details: Nexus Humans Millennial Onboarding 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 Millennial Onboarding 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 1 Days 6 CPD hours This course is intended for Software Engineers Overview The objective of this course is to learn the key language concepts to machine learning, Spark MLlib, and Spark ML. This course will teach you the key language concepts to machine learning, Spark MLlib, and Spark ML. The course includes coverage of collaborative filtering, clustering, classification, algorithms, and data volume. This course will teach you the key language concepts to machine learning, Spark MLlib, and Spark ML. The course includes coverage of collaborative filtering, clustering, classification, algorithms, and data volume.

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.

Duration 2 Days 12 CPD hours This course is intended for This course benefits individuals responsible for configuring and monitoring devices running the Junos OS. Overview Describe the history and rationale for MPLS, as well as its basic terminology. Explain the MPLS label operations (push, pop, swap) and the concept of label-switched path (LSP). Describe the configuration and verification of MPLS forwarding. Describe the functionalities and operation of RSVP and LDP. Configure and verify RSVP-signaled and LDP-signaled LSPs. Select and configure the appropriate label distribution protocol for a given set of requirements. Describe the default Junos OS MPLS traffic engineering behavior. Explain the Interior Gateway Protocol (IGP) extensions used to build the Traffic Engineering Database (TED). Describe the Constrained Shortest Path First (CSPF) algorithm, its uses, and its path selection process. Describe administrative groups and how they can be used to influence path selection. Describe the default traffic protection behavior of RSVP-signaled LSPs. Explain the use of primary and secondary LSPs. Describe the operation and configuration of fast reroute. Describe the operation and configuration of link and node protection. Describe the operation and configuration of LDP loop-free alternate. Describe the LSP optimization options. Explain LSP priority and preemption. Describe the behavior of fate sharing. Describe how SRLG changes the CSPF algorithm when computing the path of a secondary LSP. Explain how extended admin groups can be used to influence path selection. Explain the purpose of several miscellaneous MPLS features. This two-day course is designed to provide students with a solid foundation on Multiprotocol Label Switching (MPLS). Course Outline Course Introduction MPLS Fundamentals MPLS Foundation Terminology MPLS Configuration MPLS Packet Forwarding Label Distribution Protocols Label Distribution Protocols RSVP LDP Routing Table Integration Mapping Next-Hops to LSPs Route Resolution Example Route Resolution Summary IGP Passive Versus Next-Hop Self for BGP Destinations Constrained Shortest Path First RSVP Behavior Without CSPF CSPF Algorithm CSPF Tie Breaking Administrative Groups Inter-area Traffic Engineered LSPs Traffic Protection and LSP Optimization Default Traffic Protection Behavior Primary and Secondary LSPs Fast Reroute RSVP Link Protection LDP LFA and Link Protection LSP Optimization Fate Sharing Junos OS Fate Sharing SRLG Extended Admin Groups Miscellaneous MPLS Features Forwarding Adjacencies Policy Control over LSP Selection LSP Metrics Automatic Bandwidth Container LSPs TTL Handling Explicit Null Configuration MPLS Pings