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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

This course is intended for This course is intended for anyone who wants to learn the fundamentals of project management. No prior experience required. Overview Goals and benefits of implementing project management Key project management terminology, frameworks, and tools How to apply the approaches and processes to better manage and complete a project Important interpersonal interactions needed for successful projects This 1-Day virtual Project Management Best-Practices course provides an overview of fundamental elements of the project lifecycle ? from project initiation through project close. With a focus on traditional project management concepts, students will complete this course with an improved ability to understand the best path forward for bringing projects to successful completion. Students will benefit from this course by understanding the foundational principles of project management, improving their project management skills, utilizing tools and techniques to effectively manage projects, gaining a common project management language to improve communication, and learning frameworks to identify, manage, and mitigate risk. Concepts learned in this course are immediately applicable to ongoing projects. Note: This course has been approved by PMI for 8 PDUs. 1 - Introduction What are Projects? What is Project Management? Basic Project Management Process Project Selection How Projects Further Organizational Goals What Factors can Influence Projects? Documentation Project Management Tools Role of the Project Manager The Language of Project Management 2 - Starting a Project Authorizing the Project (Project Selection) Assigning the PM Identifying and Documenting the High-Level Scope Gathering a Planning Team Identifying and Documenting the Impacted Parties 3 - Planning a Project Adapting to the Needs of the Project (Planning Level) Identifying the Work Required Estimating Time, Cost and Resources Required Developing a Schedule Developing a Budget Planning Communications and Quality Risk Management Purchases and Outside Vendors for a Project 4 - Executing the Project Baselines Managing Participants in the Project Managing Interested and Impacted Parties Performing the Planned Work Negotiating and Signing Contracts Managing Communications, Risk and Quality 5 - Overseeing and Controlling the Project Controlling the Scope, Schedule and Budget Controlling Change to the Project (Scope, Schedule, Cost and Final Product) Quality Assurance and Control Contract Administration 6 - Ending a Project Overseeing and Controlling the Project Executing the Project Closing Contracts Transferring the Final Product Lessons Learned and Archiving Records

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Level 3 Supporting Teaching and Learning in Schools Certificate is a RQF qualification & this course play a major role by working with pupils & supporting teachers. This course has been designed to teach the knowledge required to be a teaching assistant and support children’s learning from birth to nineteen years. The course covers various requirements needed to work as an assistant within schools and how to approach a career in the education sector.  ABOUT THIS COURSE: Level 3 Award in Supporting Teaching and Learning is a knowledge only qualification. Experience in the real work environment is not required and the entire course is completed online. Please note that this is a knowledge only Level 3 qualification and does not require any practical assessments. COURSE ASSESSMENT: To pass this course learners must pass 4 assignments. These are completed after navigating through the corresponding lessons and writing your answers to assignment questions. Once these have been read and marked by your personal tutor, feedback and marks are provided to students which contain helpful tips to improve work in future assignments. UNITS COVERED: • Unit 1: Schools and Colleges as Organisations • Unit 2: Support Health and Safety in a Learning Environment • Unit 3: Understand how to Safeguard Children and Young People • Unit 4: Understand How Children and Young People Develop HOW MUCH THIS COURSE COST? Level 3: Award in Supporting Teaching and Learning Course will cost for Distance Learning / Online £249.99 and for class based £349.99. There is no any hidden fess/cost. 

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