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
Duration 0.5 Days 3 CPD hours This course is intended for This course is primarily designed for business leaders, consultants, product and project managers, and other decision-makers who are interested in growing the business by leveraging the power of AI. Other individuals who wish to explore basic AI concepts are also candidates for this course. This course is also designed to assist students in preparing for the CertNexus AIBIZ⢠(Exam AIZ-210) credential. Overview In this course, you will identify ways in which AI can bring significant value to the business. You will: Describe AI fundamentals. Identify the functions of AI in business. Implement business requirements for AI. Artificial intelligence (AI) is not just another technology or process for the business to consider?it is a truly disruptive force, one that delivers an entirely new level of results across business sectors. Even organizations that resist adopting AI will feel its impact. If the organization wants to thrive and survive in this transforming business landscape, it will need to harness the power of AI. This course is designed to help business professionals conquer and move beyond the basics of AI to apply AI concepts for the benefit of the business. It will give you the essential knowledge of AI you'll need to steer the business forward. Lesson 1: AI Fundamentals Topic A: A Brief History of AI Topic B: AI Concepts Lesson 2: Functions of AI in Business Topic A: Improve User Experiences Topic B: Segment Audiences Topic C: Secure Assets Topic D: Optimize Processes Lesson 3: Implementing Business Requirements for AI Topic A: Identify Design Requirements Topic B: Identify Data Requirements Topic C: Identify Risks in Implementing AI Topic D: Develop an AI Strategy
Artificial Intelligence brings exciting new opportunities to the field of Conversational User Interfaces (CUI). Learn key concepts and proven design methods to deliver cutting-edge experiences and reach better business outcomes. Silvia Podesta is a Designer in the Client Engineering Team at IBM Nordics. She leverages design thinking, service and UX design to help clients identify opportunities for innovation and pioneer transformational experiences through IBM technology.
One of the criticisms levelled at the Real Estate sector is that it has traditionally been a well-connected space, with entry to it dictated by who you know, rather than what you know. With many University degrees in Real Estate teaching theoretical knowledge, how can you articulate this experience on a CV, and obtain greater practical experience with skills like modelling capabilities? In this webinar, Directors at Cobalt Recruitment, Maria Sinclair and Tom Enefer, will go through what new entrants to the Real Estate sector need to have on their CV and the avenues they can take to get more practical experience, including: - How you can communicate your education and modules studied effectively with employers - Tips to make your CV stand out - The industry apprenticeships available - Relevant internships on offer - The university sandwich year placements there are - Courses you can take to get a better understanding of the sector
What will you learn in this course? Comprehend academic lectures, interviews, articles, and literature. Understand anything written or spoken. Summarise texts. Express yourselves spontaneously in all situations either simple or complex. The main topics to be covered in this course are: entertainment, tourism, travel, news, social & political issues, relationships, technology, philosophy, science, greek culture & history and much more...
What will you learn in this course? Understand newspaper articles, the news and lectures and participate in discussions on a wide range of professional and specialised topics. Communicate with native speakers in all situations - everyday and formal. Deal with simple and more complex situations related to education, health system etc. Understand a wide range of simple and demanding texts and easily identify any information presented. Express yourselves spontaneously. Use language effectively for social, academic, and professional purposes. The main topics to be covered in this course are about emotions, images, mind, learning, modern life, truth & lies, technology, environment, greek culture and much more...
A workshop on the art of switching off and letting go, and why it's important that you do.
BRIT Creative Coaching is structured for Performing Arts Students to reach their goals. Discover and build new skills that you need outside the studio.
Person-centred approaches are a core skills framework that articulates what it means to be person-centred and how to develop and support the workforce to work in this way. Developed in partnership with Skills for Health and Skills for Care, the Framework aims to distil best practices and to set out core, transferable behaviours, knowledge and skills. It is applicable across services and sectors and across different types of organisations. Person-centred approaches underpins existing dementia, learning disabilities, mental health and end of life care core skills frameworks. This subject forms standard 5 in The Care Certificate.