
Explore how operations management drives small business success, from scheduling and stock control to layout decisions, with practical activities, mini case studies, and forums to apply techniques.
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Introduce two new sections on artificial intelligence in operations management, covering AI basics and its application to the design, planning, and development of operations.
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Learn how operations management helps small businesses save costs, increase profits, and avoid failures, while applying these approaches to strategic goals.
Explore artificial intelligence in operations management for small businesses, with two new sections: understanding artificial intelligence and applying it to design, planning, and development of operations.
Explore how artificial intelligence drives operations management, covering neural networks and applications across design, planning, and improvement, including supervised, unsupervised, semi-supervised, reinforcement learning, and natural language processing.
Explore how AI enhances operations management through visual quality control in food production, with AMF Bakery Systems' cheese topping optimization and from-scratch versus off-the-shelf AI options.
Explore what a neural network is and how it works in operations management for small businesses, covering inputs, weights, biases, activation, training, and practical business applications.
Study supervised machine learning with labeled data to predict outcomes such as interviews and loan defaults. Explore four main types—supervised, unsupervised, semi-supervised, reinforcement learning—and natural language processing in operations management.
Define artificial intelligence and its core parts: machine learning, deep learning, and neural networks, and show how they sense, learn, predict, plan, and act in small business operations management.
Explore unsupervised machine learning, which finds patterns in unlabeled data through clustering, association, and dimensionality reduction to inform recommendations and insights, unlike supervised learning with labeled outputs.
Discover how semi-supervised learning combines unsupervised clustering and supervised models to exploit unlabeled data, forming a training set and using pseudo labels for tasks like handwriting recognition and fraud detection.
Explore reinforcement learning, where an agent learns from environment feedback to maximize cumulative rewards. Grasp states, actions, rewards, policy, and algorithms like Q-learning and Saorsa in operations contexts.
Explore natural language processing foundations, from rules-based and statistical approaches to neural networks, and apply speech recognition, tokenization, and sentiment analysis in operations management.
Artificial intelligence reshapes product and service design with generative design, simulation, and AI tools, democratizing sketching, reducing iterations, and enabling AI-enabled services like chatbots and recommender systems.
Explore how artificial intelligence shapes service design through demand analysis and AI-enabled features, using time series and machine learning for forecasting, chatbots, and recommender systems.
Apply artificial intelligence to supply network design by improving demand forecasting, optimizing routes, and refining warehouse design, while unsupervised learning analyzes layout and path data for better picking with robotics.
Explore how artificial intelligence designs process technology across materials, information, and customer processing, with 3D printing fault correction, AI software bug detection, and chatbots enabling hyper personalization of services.
Discover how artificial intelligence enhances demand forecasting for supply planning, warehouse operations, logistics, and customer relationships, comparing supervised learning with time series and Delphi methods.
Explore how artificial intelligence powers warehouse management to boost efficiency, from mobile autonomous robots to automated storage and retrieval systems, and how reinforcement learning optimizes stocking and inventory management.
Utilize AI-powered analytics and deep reinforcement learning to optimize dynamic routes with real-time traffic and weather, plus predictive maintenance and autonomous delivery options for improved logistics efficiency.
Explore how artificial intelligence integrates CRM and ERP to optimize project planning and control through AI-powered chatbots, machine learning, and natural language processing.
Leverage ai to improve product and service quality through visual defect detection, automatic removal, and root-cause analysis, guided by the Six Sigma define-measure-analyze-act-control cycle.
Explore how artificial intelligence and sentiment analysis enhance service quality in small businesses by real-time emotion and cognitive analysis of customer feedback to drive targeted improvements.
Small business operations are often developed informally and by trial and error. Operations management can make or break a business. As your business grows there will be a need to ensure the effectiveness and efficiency of its operations. Operations management techniques, which have their origins in large organisations, can be applied with great results in small businesses. This course is a practical guide to how these proven techniques can be used in small businesses.
This course will take you on a journey through: