Undergraduate Certificate in AI for Product Lifecycle Management

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The Undergraduate Certificate in AI for Product Lifecycle Management is a career-enhancing course that focuses on the integration of artificial intelligence (AI) in product lifecycle management (PLM). This certificate program is designed to equip learners with essential skills to excel in the rapidly evolving field of AI-driven PLM, addressing industry's growing demand for professionals with expertise in AI applications for product development, production, and after-sales support.

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Learners will gain hands-on experience with cutting-edge AI technologies and methodologies, preparing them to improve efficiency, reduce costs, and drive innovation in product lifecycle management. Completion of this certificate program will not only validate learners' knowledge and skills in AI-driven PLM but also provide a strong foundation for career advancement in various industries, including manufacturing, automotive, aerospace, and technology.

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โ€ข Introduction to Artificial Intelligence [AI]
โ€ข AI in Product Lifecycle Management [PLM]
โ€ข Machine Learning [ML] for Predictive Analytics in PLM
โ€ข Natural Language Processing [NLP] in PLM
โ€ข Computer Vision [CV] for Product Design & Inspection
โ€ข AI-Driven Product Data Management [PDM]
โ€ข AI Ethics & Bias in PLM
โ€ข AI Applications in Manufacturing & Supply Chain
โ€ข Implementing AI in PLM: Challenges and Best Practices

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The undergraduate certificate in AI for Product Lifecycle Management prepares students for various roles in AI, data science, and related fields. This 3D pie chart showcases the job market trends for AI professionals in the UK and highlights the percentage of professionals employed in each role. 1. AI Engineer: 25% AI engineers focus on designing, implementing, and managing AI systems. They are responsible for developing and maintaining AI models, integrating AI capabilities into existing systems, and ensuring the efficient functioning of AI applications. 2. Data Scientist: 20% Data scientists analyze and interpret complex datasets using statistical techniques, machine learning, and big data tools. They design and implement data models, create algorithms, and use predictive analytics to address business challenges. 3. Machine Learning Engineer: 18% Machine learning engineers specialize in designing, building, and implementing machine learning systems. They focus on developing algorithms, training models, and ensuring the successful integration of machine learning capabilities into products and services. 4. Business Intelligence Developer: 15% Business intelligence developers analyze data to create dashboards, reports, and visualizations that help businesses make informed decisions. They work with data warehousing, databases, and data mining tools to extract and analyze data. 5. Product Manager: 14% Product managers lead product development teams, working closely with engineering, design, and marketing teams to create AI-based products and services. They are responsible for defining the product vision, roadmap, and go-to-market strategy. 6. Other: 8% This category includes roles such as AI researcher, data analyst, and AI architect, among others. These professionals work in various industries, including finance, healthcare, and manufacturing, applying AI and machine learning techniques to improve processes and decision-making.

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UNDERGRADUATE CERTIFICATE IN AI FOR PRODUCT LIFECYCLE MANAGEMENT
ๆŽˆไบˆ็ป™
ๅญฆไน ่€…ๅง“ๅ
ๅทฒๅฎŒๆˆ่ฏพ็จ‹็š„ไบบ
London School of International Business (LSIB)
ๆŽˆไบˆๆ—ฅๆœŸ
05 May 2025
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