Executive Development Programme in Automotive AI and Deep Learning

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The Executive Development Programme in Automotive AI and Deep Learning certificate course is a comprehensive program designed to meet the surging industry demand for professionals with expertise in AI and machine learning. This course emphasizes the application of deep learning techniques in the automotive sector, covering critical areas like autonomous vehicles, predictive maintenance, and advanced driver-assistance systems.

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ใ“ใฎใ‚ณใƒผใ‚นใซใคใ„ใฆ

By enrolling in this course, learners will gain essential skills necessary for career advancement in the rapidly evolving automotive industry. The curriculum equips learners with the ability to design and implement AI and deep learning models, understand the ethical implications of AI, and lead data-driven decision-making processes. The course also provides hands-on experience with industry-standard tools and techniques, ensuring learners are well-prepared to tackle real-world challenges in the automotive sector. In summary, this course is essential for professionals seeking to stay ahead in the competitive automotive industry, providing them with the necessary skills and knowledge to leverage AI and deep learning for innovation, efficiency, and growth.

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ๅ…ฑๆœ‰ๅฏ่ƒฝใช่จผๆ˜Žๆ›ธ

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ๅพ…ๆฉŸๆœŸ้–“ใชใ—

ใ‚ณใƒผใ‚น่ฉณ็ดฐ

โ€ข Introduction to Automotive AI: Fundamentals of AI, AI applications in the automotive industry, opportunities and challenges

โ€ข Deep Learning Basics: Neural networks, backpropagation, convolutional neural networks (CNN), recurrent neural networks (RNN)

โ€ข Computer Vision for Autonomous Vehicles: Object detection, image segmentation, lane recognition, traffic sign and light detection

โ€ข Natural Language Processing in Automotive: Speech recognition, text-to-speech, sentiment analysis, chatbots

โ€ข Automotive Data Analytics: Data collection, data preprocessing, predictive analytics, decision trees, regression analysis

โ€ข Reinforcement Learning for Autonomous Driving: Q-learning, deep Q-networks (DQN), policy gradients

โ€ข Ethics and Safety in Autonomous Vehicles: Ethical considerations, safety standards, liability issues

โ€ข Automotive AI Use Cases and Case Studies: AI implementations in various automotive applications, real-world examples, lessons learned

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ใ„ใคใ‚ณใƒผใ‚นใ‚’้–‹ๅง‹ใงใใพใ™ใ‹๏ผŸ

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ใ‚ญใƒฃใƒชใ‚ข่จผๆ˜Žๆ›ธใ‚’ๅ–ๅพ—

ใ‚ตใƒณใƒ—ใƒซ่จผๆ˜Žๆ›ธใฎ่ƒŒๆ™ฏ
EXECUTIVE DEVELOPMENT PROGRAMME IN AUTOMOTIVE AI AND DEEP LEARNING
ใซๆŽˆไธŽใ•ใ‚Œใพใ™
ๅญฆ็ฟ’่€…ๅ
ใงใƒ—ใƒญใ‚ฐใƒฉใƒ ใ‚’ๅฎŒไบ†ใ—ใŸไบบ
London School of International Business (LSIB)
ๆŽˆไธŽๆ—ฅ
05 May 2025
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