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Leverage Data Science for a More Agile Supply Chain
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Leverage Data Science for a More Agile Supply Chain

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1.符合資格者將於出貨後三個工作日陸續發送交易訊息通知。2.點數將於廠商出貨後，隔天起算110天後陸續確認發送。3.國際商家之商品金額及回饋點數依據將以商品未稅價格為準。4.國際商家之商品金額可能受匯率影響而有微幅差異。5.禮品卡支付以及使用未授權優惠碼不符合贈點資格。6.點數發送依據及返點上限將以「訂單總金額」計算（不含運費及稅額），不論訂單中有多少商品，於LINE購物皆視為只購買一商品（金額為當筆訂單所有商品加總金額），亦即點數回饋計算並非以coursera實際購買商品數量拆分計算 。7. 同6說明，訂單完成後的顯示金額可能包含部分運費或稅金，可返點金額將以系統回傳金額為準 8.若於商家App下單，不符合LINE購物導購資格。
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Over the past two decades, the supply chain has become more complex. While advancing technology has allowed companies to capture this complexity within stores of ever accumulating data, companies have not kept up with how to analyze and derive insights from that data. This specialization uses hands-on activities to show how data science techniques can turn raw data into decision-makers for a more agile supply chain. Foundational techniques such as demand forecasting, inventory management with demand variability, and using the newsvendor model are covered, in addition to more advanced techniques such as how to optimize for capacity and resources as well as mitigate risks with the Monte Carlo simulation. By the end of this specialization, you will be able to: Describe how demand planning, supply planning, and constrained forecast are associated with one another. Use Excel to analyze historical data to quantify future needs. Analyze historical data to determine inventory levels in steady and uncertain demand situations using Excel. Manage inventory in an uncertain environment. Quantify the inventory needs for single-period items using the newsvendor model. Identify the components of capacity optimization, resource optimization, and Monte Carlo simulation. Set up and solve optimization problems in Excel. Build a demand and inventory snapshot and run a Monte Carlo simulation to solve for a more agile supply chain.

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