跟讀練習: Class Takeaways — Turning Data Into a Superpower - 通過影片學習英語口語

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Hi, my name is Mohsen Bayadi and I'm a professor of operation information and technology at Stanford Graduate School of Business.

In a world with a ton of information, the ability to turn raw data into better decisions is a superpower.

Today I will be sharing five key takeaways from my course business intelligence from big data

first guide your decisions by data human intuition is powerful but when it comes to assessing uncertainty it's sometimes pretty flawed

we naturally see patterns when there is no pattern

or we overreact to noise let me give you an example

consider a hospital vp in charge of quality of care who sees a drop in infection rates

and assumes a new protocol is working.

But often, it's just a lucky streak.

Random noise shows up as a trend.

By grounding your decisions in diverse data rather than a single perspective or AI tool,

you can tease out the true signal from the noise and manage uncertainty with better precision.

second invest in your technical capabilities by getting your hands dirty the philosophy of this course is

that the best way to learn is by doing you can't just read about ai

and data science you have to use the tools yourself to truly lead you need to understand the capabilities

and limitations of these technologies in this class we dive into writing code using ai apis

And it's the beauty of these hands -on experiences that demystifies the technology for us,

forcing you to understand it better and empowers you to build quick proof of concepts that can transform your business.

Third, formulate the right questions.

We often rush to find answers, but the hardest part of using data for decisions is asking the right questions.

A sophisticated AI agent or model is often useless if it solves the wrong problem.

An important skill we work on in this course is to

learn to translate a business challenge into a concrete model where you can identify the right AI -based method to solve it.

Before using any technology, ask yourself, what exactly are we trying to solve?

And how will data and AI tell us if we have succeeded?

fourth augment technology with expert human judgment we often see two extremes those who avoid ai

because it makes mistakes and those who over rely on it both are suboptimal

and the latter is even dangerous these technologies often have blind spots nuanced issues of bias

that won't go away easily your goal shouldn't be cognitive offloading or letting the machine do all the thinking.

Instead, use your expert judgment to verify the output, understand the limitations, and layer your reasoning on top of the technology.

Finally, lead through collaboration.

Decision -making with data is a team sport.

An individual contributor's style of work that happens in a silo often has limited impact because it lacks business context.

As a leader, your competitive advantage comes from bridging that gap.

Cross -functional teamwork is key.

By enabling deep collaboration between domain experts,

AI scientists, and engineers, you make sure the technical solutions are aligned with real business value.

Don't just consume the analysis, actively shape it.

So, what does this all add up?

By guiding decisions with data, investing in your capabilities, and balancing AI power with human wisdom, you don't just become a user of technology.

You become a leader who can navigate uncertainty with more clarity.

Implementing these principles will help you lead your teams effectively in a world that is becoming more AI -driven.

Teaching is beautiful because it helps you learn better.

At the same time, sometimes I just get excited, like I want to learn about a new technology and I want to share that with others.

So it allows me to do both.

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流利口語所需的一切

AI 發音評分逐句打分

音標練習掌握每個音

詞彙學習建立你的詞庫

詞彙遊戲邊玩邊學

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FOR YOU

本課的詞彙與口語要點

這節口語課以影片“Class Takeaways — Turning Data Into a Superpower”為素材。影片中反覆出現的詞有：technology, decision, learn, uncertainty, capabilities。這段影片共有 41 個句子、640 個單詞可供跟讀。講話部分時長為 4:51。說話人語速平穩，每分鐘約 132 個詞，很適合跟讀。只有 80% 的單詞屬於英語最常用的 3,000 詞，詞彙難度較高。

影片中的重點詞彙

影片中 15 個值得學習的單詞，附發音和釋義：

單詞	發音	釋義
solve 動詞	/sɒlv/	解決 /解決
uncertainty 名詞	/ʌnˈsɜːtənti/	不確定性
invest 動詞	/ɪnˈvɛst/	耗費 /耗費, 投資 /投資
collaboration 名詞	/kəˌlæbəˈɹeɪʃən/	合作, 協作 /協作
judgment 名詞	/ˈd͡ʒʌd͡ʒ.mənt/	判斷 /判斷
limitation 名詞	/lɪmɪˈteɪʃən/	限制
rush 動詞	/ɹʌʃ/	急速去, 急速做
concrete 形容詞	/ˌkɑnˈkɹit/	切實的 /切實的, 具體的 /具體的
output 名詞	/ˈaʊtpʊt/	輸出 /輸出
skill 名詞	/skɪl/	技巧, 技能
layer 名詞	/ˈleɪ̯ɚ/	層 /層
principle 名詞	/ˈpɹɪn.sɪ.pəl/	原理, 原則 /原則
infection 名詞	/ɪnˈfɛkʃən/	傳染 /傳染
domain 名詞	/ˌdəʊˈmeɪ̯n/	領域 /領域
wisdom 名詞	/ˈwɪzdəm/	智慧

影片中出現的短語動詞

單詞	釋義
go away 動詞	離開 /離開, 走
show up 動詞	露面

需要注意的發音

說話人用了 7 次縮略和弱讀形式，例如 don't, I'm, can't。請按聽到的簡短形式來說。

“sh” 和 “zh” 音: collaboration /kəˌlæbəˈɹeɪʃən/, limitation /lɪmɪˈteɪʃən/, rush /ɹʌʃ/, infection /ɪnˈfɛkʃən/, precision /pɹɪˈsɪʒ.ən/
長單詞——注意重音位置: capability /ˌkeɪ.pəˈbɪl.ɪ.ti/, uncertainty /ʌnˈsɜːtənti/, collaboration /kəˌlæbəˈɹeɪʃən/, limitation /lɪmɪˈteɪʃən/, naturally /ˈnæt͡ʃ.(ə.)ɹə.li/

中文母語者容易讀錯的音：

/v/ — 不要讀成 /w/，上齒輕觸下唇: solve /sɒlv/, invest /ɪnˈvɛst/, diverse /daɪˈvɜːs/, actively /ˈæktɪvli/, dive /daɪv/
詞尾子音 — 要讀清楚，後面不要加母音: solve /sɒlv/, invest /ɪnˈvɛst/, judgment /ˈd͡ʒʌd͡ʒ.mənt/, rush /ɹʌʃ/, concrete /ˌkɑnˈkɹit/
/r/ 和 /l/ 的區別: collaboration /kəˌlæbəˈɹeɪʃən/, naturally /ˈnæt͡ʃ.(ə.)ɹə.li/, principle /ˈpɹɪn.sɪ.pəl/, rely /ɹɪˈlaɪ/, protocol /ˈpɹoʊtəˌkɑl/

如何用這段影片練習

先完整聽一遍影片，不要開口，記下不認識的單詞。
用正常速度逐句跟讀，每句重複到你的節奏與說話人一致為止。
錄下自己的聲音並與原聲對比，特別注意 solve, uncertainty, invest 這類單詞。

什麼是跟讀法？

跟讀法 (Shadowing) 是一種有科學依據的語言學習技巧，最初開發用於專業口譯員的培訓，並由多語言者Alexander Arguelles博士普及。這個方法簡單而強大：您在聽英語母語原聲的同時立即大聲重複——就像是一個延遲1-2秒緊跟說話者的影子。與被動聽力或語法練習不同，跟讀法強迫您的大腦和口腔肌肉同時處理並模模擬實的講話模式。研究表明它能顯著提高發音準確性，語調，節奏，連讀，聽力理解和口語流利度——使其成為雅思口語備考和真實英語交流最有效的方法之一。

影子跟讀法: 閱讀完整分步指南 →

跟讀練習: Class Takeaways — Turning Data Into a Superpower - 通過影片學習英語口語

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