Shadowing Practice: Class Takeaways — Turning Data Into a Superpower - Learn English Speaking with Video
Les maken...
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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.
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In a world with a ton of information, the ability to turn raw data into better decisions is a superpower.
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Today I will be sharing five key takeaways from my course business intelligence from big data
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first guide your decisions by data human intuition is powerful but when it comes to assessing uncertainty it's sometimes pretty flawed
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we naturally see patterns when there is no pattern
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or we overreact to noise let me give you an example
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consider a hospital vp in charge of quality of care who sees a drop in infection rates
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and assumes a new protocol is working.
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But often, it's just a lucky streak.
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Random noise shows up as a trend.
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By grounding your decisions in diverse data rather than a single perspective or AI tool,
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you can tease out the true signal from the noise and manage uncertainty with better precision.
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second invest in your technical capabilities by getting your hands dirty the philosophy of this course is
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that the best way to learn is by doing you can't just read about ai
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and data science you have to use the tools yourself to truly lead you need to understand the capabilities
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and limitations of these technologies in this class we dive into writing code using ai apis
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And it's the beauty of these hands -on experiences that demystifies the technology for us,
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forcing you to understand it better and empowers you to build quick proof of concepts that can transform your business.
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Third, formulate the right questions.
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We often rush to find answers, but the hardest part of using data for decisions is asking the right questions.
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A sophisticated AI agent or model is often useless if it solves the wrong problem.
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An important skill we work on in this course is to
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learn to translate a business challenge into a concrete model where you can identify the right AI -based method to solve it.
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Before using any technology, ask yourself, what exactly are we trying to solve?
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And how will data and AI tell us if we have succeeded?
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fourth augment technology with expert human judgment we often see two extremes those who avoid ai
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because it makes mistakes and those who over rely on it both are suboptimal
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and the latter is even dangerous these technologies often have blind spots nuanced issues of bias
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that won't go away easily your goal shouldn't be cognitive offloading or letting the machine do all the thinking.
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Instead, use your expert judgment to verify the output, understand the limitations, and layer your reasoning on top of the technology.
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Finally, lead through collaboration.
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Decision -making with data is a team sport.
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An individual contributor's style of work that happens in a silo often has limited impact because it lacks business context.
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As a leader, your competitive advantage comes from bridging that gap.
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Cross -functional teamwork is key.
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By enabling deep collaboration between domain experts,
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AI scientists, and engineers, you make sure the technical solutions are aligned with real business value.
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Don't just consume the analysis, actively shape it.
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So, what does this all add up?
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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.
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You become a leader who can navigate uncertainty with more clarity.
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Implementing these principles will help you lead your teams effectively in a world that is becoming more AI -driven.
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Teaching is beautiful because it helps you learn better.
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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.
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So it allows me to do both.
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Woordenschat en spreektips bij deze les
Deze spreekles is gebaseerd op de video “Class Takeaways — Turning Data Into a Superpower”. Deze woorden komen het vaakst terug: technology, decision, learn, uncertainty, capabilities. Deze video bevat 41 zinnen en 640 woorden om na te spreken. Het gesproken deel duurt 4:51. De spreker praat in een gelijkmatig tempo van ongeveer 132 woorden per minuut, prettig om te shadowen. Slechts 80% van de woorden hoort bij de 3.000 meest gebruikte Engelse woorden, dus de woordenschat is pittig.
Belangrijke woorden in deze video
15 woorden uit de video die het leren waard zijn, met uitspraak en betekenis:
| Woord | Uitspraak | Betekenis |
|---|---|---|
| solve werkwoord | /sɒlv/ | oplossen |
| uncertainty zelfstandig naamwoord | /ʌnˈsɜːtənti/ | onzekerheid |
| collaboration zelfstandig naamwoord | /kəˌlæbəˈɹeɪʃən/ | samenwerking, het samenwerken |
| judgment zelfstandig naamwoord | /ˈd͡ʒʌd͡ʒ.mənt/ | oordeel |
| limitation zelfstandig naamwoord | /lɪmɪˈteɪʃən/ | begrenzing, beperking |
| naturally bijwoord | /ˈnæt͡ʃ.(ə.)ɹə.li/ | natuurlijk |
| rush werkwoord | /ɹʌʃ/ | afraffelen |
| concrete bijvoeglijk naamwoord | /ˌkɑnˈkɹit/ | concreet |
| output zelfstandig naamwoord | /ˈaʊtpʊt/ | productie |
| skill zelfstandig naamwoord | /skɪl/ | bekwaamheid, vaardigheid |
| layer zelfstandig naamwoord | /ˈleɪ̯ɚ/ | laag |
| principle zelfstandig naamwoord | /ˈpɹɪn.sɪ.pəl/ | principe, beginsel |
| infection zelfstandig naamwoord | /ɪnˈfɛkʃən/ | infectie, infectering |
| domain zelfstandig naamwoord | /ˌdəʊˈmeɪ̯n/ | domein |
| enable werkwoord | /ɪˈneɪ.bəl/ | inschakelen, in staat stellen |
Phrasal verbs die je zult horen
| Woord | Betekenis |
|---|---|
| go away werkwoord | weggaan |
| show up werkwoord | tentoonstellen |
Grammatica in deze video
De structuren die de spreker het meest gebruikt, met de exacte woorden uit de video:
| Structuur | In de video |
|---|---|
| Present perfect have/has + voltooid deelwoord — iets uit het verleden dat nu nog telt | have succeeded · has limited |
| Betrekkelijke bijzinnen who / which + zin — extra informatie over een persoon of ding | those who avoid · those who over |
Uitspraak om op te letten
De spreker gebruikt 7 samentrekkingen en verkorte vormen, zoals don't, I'm, can't. Spreek ze kort uit, zoals je ze hoort.
- De klanken “sh” en “zh”: collaboration /kəˌlæbəˈɹeɪʃən/, limitation /lɪmɪˈteɪʃən/, rush /ɹʌʃ/, infection /ɪnˈfɛkʃən/, precision /pɹɪˈsɪʒ.ən/
- Lange woorden — let op de klemtoon: capability /ˌkeɪ.pəˈbɪl.ɪ.ti/, uncertainty /ʌnˈsɜːtənti/, collaboration /kəˌlæbəˈɹeɪʃən/, limitation /lɪmɪˈteɪʃən/, naturally /ˈnæt͡ʃ.(ə.)ɹə.li/
Klanken die Nederlandstaligen lastig vinden:
- Stemhebbende eindmedeklinker — /b/, /d/, /g/, /z/, /v/ niet verscherpen: solve /sɒlv/, succeed /səkˈsiːd/, dive /daɪv/, cognitive /ˈkɑɡ.nɪ.tɪv/, flawed /flɔːd/
- /æ/ — opener dan de Nederlandse “e”: collaboration /kəˌlæbəˈɹeɪʃən/, naturally /ˈnæt͡ʃ.(ə.)ɹə.li/, actively /ˈæktɪvli/, transform /tɹænsˈfɔɹm/, translate /tɹænzˈleɪt/
- /g/ — een harde plofklank, geen Nederlandse “g”: cognitive /ˈkɑɡ.nɪ.tɪv/, navigate /ˈnæv.ɪ.ɡeɪt/, augment /ɔɡˈmɛnt/
Zo oefen je met deze video
- Luister de hele video één keer zonder te spreken en noteer de woorden die je niet kent.
- Spreek zin voor zin na op normale snelheid en herhaal elke zin tot je ritme gelijk is aan dat van de spreker.
- Neem jezelf op en vergelijk met het origineel; let daarbij op woorden als solve, uncertainty, collaboration.
Wat is de Shadowing-techniek?
Shadowing is een wetenschappelijk onderbouwde taalleermethode die oorspronkelijk is ontwikkeld voor professionele tolkentraining en gepopulariseerd door polyglot Dr. Alexander Arguelles. De methode is eenvoudig maar krachtig: je luistert naar native Engelse audio en herhaalt het onmiddellijk hardop — als een schaduw die de spreker volgt met slechts 1–2 seconden vertraging. In tegenstelling tot passief luisteren of grammaticadrills, dwingt shadowing je hersenen en mondspieren om echte spraakpatronen tegelijkertijd te verwerken en te reproduceren. Onderzoek toont aan dat het de uitspraaknauwkeurigheid, intonatie, ritme, verbonden spraak, luisterbegrip en spreekvaardigheid aanzienlijk verbetert — waardoor het een van de meest effectieve methoden is voor IELTS Speaking-voorbereiding en echte Engelse communicatie.