Pratique du Shadowing: How I use AI to learn engineering (anti brain rot studying) - Apprendre l'anglais à l'oral avec la vidéo

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Learning hard things used to take me weeks.

I used to look at slides, I used to look at these terrible lecture recordings from my professors with really bad audio

and then I would look at Indian men on YouTube giving me tutorials.

Now AI gets me unstuck in minutes and it's not by doing the work for me, it's by showing me the concepts in a visual manner,

cutting out all the noise from the signal and giving me those most important resources to learn ASAP.

Hi I'm Alex, I graduated with an electrical engineering degree two years ago i landed internships in ai hardware software engineering

and now i work as a member of technical staff at

a really cool ai startup working on training of large language models

so i literally learn hard things for a living here are

the four ways i use ai to learn at an incredible speed

and how you can steal this for your own purposes

and your educational needs let's get into the video back in the day

when i was a little kid i remember going on youtube

and watching free blue one brown he's a really cool mathematics youtuber

and he had fabulous fantastic exceptional presentations of maths in a

very visual manner he used an incredible like python tool

that he built to just make maths beautiful

and guess what now we can do this with anything we want not just maths

but with engineering too And I do this at work now

and it's honestly astonishing how good AI models are at showing us really stuff in an elegant manner.

Let me give you an example.

Imagine you're a mechanical engineering student and you need to do some CAD

but you don't really know what you should really even design and you don't really even know where to start.

Well, what you can do now is fire up something like claude code

or gpt codex

and start prompting away let's say you wanted to build a

robotics project you can type in something like hey claude i want to build a robotics project

but i'm not really too sure where to start give me

three ideas for a interactive presentation pitch them to me tell them why this one is the best one

and why should i build it and make a 3d model out of it

so i can see it this is super cool it will

generate a full presentation with a 3d model you can have

a look at it spin it around zoom in zoom out

try it out it's super super cool another example let's say

you're an electrical engineering student you have some electronics to do i remember for example i had an stm32

and i had to connect it to like an st link v3 to do some power measurements

and i remember it was very very confusing how to connect

these together the data sheet was terrible imagine a situation where you could just visualize how to connect stuff together

and you can just get to your work start getting your coursework done

that would be incredible huh so you can do

that now take a photo of your hardware

and tell claude make me an interactive dashboard

or presentation showing me how to wire the stm32 together to this other piece of hardware

so i can take power readings

and it will design for you this really cool interactive tool to show you how you wire this to

that this to that this to that step by step

so it's just so simple for you to follow

and it's incredible please try it out by the way

if you're going to do this i do recommend spending more of those expensive tokens on the better models

because they are much better at the 3d world

but this is just one element of it right this is just visualization that's a great way to learn

but in and of itself it's not enough and there are

so many resources out there which leads me to the next point of my video

and by the way i'm giving out my cv template for

free it got me interviews at google samsung hsbc my current

role as a member of technical staff at this ai startup

it's a really good cv template just go to alexgonick .com

resume link in the description go grab it use ai to decide what is actually worth reading

so in my job a quite a big element of it

can be reading research papers trying to figure out what's this

new little piece of architecture that's been slid into this transformer to make it operate in a cool way

but there's so much to read and you can't read everything

so you need to decide what you're going to read what

you're going to study what what information do you think is

valuable enough what's valuable for your time to actually go into your coranum

and i think the equivalent is at university i remember very

clearly you go into your lectures in the first few classes

the professor says yeah i have these book recommendations please read

please check out this book this book this book this book

they're all like 1 000 pages each one was written in

1970 what do you read should you even read them right

you should not read all five books that's for sure it

is going to be a complete waste of your time use

ai as a filter as a as a way to really

find exactly what you need from these books hey i got

this book recommendation list i'm not sure what this is about

i'm studying my course my course has this syllabus what book would be the most relevant to look at

and then once it's giving you a response guess what it's

probably not reasonable to read the whole book it's probably only one

or two or three chapters

that are actually going to be useful zoom in again ask it

which chapters of this book are like the best what's the 80 20 of this book

that will get me up to scratch with microwave communication systems

or stochastic control go and really do that filtering

so here's prompt for you

that you should use here's my here's my module slash class syllabus

and here is the reading list which books

and chapters from this book are actually worth my time considering my specific curriculum

and the exams i'm going to sit

which tutorial problems are worth doing this prompt is super super

good it's really really good i strongly recommend you use it it will save you a lot of time

if you are that type of person that likes to go a bit deeper

and just just read and capture some of

that information i on the other hand

when i have a huge list of papers

that potentially i want to read

and maybe i found them on twitter i just tell it

hey i found these five papers i want to get to

i want to get a good update i want to learn

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a bit more on this specific side of reinforcement learning

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which of these papers is the best to read

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which is the most legitimate and it tells me

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and then i go and then i read it

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and it's great i don't have to spend two hours reading papers

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when i can just spend 15 minutes

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but i know how it is to be a student i was there just two years ago

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and sometimes you don't have a you don't have all this

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fancy time to do a bunch of reading sometimes you got an exam next week

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and you need to get a lot of stuff done so

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that leads me to my next point which is find the 20

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that is essential to do so story time when I was

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when I was around 22 I was this was around 2023 I was an intern

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and hardware intern chat gbt3 just came out

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and I remember prompting it with something like hey could you

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explain to this to me like I'm five years old

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and I remember that was like an incredible thing to write

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and it did a fantastic job actually

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and it really made me fascinated by AI

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and this prompt was the base for what i'm about to kind of speak to you about

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and it's that usually in a topic

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that you are working on you're studying you're building a project

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on you don't need to know everything you don't even need

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to know half of it you only probably need to know

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20 to get moving to get going to get unstuck to go forwards

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when i was working on my thesis in graph neural networks

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for simulating airway flow in the lungs i got stuck okay i was doing all

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that self -learning by myself

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and i really really really didn't know what to do in certain moments

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and in those moments you just need to just get to

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the next step you know in deep learning you've got forward

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passes you've got activation functions you've got soft max tan h

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and relu you've got um you've got inputs outputs you've got matrices you've got

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so much stuff going on so much stuff

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that you can go really deeply on you've got different architectures

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you've got transformer you've got neural normal normal neural networks you've

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got graph neural networks what's the difference oh my god i

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can go on forever is there's too much there's too much to study there's too much to learn

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and i needed to really filter that down and i did i identified

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that i just need to get a training loop going see a few epochs feed it some training data

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and when i broke down

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that problem into something way more simple i just focused on studying

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that little tiny section on how do i use pytorch to run some data for a neural network

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and i figured out and i kept going

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and i still didn't know what how back pocket back propagation really works like back then

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but it was enough to get going so use ai to figure out

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what is the thing that you really need to know to get going then use

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that llm to to to get that resource to to get you to study

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that 20 out of the 100 that you really need

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and then get it done and then go back

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and learn the rest if you want to but don't think

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that you need to study everything to get going you do not

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and it's going to cost you many many hours

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if you think that's the case and that's how you learn things quickly and once you're unstuck Well, you need the best things to learn from, which leads me to my next point.

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By the way, if you're an engineering student and you're seriously stuck landing an internship, then you've landed in a great spot.

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I have a coaching program where I work with ambitious engineering students to get you your dream role.

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A, we create a fantastic portfolio of projects for you.

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B, we freshen everything up, your LinkedIn, your CV, so it's actually serious.

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And C, you get those interviews, you smash them and you get that dream job.

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If you're interested in this, link in the description.

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Make AI find you the best resource.

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So I started to get into CAD recently.

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It's actually a very interesting part of engineering.

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And I know very little about it.

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Okay, very, very little.

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I did very little CAD at uni and I tried to avoid it.

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I was really bad.

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But now, because of my job, actually, I'm really involved in doing computer -aided stuff

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and i've started using ai to really go deep

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and find these fantastic resources in the cad world i

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and i would never been able to figure this out by

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myself okay is i got ai to run these sub agents to pretty much scatter the whole of internet

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and find me really cool um data like cool templates of CAD stuff.

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I found NASA 3D models of Mars rovers.

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I found satellite files in .stl that I can just upload into my CAD software.

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I could not believe it.

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There is so much fantastic 3D models for free.

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You can literally build your own Mars rover for free.

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Everything is there open sourced download the files print it out

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wow guys it's it's incredible i was mind blown okay

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and i will and i would have never been able to figure

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that out without the use of ai

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so remember you searching through the internet for 10 hours is

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probably still going to be slower than 10 sub agents crawling the internet

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and they'll find you much better stuff

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if you just specify exactly what you're looking for just make sure you click on the links

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and double check that everything is legit

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because ai does hallucinate still just a big fyi

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so a little recap make stuff visual okay filter out all the bs

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which is on the internet 80 20 okay figure out what the 20

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that you need to know in your head right now to get stuff done

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and finally make sure when you are studying you use the best resource to do

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so and use ai to do these four things

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because it's better at you than us okay it's better now go learn something hard now

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if you want to learn more about ai tools

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that are actually good for you as an engineering student then

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go check out this video over here i go through my favorite tools

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that i would use as an engineering student if i was there now in 2026 and beyond that's everything see ya

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Vocabulaire et conseils d’expression pour cette leçon

Cette vidéo contient 197 phrases et 2330 mots à répéter en shadowing. La partie parlée dure 12:42. Le locuteur parle vite, environ 183 mots par minute : attendez-vous à des liaisons et à des sons réduits. 84 % des mots font partie des 3 000 mots les plus courants en anglais ; le reste mérite d’être vu avant de commencer.

Vocabulaire clé de cette vidéo

15 mots de la vidéo à retenir, avec leur prononciation et leur sens :

Mot	Prononciation	Sens
resource nom	/ɹɪˈzɔːs/	ressource
prompt verbe	/pɹɑmpt/	inciter
neural adjectif	/ˈnʊɹəl/	neural
hardware nom	/ˈhɑɹdˌwɛɹ/	équipement
filter nom	/ˈfɪltɚ/	filtre
mathematics nom	/mæθ(.ə)ˈmæt.ɪks/	mathématiques
connect verbe	/kəˈnɛkt/	accoupler, connecter
interactive adjectif	/ˌɪn.tɚˈæk.tɪv/	interactif
template nom	/ˈtɛm.plɪt/	gabarit, calibre
element nom	/ˈɛləmənt/	élément
wire nom	/ˈwaɪɚ/	fil
architecture nom	/ˈɑː.kɪˌtɛk.t͡ʃə/	architecture
slide nom	/ˈslaɪ̯d/	toboggan, glissoire
lecture nom	/ˈlɛk.t͡ʃə/	conférence, cours magistral
recommendation nom	/ˌɹɛkəmɛnˈdeɪʃən/	recommandation

Les verbes à particule que vous entendrez

Mot	Prononciation	Sens
figure out verbe		cerner
check out verbe		mater, regarder
break down verbe		tomber en panne
come out verbe	/ˌkʌm ˈaʊt/	sortir
cut out verbe		arrêter de
go back verbe		rentrer, retourner
go through verbe		traverser
zoom out verbe	/ˌzuːm ˈaʊt/	dézoomer

Prononciation à surveiller

Le locuteur utilise 47 contractions et formes réduites, comme you're, you've, I'm. Prononcez-les sous leur forme courte, telles que vous les entendez.

Les sons « th »: mathematics /mæθ(.ə)ˈmæt.ɪks/, thesis /ˈθisɪs/
Les sons « sh » et « zh »: presentation /ˌpɹɛzn̩ˈteɪʃn̩/, recommendation /ˌɹɛkəmɛnˈdeɪʃən/, internship /ˈɪntɜːnʃɪp/, capture /ˈkæp.(t)ʃɚ/, sheet /ʃit/
Mots longs — placez bien l’accent: mathematics /mæθ(.ə)ˈmæt.ɪks/, interactive /ˌɪn.tɚˈæk.tɪv/, architecture /ˈɑː.kɪˌtɛk.t͡ʃə/, electrical /ɪˈlɛktɹɪkəl/, recommendation /ˌɹɛkəmɛnˈdeɪʃən/

Comment s’entraîner avec cette vidéo

Écoutez la vidéo en entier une fois sans parler et notez les mots que vous ne connaissez pas.
Commencez à la vitesse 0,75×, répétez phrase par phrase, puis revenez à la vitesse normale quand cela devient facile.
Enregistrez-vous et comparez avec l’original, en faisant attention à des mots comme resource, prompt, neural.

La grammaire de cette vidéo

Les structures que le locuteur utilise le plus, avec les mots exacts de la vidéo :

Structure	Dans la vidéo
« Used to » used to + verbe — une habitude ou un état passé qui n’est plus vrai	used to take · used to look
Present perfect have/has + participe passé — une action passée qui compte encore maintenant	that's been · you've landed · i've started

Qu'est-ce que la technique du Shadowing ?

Le Shadowing est une technique d'apprentissage des langues fondée sur la science, développée à l'origine pour la formation des interprètes professionnels. Le principe est simple mais puissant : vous écoutez de l'anglais natif et le répétez immédiatement à voix haute — comme une ombre suivant le locuteur avec un décalage de 1 à 2 secondes. Les recherches montrent une amélioration significative de la précision de la prononciation, de l'intonation, du rythme, des liaisons, de la compréhension orale et de la fluidité.

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Pratique du Shadowing: How I use AI to learn engineering (anti brain rot studying) - Apprendre l'anglais à l'oral avec la vidéo

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