शैडोइंग अभ्यास: 資工科系真的不能念了嗎？為什麼新鮮人突然找不到工作？工程師飯碗不保？！｜Kelly Tsai - वीडियो के साथ अंग्रेजी बोलना सीखें
पाठ बनाया जा रहा है...
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In 2016, the American CS university
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The job is to be more than the average of all the people in the world
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The internet is everywhere Where do you know what CS is?
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Why do you know the door is the door?
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The first thing you can see is AI But the fact that you can see the door is another thing
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Welcome to Kelly Channel, I'm Kelly We were in the first time, we were in the first time We were in the first time, and we received 400 more of the news I went to the next time,
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a lot of people were in the name of CSBA Did you study?
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GetHub is really beautiful people and then I think that in the old school, the situation is not like that.
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There are reports that in the 2016 year, the CS students are the失業率 even more than the average average of all the people.
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The 20th century, the most stable, the most stable, the most stable.
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Now the new new ones are still more than the new ones.
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The internet is everywhere, and the new ones are still working.
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Many of them are still reading the資格, or the new ones are still reading the story.
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Today, we'll answer the last few years.
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CS is not going to be able to read it.
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Let's start!
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First of all, CS's career rate is what's up.
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According to the New York College of CS, the program is 22-27 years of CS's career rate, the career rate is 7%,
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the computer's more than 7.8%.
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In the data, the entire career rate is only 2-3%.
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The last year, the last year, the career rate is a 2-3% The career rate is more
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than 2.5% Indeed the technology development of the industry to the 4th of the year compared to the 2022 that the First,
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the first thing is the first thing is the first thing.
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The whole time, the whole company's job is only 2.8%.
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That's why the whole team is a lot of people who work well.
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He's going to go to the next thing to the next thing.
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CS's business business is not going to go to the next thing.
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And this is not CS's problem.
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According to the research research, 2023, the US's job is 8.5% from the young people.
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The other thing is that CS's job is to deal with the same problem.
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But CS is because it's the most high-refering The range of the range is more obvious
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The entire range of the range of the range from 2023 to now is 35%
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The range of the range of the range of the range is about There's no practice experience, the range is very true
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The range of the range of the range of the range of the range is 81.6%
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The range is 40.7% It's just a little bit more than
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a half This is the time of the range of the range It's not a big business in the range
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The second range is that CS is actually more than a lot of the range of the range
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Even some of the Cs's work-in-law-souls
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The New York University of Cs's work-in-law-souls
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The Cs's work-in-law-souls is 7.9% The Cs's work-in-law-souls The Cs's work-in-law-souls and the Cs's work-in-law-souls
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is just to graduate after to do not need this degree of work to do 63.9%
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and 65.8% The Cs's work-in-law-souls is also 54.6%
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So Cs's work-in-law-souls is more difficult to find the first job-in-law-souls But if you find it, I think that's the case for about 8 times,
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I think it's still job to work.
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This situation is actually better than many other people in the world.
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Why do you have the door to open up?
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The first thing to think of is AI.
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AI is still there.
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It's really about the first thing to do.
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But it's the murder of the killing of the people.
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Huffle has a追踪 6,000 million people's job research.
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In AI, the company is about 9-10%.
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But the business of the company's business is almost impossible.
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Standard for example, there are a number of different numbers.
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And AI, the code, was not that much.
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Anthropic did a test, which helped the AI to learn a new tool.
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After this, the idea and the idea of the test is more than 17 minutes.
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Another called METR company found that the AI team used the AI, which was done by the time, although they thought it would be faster.
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So AI is a bit more than a basic basic design.
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It's not the whole of the business.
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But the real thing is the two things.
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First, it's a bit of a surprise.
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It's a bit of a surprise to go to the the teacher's father's daughter's daughter.
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New York University has been able to calculate the young high school year-to-day school
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and the first year-to-day school year-to-day school is the biggest difference between the two years.
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It's about 64%.
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The logic is that
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a new person becomes a new company's job is to sit on the other side of the company
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and look and ask and ask and ask.
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But the new person is going to go to the next day, almost no longer.
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The company is going to go to the next day, the new person's job is going to be very high and then just don't open the door, just pick up the door.
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The second reason is the case.
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If you're going to take a look at the case, it's the case.
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That's the case.
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There's a rule called Section 174.
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In 2022, the company will pay for the company's money to not be able to pay for the money, to pay for a lot of money to pay for a lot of money.
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The reason is that the company is not able to pay for money, but because the money is not able to pay for money, the money is not able to pay for the money.
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So they will pay for the money to pay for the money.
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For the way to live, the most quickly is to to cut the company's office.
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The law law in 2025, although it was still back to the office But it was in the past few years, it was a lot of people who were able to pay for the money.
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The most people were asking is, now is it not to be able to choose CS?
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We can look at 2000 years, the internet's power was broken.
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The time of the NASDAQ's number from 5000 more points, from the time of the time, it fell to even 1000.
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The internet's network was stopped, the company was called and the company was called by the Chinese.
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The American CS's in the world's in the world from that after, it's 6 years and it's a bit of 2007 or 2008.
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That's a few years, everyone thinks the whole road is dead.
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But according to the later the American計算機会 report that they were forced to ask to not read CS that many years, the IT-to-year number of people actually has been increased and more than the other than the other.
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After the time of the智慧型 the time of the time, the demand was big.
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2007 after CS, the new people started to increase.
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The new people of CS are a low-to-date.
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It's always a bad news for短期.
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Everyone will be a little bit of a rush and a little bit of a rush
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but the demand is still still there just will be a fear for the And
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while the time is still moving to the revenue this way
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of the return is still there According to the following According
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to the following the Hamilton Project of the entire year a
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CS-BHM 30-40 years of the total累積 is usually over 200 million
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and the total of 6,000 more than a year and the average of the year's graduate is about 120 million
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But here to talk about this is the last year the
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entire year of the total累積 of the number AI-10s can't be able to fix
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and no one can guarantee It's also showing that this year's long-term so the first job is really hard to find it.
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But if you have been walking too long, the path of the return is still standing.
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If you don't want to choose CS this question, I think it's true.
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If you are really interested in CS, you will still be interested in CS.
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But if you go to the end of the day, it's still a good time.
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I think if you want to choose CS this question, I think if you really want CS to be interested and excited, that you still should be.
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But if you don't like CS, I just want to study it.
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I'm going to go to the next stage.
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Then you will be very hard.
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If you already decided to go this business, how do you decide to live this business?
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AI is probably going to be a cheap one.
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But it's not going to be a whole of the entire business.
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It's not going to be a whole of the entire business.
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and even if you do AI, you can't go through the things
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The first one is the技術研究 the core of the AI This one is in Mc希 in the AI-based organization
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gave a name called T-型
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The number is to say can be able to use the field of knowledge domain knowledge to decide a system
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which is what to do AI which is what to do
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and to decide the way to decide the way to decide the way to check
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and check and check AI itself out of the things, right?
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The number is to say it can be able to use the AI-based technology to turn into
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so what Let's hear from others.
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This is a good thing to hear from people.
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It's still still there.
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Like the health insurance company.
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According to the US, the US government's business plan The US government's business plan is to give up to 29% to 33%.
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The most important job is to give up to 4% to 5%.
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It's 6 or 7%.
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The World's business plan is to give up to the health insurance company.
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But it's not enough to give up to the technology.
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Because even if you use AI, it's still a good thing.
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So the more useful is the second one.
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The second one is the best.
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They are more than a big part of the world and also a variety of different areas
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and can be able to guide AI and guide people The value is not
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that they can do their own
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but they can be able to connect the way to the world
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and can be able to guide AI tools and can be able to guide AI in a模糊不清
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This is what I think people are doing with the same thing Now, we all use AI to divide by three
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The top of the world is only with AI to talk about
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and ask them to write things The bottom of the world is using AI to make a product out
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But the most important thing is that the AI can be able to solve the real business and then change the money.
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And I want to tell you a fact.
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If you have a business idea, it will be directly affected your money.
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The company of OmniSan is now in the 4th of June, which will be the AI-based user for the AI-based users.
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But the standard is not to look at you will not use AI, but to look at the three things.
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AI-based companies' spending time, and the financial impact of the company, and the job-based business, and the job-based people have been widely used.
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The difference between the technology and the technology is an important part of the technology.
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It's a real-time thing that we need to do with the technology.
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It's just a bit more than the technology.
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We're usually trying to make things out of the way, but we're not trying to decide this thing is what it's worth and worth.
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And I mentioned the T-Sign and M-Sign is actually just in the Havel School of Health.
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There's a course in helping you to help you help you understand this.
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It's the knowledge of the Havel School of Health and Health.
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Christina Wallace We are working on a web course Everyone knows
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that Can't get to the Huffle It's not easy The知識 of the星 can be able to get to this teacher
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This is the most difficult part of the course You can
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use the course of the Huffle MBA All of the course
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of the course All of the students All of the work
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that we use All of the students use of the course
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Christina Wallace Is the Huffle MBA The expert and講師 In MBA She taught the new business
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She was a coached by BCG
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She was a professor of the business She was a senior in the business
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And the business manager Even her successors She's even a business
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manager She's a new business manager She's a new case study I recommend you to go to this class
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because the Huffle School is the only one to ask MBA
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students to attend the first year to do the first year's business
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because they believe that you are not believe that you are not a business.
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The business management system of the mind of the mind is very important to everyone.
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I saw the book and thought that the content was really a very clear.
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There are a lot of the recent news that I've been talking about
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and the news that I've been talking about and a half-year-old, like, from 0 to 350 million of the base44, which is a matter of fact, one person can be a team of companies.
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Look how they're working on their job.
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And there are a couple of different things that I've been doing.
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One company called TableIQ, they have no idea of new AI-based design, but is to be able to review the restaurant's work.
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They are looking at the restaurant and the kitchen, and looking at the food, the order of the meal, the food waste, and the food supply.
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They are all in the morning, and they are all in the morning, and they are giving the company a new idea.
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Christina said they have built a data-driven design every day to increase the restaurant's design, and they are making the design more accurate.
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This is become TableIQ's team's team.
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It is not a team to be a team to be a team.
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And in a year, they have already been able to achieve the money 70%.
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The course of the course is what I mentioned before using
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the business of business to help AI It's not going to spend time with AI talking
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or how to use the tools to do things
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but it's going to be on the next level when the business is cheap how to do it again
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how to look at the pace of the pace how to
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do it in the pace of AI how to do AI to do it
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and how to do it in the game If you don't have a chance to do it, it's not a good thing so the course is still a lot of practice
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so you have to be able to think about it If you're still in the game, you're going to do it
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but not will be able to decide this thing will be worth the price of the price
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this is the right time to help you to help you
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this is the right time this is the right time now
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in the market is 7月9日到8月16日 with a low 39折 of the
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new year I can also add in my own I can
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also add in the link to the link I will put in the information box
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that if you go first to get more deep or second to help you to help you
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the right time is the same thing
198
that is not to let you stop in the only way of the action
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because that is AI will be the most to get the point that we will get the first question
200
What is CS yet to be able to read?
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I'll be able to read it every few years.
202
The internet is the air, and the air, and the air.
203
Every time there is a man says that 工程师 is done.
204
Every time living here is the I wish to change the new ideas.
205
I want to change the equipment.
206
My experience is that the business industry is not a good thing.
207
It's a good thing.
208
I'm always going to learn the next thing.
209
I've been able to read it for seven years.
210
I've seen several of these kinds of things.
211
At GPD came out that year, I think there are two years ago, but the two years later it was those people who are the most likely to be able to do AI
212
because they are the team's team that's the best AI to capture and to solve real problems.
213
It's those who think this is no matter, and then they will be able to write down the code.
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I'm talking about the company's job, and I'm looking at the newsroom, and I'm seeing the newsroom when I'm looking at the newsroom.
215
It's also the reason I think this is important for today.
216
If you're in Taiwan, I think this is a very far away from you.
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Taiwan's business industry will be followed by the US, But the way that you can't go away from the house, but the way that you can't go away from the house, such as the financial system, such as the lack of people, Taiwan is still very short.
218
If you want to read CS, you can ask yourself what kind of mind to read.
219
If you're very excited about it, I would say go for it.
220
But if you're a bit older, you can't work with your own mind, you can't do that.
221
I'm going to ask you this video, if you want to learn CS, then you can do this video.
222
If you're in the video, or you're in the video, or you're in the video, you can tell me your situation.
223
Then we'll see you next time!
224
Bye bye!
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इस पाठ की शब्दावली और बोलने के सुझाव
यह B2 स्तर का स्पीकिंग पाठ वीडियो “資工科系真的不能念了嗎？為什麼新鮮人突然找不到工作？工程師飯碗不保？！｜Kelly Tsai” पर आधारित है। इस वीडियो में शैडोइंग के लिए 224 वाक्य और 3110 शब्द हैं। बोला गया हिस्सा 13:37 लंबा है। वक्ता तेज़ बोलता है, लगभग 228 शब्द प्रति मिनट, इसलिए जुड़ी हुई और कमज़ोर ध्वनियाँ ज़्यादा मिलेंगी। 91% शब्द अंग्रेज़ी के 3,000 सबसे आम शब्दों में से हैं, इसलिए शब्दावली आसान है।
इस वीडियो की मुख्य शब्दावली
वीडियो के 8 सबसे कठिन शब्द, उच्चारण और अर्थ के साथ:
| शब्द | उच्चारण | अर्थ |
|---|---|---|
| stable संज्ञा | /ˈsteɪ.bəl/ | गोष्ठ, अश्वालय |
| solve क्रिया | /sɒlv/ | सुलझाना, हल करना |
| meal संज्ञा | /ˈmiːl/ | भोजन, जेमन |
| compare क्रिया | /kəmˈpɛɚ/ | तौलना |
| guarantee संज्ञा | /ˌɡæɹ.ənˈtiː/ | प्रतिभूति |
| divide क्रिया | /dɪˈvaɪd/ | बांटना |
| successor संज्ञा | /səkˈsɛsɚ/ | उत्तराधिकारी |
| calculate क्रिया | /ˈkælkjʊleɪt/ | गणना करना, हिसाब रखना |
वीडियो में आने वाली फ़्रेज़ल वर्ब
| शब्द | अर्थ |
|---|---|
| pick up क्रिया | उठाना |
दोहराने लायक वाक्य
वीडियो के छोटे, पूरे वाक्य जिन्हें आप रोज़ की बातचीत में इस्तेमाल कर सकते हैं:
- Why do you know the door is the door?
- Today, we'll answer the last few years.
- I think it's still job to work.
- Why do you have the door to open up?
- I'm going to go to the next stage.
इस वीडियो का व्याकरण
वक्ता जिन संरचनाओं का सबसे अधिक प्रयोग करता है, वीडियो के असली शब्दों के साथ:
| संरचना | वीडियो में |
|---|---|
| Present perfect continuous have/has been + -ing — पहले शुरू हुआ काम जो अब भी जारी है | have been walking · I've been talking · I've been doing |
| Present perfect have/has + past participle — बीता हुआ काम जिसका असर अभी भी है | has been · has been increased · have been |
| Passive voice be + past participle — ज़ोर इस पर कि क्या होता है, न कि कौन करता है | was done · was broken · was stopped |
| Relative clauses who / which + उपवाक्य — व्यक्ति या वस्तु के बारे में अतिरिक्त जानकारी | people who work · people who were · June, which will |
ध्यान देने योग्य उच्चारण
वक्ता 39 बार संक्षिप्त रूपों का प्रयोग करता है, जैसे you're, I'm, can't। इन्हें वैसे ही छोटा बोलें जैसा आप सुनते हैं।
- “sh” और “zh” की ध्वनियाँ: rush /ɹʌʃ/, capture /ˈkæp.(t)ʃɚ/
हिंदी भाषियों के लिए मुश्किल ध्वनियाँ:
- /v/ और /w/ का फ़र्क़ — /v/ में ऊपर के दाँत निचले होंठ को छूते हैं, /w/ में होंठ गोल होते हैं: solve /sɒlv/, divide /dɪˈvaɪd/
- /æ/ — “ऐ” से ज़्यादा खुला: guarantee /ˌɡæɹ.ənˈtiː/, capture /ˈkæp.(t)ʃɚ/, calculate /ˈkælkjʊleɪt/, anthropic /ænˈθɹɒp.ɪk/
इस वीडियो से अभ्यास कैसे करें
- पहले बिना बोले पूरा वीडियो एक बार सुनें और जो शब्द नहीं आते उन्हें लिख लें।
- 0.75× गति से शुरू करें, एक-एक वाक्य की शैडोइंग करें, और सहज लगने पर सामान्य गति पर लौटें।
- अपनी आवाज़ रिकॉर्ड करें और मूल से तुलना करें, ख़ासकर stable, solve, meal जैसे शब्दों पर ध्यान दें।
शैडोइंग तकनीक क्या है?
शैडोइंग (Shadowing) एक विज्ञान-समर्थित भाषा सीखने की तकनीक है जो मूल रूप से पेशेवर दुभाषिया प्रशिक्षण के लिए विकसित की गई थी। विधि सरल लेकिन शक्तिशाली है: आप मूल अंग्रेज़ी ऑडियो सुनते हैं और तुरंत इसे ज़ोर से दोहराते हैं — जैसे वक्ता की छाया 1-2 सेकंड की देरी से। शोध से पता चलता है कि यह उच्चारण सटीकता, स्वर, लय, जुड़ी हुई ध्वनियाँ, सुनने की समझ और बोलने की प्रवाहशीलता में काफ़ी सुधार करता है।