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Questões de Inglês do ENEM

Questões de Inglês, da área de Linguagens, com gabarito em cada página.

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  • 57 assuntos

Resultados: 5.311 questões

Página 81 de 266

  • Linguagens

    Inglês

    Beyonce, colorism, and why all of this needs to end


    by Ernest Owens


        Yes, the Super Bowl was on fire. As one who is very critical of halftime show performances, I cannot deny that Beyoncé brought the energy and attention. All of this led to her releasing her tour dates for the Mrs. Carter Show. As excited as I was to actually buy these tickets, something turned me off. The poster.


    Imagem da questão de Inglês, Escola Superior de Propaganda e Marketing 2018, Interpretação de texto | Reading comprehension


       If you haven’t seen the photographs for Beyonce’s new world tour, you probably wouldn’t even recognize her. You will see an image of what looks like a Victorian white woman in the Elizabethan era. Her (prosthetic) blonde hair puffed and extended to reveal a face that is almost as white as snow. Lips red and her skin powdered. This is not the same bronze Beyonce that I saw rocking the stage in an all female band with her darker Destiny’s Child counterparts. I was only left with memories of previous patterns that the multi-Grammy award winning artist had done in previous years in regards to her skin. And I asked myself the question: why, Bey?

         Let’s not act like this is something new. Over the years, it seems as though Beyonce has gotten lighter as she has gotten older. No, this is not genetics and let’s not pretend her skin color in her first Destiny’s Child album cover matches that of her latest album. Whether it is that highly controversial Revlon advertisement or her own album cover art, Beyonce has consistently been called out on alterations done to her pigments.

        What does this say about our society for black women? It tells me that, an independent, confident and successful woman of color still struggles to have the confidence to fully embrace the skin she is in. If one of the most powerful women in entertainment feels she has to lighten her skin for projection, what does that say for the rest of us?

        Believe it or not, colorism, the stigma associated with skin complexion, has been an ill that has not yet been dissolved by the black community. What was first given to us by slave masters in separating the house slaves from the field ones, has now taken place in how we objectify our women and each other.

        This is pretty problematic in many ways. It’s first of all self-loathing and unnecessary for today’s times. The fact that our nation had an African-American first lady with a complexion that isn’t on the lighter side of the spectrum, nor does it try to be, shows a compelling advancement in appreciation for all women of color in many ways.

         Furthermore, the only reason why such stigma in our country continues is contributed to our own behavior that is shaped by the influential people of color around us. It devastated me when I saw that Sammy Sosa had lightened his skin. As successful as he was in a field that was not necessarily fixated on male skin complexion, it saddened me to see him do it. In many ways, it even made me reflect back on the transition of the late great Michael Jackson and what explanations he had for such a more pale white appearance.

        And why does all of this matter? Because I grew up hearing stories of young dark black girls getting their faces scrubbed with skin lightening soaps out of their free will. Tales of young women being abandoned by their mothers because they were too dark.

        If this is the reality that had more implications back in the early 20th century than it does now, please stop it. Stop trying to explain why you are dating the ebony skin girl. Stop making it seem exceptional that a girl of a darker complexion is actually attractive. Celebrities, stop putting extraneous powders and lighteners on your skin: we all know what you used to look like and we still love you. And people of color: let’s not continue to perpetuate an oppressive cycle of self-loathing of our appearance and heritage. If this can be accomplished, then perhaps even in our own race we can truly make our lives not be judged by the color of our skin but by the content of our character.


    (adapted from www.huffingtonpost.com, 14/02/2013)

    The author of the article:
    Escolha uma alternativa para a questão 4d433ac4-fd
  • Linguagens

    Inglês

    Beyonce, colorism, and why all of this needs to end


    by Ernest Owens


        Yes, the Super Bowl was on fire. As one who is very critical of halftime show performances, I cannot deny that Beyoncé brought the energy and attention. All of this led to her releasing her tour dates for the Mrs. Carter Show. As excited as I was to actually buy these tickets, something turned me off. The poster.


    Imagem da questão de Inglês, Escola Superior de Propaganda e Marketing 2018, Interpretação de texto | Reading comprehension


       If you haven’t seen the photographs for Beyonce’s new world tour, you probably wouldn’t even recognize her. You will see an image of what looks like a Victorian white woman in the Elizabethan era. Her (prosthetic) blonde hair puffed and extended to reveal a face that is almost as white as snow. Lips red and her skin powdered. This is not the same bronze Beyonce that I saw rocking the stage in an all female band with her darker Destiny’s Child counterparts. I was only left with memories of previous patterns that the multi-Grammy award winning artist had done in previous years in regards to her skin. And I asked myself the question: why, Bey?

         Let’s not act like this is something new. Over the years, it seems as though Beyonce has gotten lighter as she has gotten older. No, this is not genetics and let’s not pretend her skin color in her first Destiny’s Child album cover matches that of her latest album. Whether it is that highly controversial Revlon advertisement or her own album cover art, Beyonce has consistently been called out on alterations done to her pigments.

        What does this say about our society for black women? It tells me that, an independent, confident and successful woman of color still struggles to have the confidence to fully embrace the skin she is in. If one of the most powerful women in entertainment feels she has to lighten her skin for projection, what does that say for the rest of us?

        Believe it or not, colorism, the stigma associated with skin complexion, has been an ill that has not yet been dissolved by the black community. What was first given to us by slave masters in separating the house slaves from the field ones, has now taken place in how we objectify our women and each other.

        This is pretty problematic in many ways. It’s first of all self-loathing and unnecessary for today’s times. The fact that our nation had an African-American first lady with a complexion that isn’t on the lighter side of the spectrum, nor does it try to be, shows a compelling advancement in appreciation for all women of color in many ways.

         Furthermore, the only reason why such stigma in our country continues is contributed to our own behavior that is shaped by the influential people of color around us. It devastated me when I saw that Sammy Sosa had lightened his skin. As successful as he was in a field that was not necessarily fixated on male skin complexion, it saddened me to see him do it. In many ways, it even made me reflect back on the transition of the late great Michael Jackson and what explanations he had for such a more pale white appearance.

        And why does all of this matter? Because I grew up hearing stories of young dark black girls getting their faces scrubbed with skin lightening soaps out of their free will. Tales of young women being abandoned by their mothers because they were too dark.

        If this is the reality that had more implications back in the early 20th century than it does now, please stop it. Stop trying to explain why you are dating the ebony skin girl. Stop making it seem exceptional that a girl of a darker complexion is actually attractive. Celebrities, stop putting extraneous powders and lighteners on your skin: we all know what you used to look like and we still love you. And people of color: let’s not continue to perpetuate an oppressive cycle of self-loathing of our appearance and heritage. If this can be accomplished, then perhaps even in our own race we can truly make our lives not be judged by the color of our skin but by the content of our character.


    (adapted from www.huffingtonpost.com, 14/02/2013)

    The author of the article criticizes the fact that the producers:
    Escolha uma alternativa para a questão 4d46e6a4-fd
  • Linguagens

    Inglês

    Beyonce, colorism, and why all of this needs to end


    by Ernest Owens


        Yes, the Super Bowl was on fire. As one who is very critical of halftime show performances, I cannot deny that Beyoncé brought the energy and attention. All of this led to her releasing her tour dates for the Mrs. Carter Show. As excited as I was to actually buy these tickets, something turned me off. The poster.


    Imagem da questão de Inglês, Escola Superior de Propaganda e Marketing 2018, Interpretação de texto | Reading comprehension


       If you haven’t seen the photographs for Beyonce’s new world tour, you probably wouldn’t even recognize her. You will see an image of what looks like a Victorian white woman in the Elizabethan era. Her (prosthetic) blonde hair puffed and extended to reveal a face that is almost as white as snow. Lips red and her skin powdered. This is not the same bronze Beyonce that I saw rocking the stage in an all female band with her darker Destiny’s Child counterparts. I was only left with memories of previous patterns that the multi-Grammy award winning artist had done in previous years in regards to her skin. And I asked myself the question: why, Bey?

         Let’s not act like this is something new. Over the years, it seems as though Beyonce has gotten lighter as she has gotten older. No, this is not genetics and let’s not pretend her skin color in her first Destiny’s Child album cover matches that of her latest album. Whether it is that highly controversial Revlon advertisement or her own album cover art, Beyonce has consistently been called out on alterations done to her pigments.

        What does this say about our society for black women? It tells me that, an independent, confident and successful woman of color still struggles to have the confidence to fully embrace the skin she is in. If one of the most powerful women in entertainment feels she has to lighten her skin for projection, what does that say for the rest of us?

        Believe it or not, colorism, the stigma associated with skin complexion, has been an ill that has not yet been dissolved by the black community. What was first given to us by slave masters in separating the house slaves from the field ones, has now taken place in how we objectify our women and each other.

        This is pretty problematic in many ways. It’s first of all self-loathing and unnecessary for today’s times. The fact that our nation had an African-American first lady with a complexion that isn’t on the lighter side of the spectrum, nor does it try to be, shows a compelling advancement in appreciation for all women of color in many ways.

         Furthermore, the only reason why such stigma in our country continues is contributed to our own behavior that is shaped by the influential people of color around us. It devastated me when I saw that Sammy Sosa had lightened his skin. As successful as he was in a field that was not necessarily fixated on male skin complexion, it saddened me to see him do it. In many ways, it even made me reflect back on the transition of the late great Michael Jackson and what explanations he had for such a more pale white appearance.

        And why does all of this matter? Because I grew up hearing stories of young dark black girls getting their faces scrubbed with skin lightening soaps out of their free will. Tales of young women being abandoned by their mothers because they were too dark.

        If this is the reality that had more implications back in the early 20th century than it does now, please stop it. Stop trying to explain why you are dating the ebony skin girl. Stop making it seem exceptional that a girl of a darker complexion is actually attractive. Celebrities, stop putting extraneous powders and lighteners on your skin: we all know what you used to look like and we still love you. And people of color: let’s not continue to perpetuate an oppressive cycle of self-loathing of our appearance and heritage. If this can be accomplished, then perhaps even in our own race we can truly make our lives not be judged by the color of our skin but by the content of our character.


    (adapted from www.huffingtonpost.com, 14/02/2013)

    According the article:
    Escolha uma alternativa para a questão 4d4a505a-fd
  • Linguagens

    Inglês

    Beyonce, colorism, and why all of this needs to end


    by Ernest Owens


        Yes, the Super Bowl was on fire. As one who is very critical of halftime show performances, I cannot deny that Beyoncé brought the energy and attention. All of this led to her releasing her tour dates for the Mrs. Carter Show. As excited as I was to actually buy these tickets, something turned me off. The poster.


    Imagem da questão de Inglês, Escola Superior de Propaganda e Marketing 2018, Interpretação de texto | Reading comprehension


       If you haven’t seen the photographs for Beyonce’s new world tour, you probably wouldn’t even recognize her. You will see an image of what looks like a Victorian white woman in the Elizabethan era. Her (prosthetic) blonde hair puffed and extended to reveal a face that is almost as white as snow. Lips red and her skin powdered. This is not the same bronze Beyonce that I saw rocking the stage in an all female band with her darker Destiny’s Child counterparts. I was only left with memories of previous patterns that the multi-Grammy award winning artist had done in previous years in regards to her skin. And I asked myself the question: why, Bey?

         Let’s not act like this is something new. Over the years, it seems as though Beyonce has gotten lighter as she has gotten older. No, this is not genetics and let’s not pretend her skin color in her first Destiny’s Child album cover matches that of her latest album. Whether it is that highly controversial Revlon advertisement or her own album cover art, Beyonce has consistently been called out on alterations done to her pigments.

        What does this say about our society for black women? It tells me that, an independent, confident and successful woman of color still struggles to have the confidence to fully embrace the skin she is in. If one of the most powerful women in entertainment feels she has to lighten her skin for projection, what does that say for the rest of us?

        Believe it or not, colorism, the stigma associated with skin complexion, has been an ill that has not yet been dissolved by the black community. What was first given to us by slave masters in separating the house slaves from the field ones, has now taken place in how we objectify our women and each other.

        This is pretty problematic in many ways. It’s first of all self-loathing and unnecessary for today’s times. The fact that our nation had an African-American first lady with a complexion that isn’t on the lighter side of the spectrum, nor does it try to be, shows a compelling advancement in appreciation for all women of color in many ways.

         Furthermore, the only reason why such stigma in our country continues is contributed to our own behavior that is shaped by the influential people of color around us. It devastated me when I saw that Sammy Sosa had lightened his skin. As successful as he was in a field that was not necessarily fixated on male skin complexion, it saddened me to see him do it. In many ways, it even made me reflect back on the transition of the late great Michael Jackson and what explanations he had for such a more pale white appearance.

        And why does all of this matter? Because I grew up hearing stories of young dark black girls getting their faces scrubbed with skin lightening soaps out of their free will. Tales of young women being abandoned by their mothers because they were too dark.

        If this is the reality that had more implications back in the early 20th century than it does now, please stop it. Stop trying to explain why you are dating the ebony skin girl. Stop making it seem exceptional that a girl of a darker complexion is actually attractive. Celebrities, stop putting extraneous powders and lighteners on your skin: we all know what you used to look like and we still love you. And people of color: let’s not continue to perpetuate an oppressive cycle of self-loathing of our appearance and heritage. If this can be accomplished, then perhaps even in our own race we can truly make our lives not be judged by the color of our skin but by the content of our character.


    (adapted from www.huffingtonpost.com, 14/02/2013)

    The pronoun “it” in the phrase “nor does it try to be”, bold faced, in paragraph 6 refers to:
    Escolha uma alternativa para a questão 4d4deecb-fd
  • Linguagens

    Inglês

        Theodor Seuss “Ted” Geisel was an American author, political cartoonist, poet, animator, book publisher, and artist, best known for authoring more than 60 children’s books under the pen name Doctor Seuss (abbreviated Dr. Seuss). As World War II began, he turned to political cartoons, drawing over 400 in two years as editorial cartoonist for the left-leaning New York City daily newspaper. He strongly supports US entry into the war. This is one of his creations from 1941:

    Imagem da questão de Inglês, Escola Superior de Propaganda e Marketing 2018, Interpretação de texto | Reading comprehension
    The cartoon:
    Escolha uma alternativa para a questão 4d510432-fd
  • Linguagens

    Inglês

        Theodor Seuss “Ted” Geisel was an American author, political cartoonist, poet, animator, book publisher, and artist, best known for authoring more than 60 children’s books under the pen name Doctor Seuss (abbreviated Dr. Seuss). As World War II began, he turned to political cartoons, drawing over 400 in two years as editorial cartoonist for the left-leaning New York City daily newspaper. He strongly supports US entry into the war. This is one of his creations from 1941:

    Imagem da questão de Inglês, Escola Superior de Propaganda e Marketing 2018, Preposições | Prepositions
    The use of the prepositions “up” and “out” after “chewed” and "spit" change the original meanings of the verbs. With them, the new meaning:
    Escolha uma alternativa para a questão 4d544213-fd
  • Linguagens

    Inglês

    Figura 1 de 3 da questão de Inglês, IF-BA 2014, Interpretação de texto | Reading comprehension
    Figura 2 de 3 da questão de Inglês, IF-BA 2014, Interpretação de texto | Reading comprehension
    Figura 3 de 3 da questão de Inglês, IF-BA 2014, Interpretação de texto | Reading comprehension

    The main idea of the text is:
    Escolha uma alternativa para a questão 4d7ab4fa-e6
  • Linguagens

    Inglês

    Figura 1 de 3 da questão de Inglês, IF-BA 2014, Interpretação de texto | Reading comprehension
    Figura 2 de 3 da questão de Inglês, IF-BA 2014, Interpretação de texto | Reading comprehension
    Figura 3 de 3 da questão de Inglês, IF-BA 2014, Interpretação de texto | Reading comprehension

    An answer by the government to the people on the streets mentioned in Text 01 could be
    Escolha uma alternativa para a questão 4d80b1a1-e6
  • Linguagens

    Inglês

    Figura 1 de 3 da questão de Inglês, IF-BA 2014, Adjetivos | Adjectives
    Figura 2 de 3 da questão de Inglês, IF-BA 2014, Adjetivos | Adjectives
    Figura 3 de 3 da questão de Inglês, IF-BA 2014, Adjetivos | Adjectives

    Observe the propositions that follow. Decide if they are correct or incorrect according to Text 01 and mark the alternative in which there are only correct propositions.


    Excerpt 01: "Protesters say the poorest are being short-changed while the government spends the large bills on new stadiums and glitzy infrastructure for the soccer competition Brazil is hosting next year and the Olympic Games coming in 2016."


    I – There is an example of passive voice.

    II – There is an example of comparative of adjectives.

    III – The noun phrase “glitzy infrastructure for the soccer competition” is formed by a determiner, a pre modifier, a noun and a post modifier.

    IV - “while” indicates simultaneous actions.
    Escolha uma alternativa para a questão 4d850c50-e6
  • Linguagens

    Inglês

    Figura 1 de 3 da questão de Inglês, IF-BA 2014, Interpretação de texto | Reading comprehension
    Figura 2 de 3 da questão de Inglês, IF-BA 2014, Interpretação de texto | Reading comprehension
    Figura 3 de 3 da questão de Inglês, IF-BA 2014, Interpretação de texto | Reading comprehension

    Observe the excerpt from Text 01 that follows. Mark the correct alternative about the use of “where”.

    Excerpt 02: “One death was reported in São Paulo state, where a young man was run over by a SUV at an intersection during a demonstration, state police said.”
    Escolha uma alternativa para a questão 4d88c4a4-e6
  • Linguagens

    Inglês

    Figura 1 de 3 da questão de Inglês, IF-BA 2014, Interpretação de texto | Reading comprehension
    Figura 2 de 3 da questão de Inglês, IF-BA 2014, Interpretação de texto | Reading comprehension
    Figura 3 de 3 da questão de Inglês, IF-BA 2014, Interpretação de texto | Reading comprehension

    Excerpt 03: "You can't go to hospital; you can't see your friends; you can't go to school; you can't go to work…”


    Observing the context, it's correct to say that Excerpt 03 from Text 01 shows
    Escolha uma alternativa para a questão 4d8bf628-e6
  • Linguagens

    Inglês

    Imagem da questão de Inglês, UEPB 2007, Interpretação de texto | Reading comprehension

    The speaker in TEXT A expresses:
    Escolha uma alternativa para a questão 4e0f6098-70
  • Linguagens

    Inglês

    TEXT
       
       HARVARD BUSINESS REVIEW calls data science “the sexiest job in the 21st century,” and by most accounts this hot new field promises to revolutionize industries from business to government, health care to academia. 
       The field has been spawned by the enormous amounts of data that modern technologies create — be it the online behavior of Facebook users, tissue samples of cancer patients, purchasing habits of grocery shoppers or crime statistics of cities. Data scientists are the magicians of the Big Data era. They crunch the data, use mathematical models to analyze it and create narratives or visualizations to explain it, then suggest how to use the information to make decisions. 
         In the last few years, dozens of programs under a variety of names have sprung up in response to the excitement about Big Data, not to mention the six-figure salaries for some recent graduates. In the fall, Columbia will offer new master’s and certificate programs heavy on data. The University of San Francisco will soon graduate its charter class of students with a master’s in analytics.
          Rachel Schutt, a senior research scientist at Johnson Research Labs, taught “Introduction to Data Science” last semester at Columbia (its first course with “data science” in the title). She described the data scientist this way: “a hybrid computer scientist software engineer statistician.” And added: “The best tend to be really curious people, thinkers who ask good questions and are O.K. dealing with unstructured situations and trying to find structure in them.”
          Eurry Kim, a 30-year-old “wannabe data scientist,” is studying at Columbia for a master’s in quantitative methods in the social sciences and plans to use her degree for government service. She discovered the possibilities while working as a corporate tax analyst at the Internal Revenue Service. She might, for example, analyze tax return data to develop algorithms that flag fraudulent filings, or cull national security databases to spot suspicious activity.
         Some of her classmates are hoping to apply their skills to e-commerce, where data about users’ browsing history is gold.
         “This is a generation of kids that grew up with data science around them — Netflix telling them what movies they should watch, Amazon telling them what books they should read — so this is an academic interest with real-world applications,” said Chris Wiggins, a professor of applied mathematics at Columbia who is involved in its new Institute for Data Sciences and Engineering. “And,” he added, “they know it will make them employable.”
      Universities can hardly turn out data scientists fast enough. To meet demand from employers, the United States will need to increase the number of graduates with skills handling large amounts of data by as much as 60 percent, according to a report by McKinsey Global Institute. There will be almost half a million jobs in five years, and a shortage of up to 190,000 qualified data scientists, plus a need for 1.5 million executives and support staff who have an understanding of data.
          Because data science is so new, universities are scrambling to define it and develop curriculums. As an academic field, it cuts across disciplines, with courses in statistics, analytics, computer science and math, coupled with the specialty a student wants to analyze, from patterns in marine life to historical texts.
        With the sheer volume, variety and speed of data today, as well as developing technologies, programs are more than a repackaging of existing courses. “Data science is emerging as an academic discipline, defined not by a mere amalgamation of interdisciplinary fields but as a body of knowledge, a set of professional practices, a professional organization and a set of ethical responsibilities,” said Christopher Starr, chairman of the computer science department at the College of Charleston, one of a few institutions offering data science at the undergraduate level.
         Most master’s degree programs in data science require basic programming skills. They start with what Ms. Schutt describes as the “boring” part — scraping and cleaning raw data and “getting it into a nice table where you can actually analyze it.” Many use data sets provided by businesses or government, and pass back their results. Some host competitions to see which student can come up with the best solution to a company’s problem.
         Studying a Web user’s data has privacy implications. Using data to decide someone’s eligibility for a line of credit or health insurance, or even recommending who they friend on Facebook, can affect their lives. “We’re building these models that have impact on human life,” Ms. Schutt said. “How can we do that carefully?” Ethics classes address these questions.
           Finally, students have to learn to communicate their findings, visually and orally, and they need business know-how, perhaps to develop new products.

    From: www.nytimes.com
    According to the text, besides being referred to as a sexy job in our century, data science
    Escolha uma alternativa para a questão 4e2f0772-af
  • Linguagens

    Inglês

    TEXT
       
       HARVARD BUSINESS REVIEW calls data science “the sexiest job in the 21st century,” and by most accounts this hot new field promises to revolutionize industries from business to government, health care to academia. 
       The field has been spawned by the enormous amounts of data that modern technologies create — be it the online behavior of Facebook users, tissue samples of cancer patients, purchasing habits of grocery shoppers or crime statistics of cities. Data scientists are the magicians of the Big Data era. They crunch the data, use mathematical models to analyze it and create narratives or visualizations to explain it, then suggest how to use the information to make decisions. 
         In the last few years, dozens of programs under a variety of names have sprung up in response to the excitement about Big Data, not to mention the six-figure salaries for some recent graduates. In the fall, Columbia will offer new master’s and certificate programs heavy on data. The University of San Francisco will soon graduate its charter class of students with a master’s in analytics.
          Rachel Schutt, a senior research scientist at Johnson Research Labs, taught “Introduction to Data Science” last semester at Columbia (its first course with “data science” in the title). She described the data scientist this way: “a hybrid computer scientist software engineer statistician.” And added: “The best tend to be really curious people, thinkers who ask good questions and are O.K. dealing with unstructured situations and trying to find structure in them.”
          Eurry Kim, a 30-year-old “wannabe data scientist,” is studying at Columbia for a master’s in quantitative methods in the social sciences and plans to use her degree for government service. She discovered the possibilities while working as a corporate tax analyst at the Internal Revenue Service. She might, for example, analyze tax return data to develop algorithms that flag fraudulent filings, or cull national security databases to spot suspicious activity.
         Some of her classmates are hoping to apply their skills to e-commerce, where data about users’ browsing history is gold.
         “This is a generation of kids that grew up with data science around them — Netflix telling them what movies they should watch, Amazon telling them what books they should read — so this is an academic interest with real-world applications,” said Chris Wiggins, a professor of applied mathematics at Columbia who is involved in its new Institute for Data Sciences and Engineering. “And,” he added, “they know it will make them employable.”
      Universities can hardly turn out data scientists fast enough. To meet demand from employers, the United States will need to increase the number of graduates with skills handling large amounts of data by as much as 60 percent, according to a report by McKinsey Global Institute. There will be almost half a million jobs in five years, and a shortage of up to 190,000 qualified data scientists, plus a need for 1.5 million executives and support staff who have an understanding of data.
          Because data science is so new, universities are scrambling to define it and develop curriculums. As an academic field, it cuts across disciplines, with courses in statistics, analytics, computer science and math, coupled with the specialty a student wants to analyze, from patterns in marine life to historical texts.
        With the sheer volume, variety and speed of data today, as well as developing technologies, programs are more than a repackaging of existing courses. “Data science is emerging as an academic discipline, defined not by a mere amalgamation of interdisciplinary fields but as a body of knowledge, a set of professional practices, a professional organization and a set of ethical responsibilities,” said Christopher Starr, chairman of the computer science department at the College of Charleston, one of a few institutions offering data science at the undergraduate level.
         Most master’s degree programs in data science require basic programming skills. They start with what Ms. Schutt describes as the “boring” part — scraping and cleaning raw data and “getting it into a nice table where you can actually analyze it.” Many use data sets provided by businesses or government, and pass back their results. Some host competitions to see which student can come up with the best solution to a company’s problem.
         Studying a Web user’s data has privacy implications. Using data to decide someone’s eligibility for a line of credit or health insurance, or even recommending who they friend on Facebook, can affect their lives. “We’re building these models that have impact on human life,” Ms. Schutt said. “How can we do that carefully?” Ethics classes address these questions.
           Finally, students have to learn to communicate their findings, visually and orally, and they need business know-how, perhaps to develop new products.

    From: www.nytimes.com
    As to the way academic institutions are reacting in response to the enormous need of professionals in the field of data science, the text informs that
    Escolha uma alternativa para a questão 4e332760-af
  • Linguagens

    Inglês

    TEXT
       
       HARVARD BUSINESS REVIEW calls data science “the sexiest job in the 21st century,” and by most accounts this hot new field promises to revolutionize industries from business to government, health care to academia. 
       The field has been spawned by the enormous amounts of data that modern technologies create — be it the online behavior of Facebook users, tissue samples of cancer patients, purchasing habits of grocery shoppers or crime statistics of cities. Data scientists are the magicians of the Big Data era. They crunch the data, use mathematical models to analyze it and create narratives or visualizations to explain it, then suggest how to use the information to make decisions. 
         In the last few years, dozens of programs under a variety of names have sprung up in response to the excitement about Big Data, not to mention the six-figure salaries for some recent graduates. In the fall, Columbia will offer new master’s and certificate programs heavy on data. The University of San Francisco will soon graduate its charter class of students with a master’s in analytics.
          Rachel Schutt, a senior research scientist at Johnson Research Labs, taught “Introduction to Data Science” last semester at Columbia (its first course with “data science” in the title). She described the data scientist this way: “a hybrid computer scientist software engineer statistician.” And added: “The best tend to be really curious people, thinkers who ask good questions and are O.K. dealing with unstructured situations and trying to find structure in them.”
          Eurry Kim, a 30-year-old “wannabe data scientist,” is studying at Columbia for a master’s in quantitative methods in the social sciences and plans to use her degree for government service. She discovered the possibilities while working as a corporate tax analyst at the Internal Revenue Service. She might, for example, analyze tax return data to develop algorithms that flag fraudulent filings, or cull national security databases to spot suspicious activity.
         Some of her classmates are hoping to apply their skills to e-commerce, where data about users’ browsing history is gold.
         “This is a generation of kids that grew up with data science around them — Netflix telling them what movies they should watch, Amazon telling them what books they should read — so this is an academic interest with real-world applications,” said Chris Wiggins, a professor of applied mathematics at Columbia who is involved in its new Institute for Data Sciences and Engineering. “And,” he added, “they know it will make them employable.”
      Universities can hardly turn out data scientists fast enough. To meet demand from employers, the United States will need to increase the number of graduates with skills handling large amounts of data by as much as 60 percent, according to a report by McKinsey Global Institute. There will be almost half a million jobs in five years, and a shortage of up to 190,000 qualified data scientists, plus a need for 1.5 million executives and support staff who have an understanding of data.
          Because data science is so new, universities are scrambling to define it and develop curriculums. As an academic field, it cuts across disciplines, with courses in statistics, analytics, computer science and math, coupled with the specialty a student wants to analyze, from patterns in marine life to historical texts.
        With the sheer volume, variety and speed of data today, as well as developing technologies, programs are more than a repackaging of existing courses. “Data science is emerging as an academic discipline, defined not by a mere amalgamation of interdisciplinary fields but as a body of knowledge, a set of professional practices, a professional organization and a set of ethical responsibilities,” said Christopher Starr, chairman of the computer science department at the College of Charleston, one of a few institutions offering data science at the undergraduate level.
         Most master’s degree programs in data science require basic programming skills. They start with what Ms. Schutt describes as the “boring” part — scraping and cleaning raw data and “getting it into a nice table where you can actually analyze it.” Many use data sets provided by businesses or government, and pass back their results. Some host competitions to see which student can come up with the best solution to a company’s problem.
         Studying a Web user’s data has privacy implications. Using data to decide someone’s eligibility for a line of credit or health insurance, or even recommending who they friend on Facebook, can affect their lives. “We’re building these models that have impact on human life,” Ms. Schutt said. “How can we do that carefully?” Ethics classes address these questions.
           Finally, students have to learn to communicate their findings, visually and orally, and they need business know-how, perhaps to develop new products.

    From: www.nytimes.com
    According to the text, in terms of what is required from a student in order to apply for a master’s degree in the area of data science, one must have
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    TEXT
       
       HARVARD BUSINESS REVIEW calls data science “the sexiest job in the 21st century,” and by most accounts this hot new field promises to revolutionize industries from business to government, health care to academia. 
       The field has been spawned by the enormous amounts of data that modern technologies create — be it the online behavior of Facebook users, tissue samples of cancer patients, purchasing habits of grocery shoppers or crime statistics of cities. Data scientists are the magicians of the Big Data era. They crunch the data, use mathematical models to analyze it and create narratives or visualizations to explain it, then suggest how to use the information to make decisions. 
         In the last few years, dozens of programs under a variety of names have sprung up in response to the excitement about Big Data, not to mention the six-figure salaries for some recent graduates. In the fall, Columbia will offer new master’s and certificate programs heavy on data. The University of San Francisco will soon graduate its charter class of students with a master’s in analytics.
          Rachel Schutt, a senior research scientist at Johnson Research Labs, taught “Introduction to Data Science” last semester at Columbia (its first course with “data science” in the title). She described the data scientist this way: “a hybrid computer scientist software engineer statistician.” And added: “The best tend to be really curious people, thinkers who ask good questions and are O.K. dealing with unstructured situations and trying to find structure in them.”
          Eurry Kim, a 30-year-old “wannabe data scientist,” is studying at Columbia for a master’s in quantitative methods in the social sciences and plans to use her degree for government service. She discovered the possibilities while working as a corporate tax analyst at the Internal Revenue Service. She might, for example, analyze tax return data to develop algorithms that flag fraudulent filings, or cull national security databases to spot suspicious activity.
         Some of her classmates are hoping to apply their skills to e-commerce, where data about users’ browsing history is gold.
         “This is a generation of kids that grew up with data science around them — Netflix telling them what movies they should watch, Amazon telling them what books they should read — so this is an academic interest with real-world applications,” said Chris Wiggins, a professor of applied mathematics at Columbia who is involved in its new Institute for Data Sciences and Engineering. “And,” he added, “they know it will make them employable.”
      Universities can hardly turn out data scientists fast enough. To meet demand from employers, the United States will need to increase the number of graduates with skills handling large amounts of data by as much as 60 percent, according to a report by McKinsey Global Institute. There will be almost half a million jobs in five years, and a shortage of up to 190,000 qualified data scientists, plus a need for 1.5 million executives and support staff who have an understanding of data.
          Because data science is so new, universities are scrambling to define it and develop curriculums. As an academic field, it cuts across disciplines, with courses in statistics, analytics, computer science and math, coupled with the specialty a student wants to analyze, from patterns in marine life to historical texts.
        With the sheer volume, variety and speed of data today, as well as developing technologies, programs are more than a repackaging of existing courses. “Data science is emerging as an academic discipline, defined not by a mere amalgamation of interdisciplinary fields but as a body of knowledge, a set of professional practices, a professional organization and a set of ethical responsibilities,” said Christopher Starr, chairman of the computer science department at the College of Charleston, one of a few institutions offering data science at the undergraduate level.
         Most master’s degree programs in data science require basic programming skills. They start with what Ms. Schutt describes as the “boring” part — scraping and cleaning raw data and “getting it into a nice table where you can actually analyze it.” Many use data sets provided by businesses or government, and pass back their results. Some host competitions to see which student can come up with the best solution to a company’s problem.
         Studying a Web user’s data has privacy implications. Using data to decide someone’s eligibility for a line of credit or health insurance, or even recommending who they friend on Facebook, can affect their lives. “We’re building these models that have impact on human life,” Ms. Schutt said. “How can we do that carefully?” Ethics classes address these questions.
           Finally, students have to learn to communicate their findings, visually and orally, and they need business know-how, perhaps to develop new products.

    From: www.nytimes.com
    Some of Eurry Kim’s peers expect to use their abilities on
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  • Linguagens

    Inglês

    TEXT
       
       HARVARD BUSINESS REVIEW calls data science “the sexiest job in the 21st century,” and by most accounts this hot new field promises to revolutionize industries from business to government, health care to academia. 
       The field has been spawned by the enormous amounts of data that modern technologies create — be it the online behavior of Facebook users, tissue samples of cancer patients, purchasing habits of grocery shoppers or crime statistics of cities. Data scientists are the magicians of the Big Data era. They crunch the data, use mathematical models to analyze it and create narratives or visualizations to explain it, then suggest how to use the information to make decisions. 
         In the last few years, dozens of programs under a variety of names have sprung up in response to the excitement about Big Data, not to mention the six-figure salaries for some recent graduates. In the fall, Columbia will offer new master’s and certificate programs heavy on data. The University of San Francisco will soon graduate its charter class of students with a master’s in analytics.
          Rachel Schutt, a senior research scientist at Johnson Research Labs, taught “Introduction to Data Science” last semester at Columbia (its first course with “data science” in the title). She described the data scientist this way: “a hybrid computer scientist software engineer statistician.” And added: “The best tend to be really curious people, thinkers who ask good questions and are O.K. dealing with unstructured situations and trying to find structure in them.”
          Eurry Kim, a 30-year-old “wannabe data scientist,” is studying at Columbia for a master’s in quantitative methods in the social sciences and plans to use her degree for government service. She discovered the possibilities while working as a corporate tax analyst at the Internal Revenue Service. She might, for example, analyze tax return data to develop algorithms that flag fraudulent filings, or cull national security databases to spot suspicious activity.
         Some of her classmates are hoping to apply their skills to e-commerce, where data about users’ browsing history is gold.
         “This is a generation of kids that grew up with data science around them — Netflix telling them what movies they should watch, Amazon telling them what books they should read — so this is an academic interest with real-world applications,” said Chris Wiggins, a professor of applied mathematics at Columbia who is involved in its new Institute for Data Sciences and Engineering. “And,” he added, “they know it will make them employable.”
      Universities can hardly turn out data scientists fast enough. To meet demand from employers, the United States will need to increase the number of graduates with skills handling large amounts of data by as much as 60 percent, according to a report by McKinsey Global Institute. There will be almost half a million jobs in five years, and a shortage of up to 190,000 qualified data scientists, plus a need for 1.5 million executives and support staff who have an understanding of data.
          Because data science is so new, universities are scrambling to define it and develop curriculums. As an academic field, it cuts across disciplines, with courses in statistics, analytics, computer science and math, coupled with the specialty a student wants to analyze, from patterns in marine life to historical texts.
        With the sheer volume, variety and speed of data today, as well as developing technologies, programs are more than a repackaging of existing courses. “Data science is emerging as an academic discipline, defined not by a mere amalgamation of interdisciplinary fields but as a body of knowledge, a set of professional practices, a professional organization and a set of ethical responsibilities,” said Christopher Starr, chairman of the computer science department at the College of Charleston, one of a few institutions offering data science at the undergraduate level.
         Most master’s degree programs in data science require basic programming skills. They start with what Ms. Schutt describes as the “boring” part — scraping and cleaning raw data and “getting it into a nice table where you can actually analyze it.” Many use data sets provided by businesses or government, and pass back their results. Some host competitions to see which student can come up with the best solution to a company’s problem.
         Studying a Web user’s data has privacy implications. Using data to decide someone’s eligibility for a line of credit or health insurance, or even recommending who they friend on Facebook, can affect their lives. “We’re building these models that have impact on human life,” Ms. Schutt said. “How can we do that carefully?” Ethics classes address these questions.
           Finally, students have to learn to communicate their findings, visually and orally, and they need business know-how, perhaps to develop new products.

    From: www.nytimes.com
    Considering the word shopper in the text, an example of a word with similar meaning is
    Escolha uma alternativa para a questão 4e3ed6ed-af
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    Inglês

    TEXT
       
       HARVARD BUSINESS REVIEW calls data science “the sexiest job in the 21st century,” and by most accounts this hot new field promises to revolutionize industries from business to government, health care to academia. 
       The field has been spawned by the enormous amounts of data that modern technologies create — be it the online behavior of Facebook users, tissue samples of cancer patients, purchasing habits of grocery shoppers or crime statistics of cities. Data scientists are the magicians of the Big Data era. They crunch the data, use mathematical models to analyze it and create narratives or visualizations to explain it, then suggest how to use the information to make decisions. 
         In the last few years, dozens of programs under a variety of names have sprung up in response to the excitement about Big Data, not to mention the six-figure salaries for some recent graduates. In the fall, Columbia will offer new master’s and certificate programs heavy on data. The University of San Francisco will soon graduate its charter class of students with a master’s in analytics.
          Rachel Schutt, a senior research scientist at Johnson Research Labs, taught “Introduction to Data Science” last semester at Columbia (its first course with “data science” in the title). She described the data scientist this way: “a hybrid computer scientist software engineer statistician.” And added: “The best tend to be really curious people, thinkers who ask good questions and are O.K. dealing with unstructured situations and trying to find structure in them.”
          Eurry Kim, a 30-year-old “wannabe data scientist,” is studying at Columbia for a master’s in quantitative methods in the social sciences and plans to use her degree for government service. She discovered the possibilities while working as a corporate tax analyst at the Internal Revenue Service. She might, for example, analyze tax return data to develop algorithms that flag fraudulent filings, or cull national security databases to spot suspicious activity.
         Some of her classmates are hoping to apply their skills to e-commerce, where data about users’ browsing history is gold.
         “This is a generation of kids that grew up with data science around them — Netflix telling them what movies they should watch, Amazon telling them what books they should read — so this is an academic interest with real-world applications,” said Chris Wiggins, a professor of applied mathematics at Columbia who is involved in its new Institute for Data Sciences and Engineering. “And,” he added, “they know it will make them employable.”
      Universities can hardly turn out data scientists fast enough. To meet demand from employers, the United States will need to increase the number of graduates with skills handling large amounts of data by as much as 60 percent, according to a report by McKinsey Global Institute. There will be almost half a million jobs in five years, and a shortage of up to 190,000 qualified data scientists, plus a need for 1.5 million executives and support staff who have an understanding of data.
          Because data science is so new, universities are scrambling to define it and develop curriculums. As an academic field, it cuts across disciplines, with courses in statistics, analytics, computer science and math, coupled with the specialty a student wants to analyze, from patterns in marine life to historical texts.
        With the sheer volume, variety and speed of data today, as well as developing technologies, programs are more than a repackaging of existing courses. “Data science is emerging as an academic discipline, defined not by a mere amalgamation of interdisciplinary fields but as a body of knowledge, a set of professional practices, a professional organization and a set of ethical responsibilities,” said Christopher Starr, chairman of the computer science department at the College of Charleston, one of a few institutions offering data science at the undergraduate level.
         Most master’s degree programs in data science require basic programming skills. They start with what Ms. Schutt describes as the “boring” part — scraping and cleaning raw data and “getting it into a nice table where you can actually analyze it.” Many use data sets provided by businesses or government, and pass back their results. Some host competitions to see which student can come up with the best solution to a company’s problem.
         Studying a Web user’s data has privacy implications. Using data to decide someone’s eligibility for a line of credit or health insurance, or even recommending who they friend on Facebook, can affect their lives. “We’re building these models that have impact on human life,” Ms. Schutt said. “How can we do that carefully?” Ethics classes address these questions.
           Finally, students have to learn to communicate their findings, visually and orally, and they need business know-how, perhaps to develop new products.

    From: www.nytimes.com
    The functions of the words purchasing, dealing, filings, programming and recommending in the text are respectively
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    Inglês

    TEXT
       
       HARVARD BUSINESS REVIEW calls data science “the sexiest job in the 21st century,” and by most accounts this hot new field promises to revolutionize industries from business to government, health care to academia. 
       The field has been spawned by the enormous amounts of data that modern technologies create — be it the online behavior of Facebook users, tissue samples of cancer patients, purchasing habits of grocery shoppers or crime statistics of cities. Data scientists are the magicians of the Big Data era. They crunch the data, use mathematical models to analyze it and create narratives or visualizations to explain it, then suggest how to use the information to make decisions. 
         In the last few years, dozens of programs under a variety of names have sprung up in response to the excitement about Big Data, not to mention the six-figure salaries for some recent graduates. In the fall, Columbia will offer new master’s and certificate programs heavy on data. The University of San Francisco will soon graduate its charter class of students with a master’s in analytics.
          Rachel Schutt, a senior research scientist at Johnson Research Labs, taught “Introduction to Data Science” last semester at Columbia (its first course with “data science” in the title). She described the data scientist this way: “a hybrid computer scientist software engineer statistician.” And added: “The best tend to be really curious people, thinkers who ask good questions and are O.K. dealing with unstructured situations and trying to find structure in them.”
          Eurry Kim, a 30-year-old “wannabe data scientist,” is studying at Columbia for a master’s in quantitative methods in the social sciences and plans to use her degree for government service. She discovered the possibilities while working as a corporate tax analyst at the Internal Revenue Service. She might, for example, analyze tax return data to develop algorithms that flag fraudulent filings, or cull national security databases to spot suspicious activity.
         Some of her classmates are hoping to apply their skills to e-commerce, where data about users’ browsing history is gold.
         “This is a generation of kids that grew up with data science around them — Netflix telling them what movies they should watch, Amazon telling them what books they should read — so this is an academic interest with real-world applications,” said Chris Wiggins, a professor of applied mathematics at Columbia who is involved in its new Institute for Data Sciences and Engineering. “And,” he added, “they know it will make them employable.”
      Universities can hardly turn out data scientists fast enough. To meet demand from employers, the United States will need to increase the number of graduates with skills handling large amounts of data by as much as 60 percent, according to a report by McKinsey Global Institute. There will be almost half a million jobs in five years, and a shortage of up to 190,000 qualified data scientists, plus a need for 1.5 million executives and support staff who have an understanding of data.
          Because data science is so new, universities are scrambling to define it and develop curriculums. As an academic field, it cuts across disciplines, with courses in statistics, analytics, computer science and math, coupled with the specialty a student wants to analyze, from patterns in marine life to historical texts.
        With the sheer volume, variety and speed of data today, as well as developing technologies, programs are more than a repackaging of existing courses. “Data science is emerging as an academic discipline, defined not by a mere amalgamation of interdisciplinary fields but as a body of knowledge, a set of professional practices, a professional organization and a set of ethical responsibilities,” said Christopher Starr, chairman of the computer science department at the College of Charleston, one of a few institutions offering data science at the undergraduate level.
         Most master’s degree programs in data science require basic programming skills. They start with what Ms. Schutt describes as the “boring” part — scraping and cleaning raw data and “getting it into a nice table where you can actually analyze it.” Many use data sets provided by businesses or government, and pass back their results. Some host competitions to see which student can come up with the best solution to a company’s problem.
         Studying a Web user’s data has privacy implications. Using data to decide someone’s eligibility for a line of credit or health insurance, or even recommending who they friend on Facebook, can affect their lives. “We’re building these models that have impact on human life,” Ms. Schutt said. “How can we do that carefully?” Ethics classes address these questions.
           Finally, students have to learn to communicate their findings, visually and orally, and they need business know-how, perhaps to develop new products.

    From: www.nytimes.com
    In terms of verb tense, the sentences “Rachel Schutt, a senior research scientist at Johnson Research Labs, taught ‘Introduction to Data Science’ last semester at Columbia.”, “In the last few years, dozens of programs under a variety of names have sprung up in response to the excitement about Big Data.” and “Most master’s degree programs in data science require basic programming skills.” are, respectively, in the
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    TEXT
       
       HARVARD BUSINESS REVIEW calls data science “the sexiest job in the 21st century,” and by most accounts this hot new field promises to revolutionize industries from business to government, health care to academia. 
       The field has been spawned by the enormous amounts of data that modern technologies create — be it the online behavior of Facebook users, tissue samples of cancer patients, purchasing habits of grocery shoppers or crime statistics of cities. Data scientists are the magicians of the Big Data era. They crunch the data, use mathematical models to analyze it and create narratives or visualizations to explain it, then suggest how to use the information to make decisions. 
         In the last few years, dozens of programs under a variety of names have sprung up in response to the excitement about Big Data, not to mention the six-figure salaries for some recent graduates. In the fall, Columbia will offer new master’s and certificate programs heavy on data. The University of San Francisco will soon graduate its charter class of students with a master’s in analytics.
          Rachel Schutt, a senior research scientist at Johnson Research Labs, taught “Introduction to Data Science” last semester at Columbia (its first course with “data science” in the title). She described the data scientist this way: “a hybrid computer scientist software engineer statistician.” And added: “The best tend to be really curious people, thinkers who ask good questions and are O.K. dealing with unstructured situations and trying to find structure in them.”
          Eurry Kim, a 30-year-old “wannabe data scientist,” is studying at Columbia for a master’s in quantitative methods in the social sciences and plans to use her degree for government service. She discovered the possibilities while working as a corporate tax analyst at the Internal Revenue Service. She might, for example, analyze tax return data to develop algorithms that flag fraudulent filings, or cull national security databases to spot suspicious activity.
         Some of her classmates are hoping to apply their skills to e-commerce, where data about users’ browsing history is gold.
         “This is a generation of kids that grew up with data science around them — Netflix telling them what movies they should watch, Amazon telling them what books they should read — so this is an academic interest with real-world applications,” said Chris Wiggins, a professor of applied mathematics at Columbia who is involved in its new Institute for Data Sciences and Engineering. “And,” he added, “they know it will make them employable.”
      Universities can hardly turn out data scientists fast enough. To meet demand from employers, the United States will need to increase the number of graduates with skills handling large amounts of data by as much as 60 percent, according to a report by McKinsey Global Institute. There will be almost half a million jobs in five years, and a shortage of up to 190,000 qualified data scientists, plus a need for 1.5 million executives and support staff who have an understanding of data.
          Because data science is so new, universities are scrambling to define it and develop curriculums. As an academic field, it cuts across disciplines, with courses in statistics, analytics, computer science and math, coupled with the specialty a student wants to analyze, from patterns in marine life to historical texts.
        With the sheer volume, variety and speed of data today, as well as developing technologies, programs are more than a repackaging of existing courses. “Data science is emerging as an academic discipline, defined not by a mere amalgamation of interdisciplinary fields but as a body of knowledge, a set of professional practices, a professional organization and a set of ethical responsibilities,” said Christopher Starr, chairman of the computer science department at the College of Charleston, one of a few institutions offering data science at the undergraduate level.
         Most master’s degree programs in data science require basic programming skills. They start with what Ms. Schutt describes as the “boring” part — scraping and cleaning raw data and “getting it into a nice table where you can actually analyze it.” Many use data sets provided by businesses or government, and pass back their results. Some host competitions to see which student can come up with the best solution to a company’s problem.
         Studying a Web user’s data has privacy implications. Using data to decide someone’s eligibility for a line of credit or health insurance, or even recommending who they friend on Facebook, can affect their lives. “We’re building these models that have impact on human life,” Ms. Schutt said. “How can we do that carefully?” Ethics classes address these questions.
           Finally, students have to learn to communicate their findings, visually and orally, and they need business know-how, perhaps to develop new products.

    From: www.nytimes.com
    The sentences “They crunch the data, use mathematical models to analyze it and create narratives or visualizations to explain it…” and “In the last few years, dozens of programs under a variety of names have sprung up in response to the excitement about Big Data...” should be classified respectively as
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