Prova de 2013: Universidade Estadual do Ceará (UECE) — questões com gabarito

Para la pregunta abajo, presentamos cuatro respuestas. Elija la correcta.

“¿Le mandaste eso a tu padre?”

En la expresión “Comer y beber” (noveno consejo) hay el empleo de la conjunción copulativa “y”. Dicha conjunción está también correcta en

“los brazos y las piernas” (décimo consejo) son dos partes del cuerpo humano. Los “codos” también lo son y están en

Siendo el avión el medio de trasporte más seguro, muchas personas tienen miedo a viajar en este medio de transporte y tratan de evitarlo a toda costa.

Para ello, la agencia de viajes Rumbo ha elaborado una lista que incluye diez consejos a que el viaje en avión pase de ser una mala experiencia a algo con lo que finalmente podamos disfrutar. 

NOVENO CONSEJO

Comer y beber en exceso puede ser perjudicial. Una copa de vino ayuda a relajarse, pero el exceso de alcohol puede generar pensamientos negativos y difíciles de controlar, llegando a resultar perjudicial cuando se trata de vuelos de larga duración.

Siendo el avión el medio de trasporte más seguro, muchas personas tienen miedo a viajar en este medio de transporte y tratan de evitarlo a toda costa.

Para ello, la agencia de viajes Rumbo ha elaborado una lista que incluye diez consejos a que el viaje en avión pase de ser una mala experiencia a algo con lo que finalmente podamos disfrutar. 

CUARTO CONSEJO

Una buena forma de reducir la ansiedad es buscar diferentes distracciones. Una buena idea puede ser la música. Genera emociones positivas y evita lo negativo. Llevar una buena selección de música relajante para escuchar durante el vuelo, especialmente en el despegue y el aterrizaje, los momentos que normalmente provocan más estrés es muy recomendable. También es interesante tener a mano un buen libro o llevar nuestras películas o series favoritas. Otra forma de “evadirse” es entablar conversación con el vecino de asiento. Por último, siempre se puede dormir.

Siendo el avión el medio de trasporte más seguro, muchas personas tienen miedo a viajar en este medio de transporte y tratan de evitarlo a toda costa.

Para ello, la agencia de viajes Rumbo ha elaborado una lista que incluye diez consejos a que el viaje en avión pase de ser una mala experiencia a algo con lo que finalmente podamos disfrutar. 

TERCERO CONSEJO

Es importante ir con tiempo al aeropuerto. Las prisas junto con el temor a perder el avión pueden generar estrés incluso antes de llegar al aeropuerto. Por eso es recomendable salir de casa con tiempo suficiente para poder llegar tranquilamente y poder relajarse.

Siendo el avión el medio de trasporte más seguro, muchas personas tienen miedo a viajar en este medio de transporte y tratan de evitarlo a toda costa.

Para ello, la agencia de viajes Rumbo ha elaborado una lista que incluye diez consejos a que el viaje en avión pase de ser una mala experiencia a algo con lo que finalmente podamos disfrutar. 

SEGUNDO CONSEJO

Conforme se vaya acercando la fecha del vuelo es bueno tratar de entrenar nuestra imaginación. Debemos visualizar todo lo que vamos a hacer para el viaje de manera exitosa, desde que salimos de casa hacia el aeropuerto hasta que aterrizamos en nuestro lugar de destino. Además tenemos que imaginarnos afrontando la situación con seguridad.

Assinale com V ou F, conforme seja verdadeiro ou falso o que é dito sobre o texto 3.

( ) O aviãozinho de papel despencando do alto é um recurso para dar mais força de persuasão à manchete, cujos termos estão dispostos um abaixo do outro, o que sugere uma queda.

( ) É correto afirmar que a capa da revista Época emprega um recurso da poesia concreta.

( ) O processo de construção da manchete de capa da revista Época inclui substituição e acréscimo de elementos linguísticos, em relação ao texto fonte.

( ) O criador da manchete de Época fez um jogo com dois sentidos do termo real, jogo que foi possível graças à mudança de gênero desse vocábulo.

( ) Na manchete de Época, apresenta-se apenas uma das funções da linguagem: a função informativa.

Está correta, de cima para baixo, a seguinte sequência:

     O texto que você lerá é um excerto retirado do primeiro parágrafo do artigo de opinião “Com um braço só”, escrito por J. R. Guzzo, que trata da corrupção na política. 

Extraído do artigo ”Com um braço só”, de

J.R. Guzzo. VEJA. 21/08/2013.

Observe com atenção o que se diz sobre o excerto seguinte: “Um dos aspectos menos atraentes da personalidade humana é a tendência de muitas pessoas de só condenar os vícios que não praticam, ou pelos quais não se sentem atraídas” (linhas 49-53).

I. Tender é o verbo correlato de tendência. Indica ação-processo, o que sugere que esse movimento pode não chegar ao ponto previsto.

II. A tendência pode ser somente uma propensão, uma inclinação, uma vocação ou pendor.

III. Na introdução do texto de Guzzo, existe a sugestão de que a tendência mencionada pelo enunciador ultrapassa os limites da simples propensão ou vocação.

Ela se realizaria concretamente. Está correto o que se diz em

Caro candidato, o primeiro texto desta prova foi extraído do livro de memórias do escritor e jornalista carioca, que nasceu em 1926, Carlos Heitor Cony. Um livro de memórias é “relato que alguém faz, frequentemente, na forma de obra literária, a partir de acontecimentos históricos dos quais participou ou foi testemunha, ou que estão fundamentados em sua vida particular”. Não deve ser confundido com autobiografia. 

CONY, Carlos Heitor. In: Eu aos pedaços:

memórias. São Paulo: Leya, 2010. p. 114-115. 

A descrição, feita pelo cronista, da cadeira em que se sentou para engraxar o sapato sugere que o móvel

Caro candidato, o primeiro texto desta prova foi extraído do livro de memórias do escritor e jornalista carioca, que nasceu em 1926, Carlos Heitor Cony. Um livro de memórias é “relato que alguém faz, frequentemente, na forma de obra literária, a partir de acontecimentos históricos dos quais participou ou foi testemunha, ou que estão fundamentados em sua vida particular”. Não deve ser confundido com autobiografia. 

CONY, Carlos Heitor. In: Eu aos pedaços:

memórias. São Paulo: Leya, 2010. p. 114-115. 

Atente à caracterização do engraxate. Segundo o cronista, ele era gordo e calvo. Essa caracterização

I. está, de algum modo, relacionada com as ideias principais do texto.

II. tem uma função textual.

III. atende a uma necessidade de coerência interna do texto.

Estão corretas as complementações contidas em

Caro candidato, o primeiro texto desta prova foi extraído do livro de memórias do escritor e jornalista carioca, que nasceu em 1926, Carlos Heitor Cony. Um livro de memórias é “relato que alguém faz, frequentemente, na forma de obra literária, a partir de acontecimentos históricos dos quais participou ou foi testemunha, ou que estão fundamentados em sua vida particular”. Não deve ser confundido com autobiografia. 

CONY, Carlos Heitor. In: Eu aos pedaços:

memórias. São Paulo: Leya, 2010. p. 114-115. 

Escreva V ou F, conforme seja verdadeiro ou falso o que se afirma sobre referenciação e relações sintático-semânticas.

( ) O enunciado que vai da linha 2 (a partir da expressão “No dia”) à linha 5 (até “milênio”) constitui, na narrativa, uma digressão cuja função discursiva é comprovar o que se afirma nas linhas 1 e 2.

( ) A expressão “esses engraxates” (linha 8) justifica-se, no texto, pela relação indireta com o verbo “engraxar”: o ato de engraxar pressupõe um agente, no caso, um profissional — um engraxate — “esses engraxates”.

( ) Nas expressões “(n)aquela espécie de cadeira canônica [...]” (linhas 10-11) e “Pegou aquele paninho que dá brilho [...]” (linhas 22-23), ao usar o pronome aquele(a), o enunciador não aponta para nenhum elemento da superfície textual, mas aposta no conhecimento de mundo do enunciatário; em algo que acredita estar na memória dele.

( ) Nas palavras do cronista, “Uso-o pouco, em parte para poupá-lo, em parte porque quando posso estou sempre de tênis.” (linhas 17-19), o pronome o(lo) substitui a expressão o meu sapato, na linha 16, funcionando como elemento de coesão entre o enunciado em pauta e o enunciado anterior.

Está correta, de cima para baixo, a seguinte sequência:

Caro candidato, o primeiro texto desta prova foi extraído do livro de memórias do escritor e jornalista carioca, que nasceu em 1926, Carlos Heitor Cony. Um livro de memórias é “relato que alguém faz, frequentemente, na forma de obra literária, a partir de acontecimentos históricos dos quais participou ou foi testemunha, ou que estão fundamentados em sua vida particular”. Não deve ser confundido com autobiografia. 

CONY, Carlos Heitor. In: Eu aos pedaços:

memórias. São Paulo: Leya, 2010. p. 114-115. 

No seguinte enunciado — “Cheguei ao Santos Dumont, o voo estava atrasado, decidi engraxar os sapatos” (linhas 5-7) — a relação entre as orações está implícita. Marque a única alternativa que explicita o sentido que esse enunciado tem no texto.

Caro candidato, o primeiro texto desta prova foi extraído do livro de memórias do escritor e jornalista carioca, que nasceu em 1926, Carlos Heitor Cony. Um livro de memórias é “relato que alguém faz, frequentemente, na forma de obra literária, a partir de acontecimentos históricos dos quais participou ou foi testemunha, ou que estão fundamentados em sua vida particular”. Não deve ser confundido com autobiografia. 

CONY, Carlos Heitor. In: Eu aos pedaços:

memórias. São Paulo: Leya, 2010. p. 114-115. 

Abaixo estão algumas assertivas sobre os dois últimos parágrafos do texto (linhas 37-48). Escreva V para a assertiva verdadeira e F para a assertiva falsa.

( ) Com o troco generoso deixado para o engraxate, o cronista quis disfarçar um preconceito que o dominava naquele momento.

( ) A culpa que o cronista experimenta é tão grande que extrapola aquele incidente pequeno da limpeza do sapato.

( ) O espanto do engraxate ao receber a gorjeta aceita a seguinte leitura: os fregueses habituais não eram tão generosos.

( ) O dinheiro estava para o sentimento de culpa do cronista assim como os votos de felicidade estavam para o sentimento de gratidão que o engraxate experimentava.

Está correta, de cima para baixo, a seguinte sequência.

Caro candidato, o primeiro texto desta prova foi extraído do livro de memórias do escritor e jornalista carioca, que nasceu em 1926, Carlos Heitor Cony. Um livro de memórias é “relato que alguém faz, frequentemente, na forma de obra literária, a partir de acontecimentos históricos dos quais participou ou foi testemunha, ou que estão fundamentados em sua vida particular”. Não deve ser confundido com autobiografia. 

CONY, Carlos Heitor. In: Eu aos pedaços:

memórias. São Paulo: Leya, 2010. p. 114-115. 

Atente ao que se diz do enunciado seguinte: “Olhei meus sapatos e tive vergonha daquele brilho humano salgado como lágrimas” (linhas 46- 48).

I. A vergonha que o cronista tem, na verdade, não é propriamente do brilho do sapato, mas do esforço humano despendido para produzilo.

II. O brilho, que exigiu esforço humano, foi conseguido à custa do pranto do trabalhador.

III. O suor que o engraxate deixou cair sobre o sapato sugere o esforço despendido pelo trabalhador explorado.

Está correto o que se diz somente em

Caro candidato, o primeiro texto desta prova foi extraído do livro de memórias do escritor e jornalista carioca, que nasceu em 1926, Carlos Heitor Cony. Um livro de memórias é “relato que alguém faz, frequentemente, na forma de obra literária, a partir de acontecimentos históricos dos quais participou ou foi testemunha, ou que estão fundamentados em sua vida particular”. Não deve ser confundido com autobiografia. 

CONY, Carlos Heitor. In: Eu aos pedaços:

memórias. São Paulo: Leya, 2010. p. 114-115. 

O enunciador do texto parte de um acontecimento prosaico, comum, ordinário, que o faz refletir. Assinale a opção que expressa o acontecimento que o leva a essa reflexão.

   

   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 “In the fall, Columbia will offer new master’s and certificate programs heavy on data.” and “Data scientists are the magicians of the Big Data era.” contain, respectively, at least one

   

   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 the sentences “…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 “This is a generation of kids that grew up with data science around them.”, one finds adjective clauses that are respectively

   

   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 “Many use data sets provided by businesses or government, and pass back their results.” and “Because data science is so new, universities are scrambling to define it…” contain, respectively, a

   

   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