Saiba como desenvolver, dominar e entregar os melhores projetos de mercado aos clientes. A melhor plataforma para aprender tecnologia no Brasil agora faz parte da maior escola de idiomas da América Latina. O programa conta com mentorias exclusivas – ao vivo – de hard skills (mentorias técnicas) e soft skills, elevando seu conhecimento na área. O Machine learning é uma ferramenta poderosa e grande aliada na Ciência de Dados, oferecendo diversas formas de utilizá-la para uma melhor análise, desenvolvimento e aperfeiçoamento para soluções mais eficazes. Adquira competências avançadas em Data, domine o conceito de Machine Learning e IA e inicie a sua carreira como cientista de dados, analista de dados, engenheiro de IA, gestor de dados e muito mais.
- Aqueles que completam o programa podem esperar um conhecimento aprofundado das modernas ferramentas de dados, acesso a uma extensa rede de profissionais da indústria e suporte contínuo de carreira.
- Você aprenderá a criar programas funcionais para realizar operações diversas, incluindo decisões, seleções, repetições e iterações, capacitando-o a desenvolver soluções para problemas do mundo real.
- O Machine learning é uma ferramenta poderosa e grande aliada na Ciência de Dados, oferecendo diversas formas de utilizá-la para uma melhor análise, desenvolvimento e aperfeiçoamento para soluções mais eficazes.
- As aulas acomodam apenas oito pessoas, de modo que a aceitação é seletiva, e só está aberta aos alunos que já residem ou podem arcar com suas próprias acomodações na área da cidade de Nova York.
Através do bootcamp, você terá acesso à uma imersão na tecnologia e ainda poderá complementar seus estudos com cursos, desafios e mentorias na DIO. Concorrência no mercado de trabalho À medida que a popularidade da ciência de dados cresce, também cresce a concorrência para cargos de ciência de dados. A melhor forma de se distinguir é criar um portefólio sólido de projectos que demonstrem as suas capacidades em ciência de dados. O conteúdo do bootcamp é ministrado por especialistas da área de Ciência de Dados e inclui aulas teóricas e práticas, além de desafios e atividades que permitem aos participantes aplicarem os conhecimentos adquiridos.
Benefícios dos Bootcamps de Ciência de Dados
Você também vai aprender estratégias para expandir sua rede de contatos profissionais. Para garantir uma rede de contatos eficiente, ao longo do Bootcamp Data Science você vai trabalhar e desenvolver habilidades de comunicação não violenta para o ambiente online e convívio em grupo. A partir https://www.vznetwork.net/php-world-wide-web-improvement-helpful-for-on-line-enterprise/ do domínio da arte de se expressar de forma clara, empática e respeitosa, você garantirá relações saudáveis tanto nas redes sociais quanto no trabalho. Durante o Bootcamp Data Science e IA, também serão trabalhadas as soft skills – habilidades não técnicas essenciais para o seu sucesso.
Envolve uma mistura de matemática, estatística, ciências informáticas, conhecimento do domínio e engenharia de dados. Os cientistas de dados recolhem, limpam e pré-processam dados, efectuam análises estatísticas e aprendizagem automática para descobrir padrões e tendências e, em seguida, comunicam as suas conclusões às partes interessadas. A Thinkful oferece um bootcamp online auto programado com um currículo baseado em projetos, uma preparação profissional e uma orientação individual com acesso a uma comunidade cheia de estudantes, mentores e ex-alunos. O curso exige cerca de 20 a 30 horas por semana de trabalho e a maioria dos alunos se formou em cerca de seis meses. Um programa que irá impulsionar sua entrada no mercado tecnológico com cursos, mentorias, desafios de código e desafios de projeto, promovendo o conhecimento ideal para seu desenvolvimento na área de tecnologia, neste caso, em Python, R, AWS e MySQL. À medida que a procura de cientistas de dados continua a aumentar em vários sectores, um bootcamp de ciência de dados pode ser o seu bilhete para uma carreira gratificante e a pedido.
Cobol é um desafio para jovens profissionais de…
O bootcamp de ciência de dados da Code Labs Academy destaca-se por proporcionar uma formação abrangente que cobre todos os aspectos essenciais da área. Para além de um currículo completo, damos especial ênfase à aprendizagem automática, oferecendo uma exploração mais extensa e aprofundada desta componente crucial em comparação com muitos outros bootcamps. Isto garante que os nossos alunos não só recebem uma compreensão alargada da ciência dos dados, como também ganham uma vantagem competitiva https://rockdeverdade.com.br/author/iliner55v/ na aprendizagem automática, uma competência muito procurada em vários sectores. Os Bootcamps de transição de carreira são ideais para quem pretende entrar no domínio da ciência dos dados, uma vez que proporcionam um percurso estruturado para uma nova carreira. Atualmente o ecossistema da startup conta com mais de 1 milhão profissionais de tecnologia, 1.000 instituições de ensino, 2.000 embaixadores, 500 experts e mais de 1.000 empresas conectadas por meio dos programas educacionais.
As empresas que não criarem uma cultura data-driven e incluírem a Ciência de Dados em suas estratégias corporativas se tornarão irrelevantes. Gestores atentos estão criando e desenvolvendo suas equipes de Data Science. É um caminho sem volta, pois o volume de dados não vai parar de crescer e quem souber extrair valor dos dados estará a frente dos concorrentes. O Instituto Infnet foi fundado em 1994, para o ensino de excelência voltado às necessidades do mercado.
Aprenda
A presença mínima obrigatória nas aulas ao vivo é de 75% em cada disciplina. A participação do aluno com câmera aberta é obrigatória para fins de chamada. Especialista em análise e visualização de dados, é responsável por fornecer insights valiosos para a solução de problemas específicos em apoio à tomada de decisões de um negócio. Também irá aprender a cultivar hábitos poderosos que impulsionarão a sua produtividade, assim como aperfeiçoar a gestão https://crabtree-reed.technetbloggers.de/virtually-everybody-wishes-that-they-had-much-more-time-to-do-the-things-that-they-will-need-to-do-it-appears-like-there-is-in-no-way-adequate-time-to-get-every-thing-accomplished-in-th do seu tempo, desenvolvendo habilidades de organização e priorização que garantirão que você cumpra prazos com eficiência. Aperfeiçoe suas habilidades técnicas e torne-se um profissional ainda mais valorizado no mercado, capaz de lidar com a automação de processos a partir do uso de dados. Você terá uma verdadeira experiência de sala de aula, participando por áudio e vídeo, tirando dúvidas com os professores e construindo seu networking.
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)
Esse formato oferece flexibilidade para os estudantes participarem de qualquer lugar com acesso à internet, permitindo uma experiência de aprendizado dinâmica e envolvente. Você aprenderá a criar programas funcionais para realizar operações diversas, incluindo decisões, seleções, repetições e iterações, capacitando-o a desenvolver soluções para problemas do mundo real. Com campus em Seattle, Silicon Valley, Barcelona, Toronto, Washington e Paris, o Data Dojo Science oferece educação rápida e acessível para profissionais de todo o mundo. O Data Incubator é um programa de oito semanas destinado a profissionais de tecnologia mais experientes com mestrado ou doutorado. Os bolsistas qualificados “já possuem 90% de habilidades difíceis de aprender” e a Incubadora de Dados promete capacitá-los “com os últimos 10%”.