• Computing and Applied Mathematics
  • 6640
  • 1515.00
    • [[inner]]
  • 12
  • - Theoretical, methodological and practical foundations in the areas of computer science, applied mathematics and computer engineering. In particular: Mathematics, Statistics, Machine Learning, Artificial Intelligence and Computer Engineering. - Know how to handle large volumes of data within data protection laws, create and implement new and current algorithms and mathematical models in A.I. - Obtain scientific quality results with fluidity; know how to integrate and work in multidisciplinary teams; good synthesis skills.
  • 180
  • Lurdes Oliveira
  • f3560@ulusofona.pt
  • 2
  • 1º Ciclo
  • DCETI - Department of Business Sciences and Information Technologies
  • N
  • This cycle provides: An introduction to computing and applied mathematics in response to current needs in a big-data context, with basic technical training in computer science, applied mathematics and computer engineering essential for handling data, algorithms and models.
  • With the exponential advance in the volume of ¿big data¿ and its digital transformation over the last decade and a half, we have witnessed and continue to observe a phase of constant reinvention not only of the infrastructures and models of information systems, but also the reinvention of new professional profiles in the transformation of data into knowledge. It can be seen that professionals trained in areas related to traditional ¿mathematics¿ have shown a very strong basis for facing this challenge. However, there is a great effort on the part of these professionals to adapt to IT infrastructures. The aim is to maintain the analytical thinking of these professionals but also to develop skills in computer engineering.
  • Information Systems and Computer Science
  • 11
  • 282450430
  • 1757
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    Passing one of the following sets of entrance exams:<\/p>\r\n\r\n16 Maths\r\n04 Economics\r\nor\r\n16 Maths\r\n07 Physics and Chemistry \r\nor\r\n16 Maths\r\n18 Portuguese\r\n\r\nor\r\n02 Biology and Geology\r\n16 Maths\r\nor\r\n13 English\r\n16 Maths\r\nor \r\n09 Geography\r\n16 Maths\r\n

    Candidates can also enter through the change of institution\/course pair schemes, or through a Special Competition, in accordance with the legal rules in force (holders of higher education courses, holders of CETs, holders of CTSPs, over 23s, holders of dual certification courses). Candidates who fulfil the conditions laid down in the International Student Statute may also enter.","careerOportunities":"- Data Scientist\r\n- Applied Mathematician\/Computer Scientist\r\n- Business Intelligence\r\n- Analyst\r\n- Machine Learning & A.I. Scientist\r\n- Solid background to pursue a Ph.D. program.","competences":"- Theoretical, methodological and practical foundations in the areas of computer science, applied mathematics and computer engineering. In particular: Mathematics, Statistics, Machine Learning, Artificial Intelligence and Computer Engineering.\r\n- Know how to handle large volumes of data within data protection laws, create and implement new and current algorithms and mathematical models in A.I.\r\n- Obtain scientific quality results with fluidity; know how to integrate and work in multidisciplinary teams; good synthesis skills.","conferedDegree":"Bachelor","creditationStatus":"Acreditado","creditationStatusCode":1,"directionContact":"Tiago Candeias","courseECTS":180,"courseName":"Computing and Applied Mathematics ","dsGrauCursoLongo":"Licenciatura in Computing and Applied Mathematics","courseSecretariatContact":"Lurdes Oliveira ","courseSecretariatEmail":"f3560@ulusofona.pt","curricularPlanCode":2,"degree":"1\u00ba Ciclo","departement":"DCETI - Department of Business Sciences and Information Technologies","hasBranches":"N","objectives":"This cycle provides: An introduction to computing and applied mathematics in response to current needs in a big-data context, with basic technical training in computer science, applied mathematics and computer engineering essential for handling data, algorithms and models.","presentation":"With the exponential advance in the volume of \u00bfbig data\u00bf and its digital transformation over the last decade and a half, we have witnessed and continue to observe a phase of constant reinvention not only of the infrastructures and models of information systems, but also the reinvention of new professional profiles in the transformation of data into knowledge.\r\nIt can be seen that professionals trained in areas related to traditional \u00bfmathematics\u00bf have shown a very strong basis for facing this challenge. 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  • EN
  • https://si.a3es.pt/sia3es/page?stage=ConsultaPublicaProcesso&processID=25685
  • Passing one of the following sets of entrance exams:

    16 Maths 04 Economics or 16 Maths 07 Physics and Chemistry or 16 Maths 18 Portuguese or 02 Biology and Geology 16 Maths or 13 English 16 Maths or 09 Geography 16 Maths

    Candidates can also enter through the change of institution/course pair schemes, or through a Special Competition, in accordance with the legal rules in force (holders of higher education courses, holders of CETs, holders of CTSPs, over 23s, holders of dual certification courses). Candidates who fulfil the conditions laid down in the International Student Statute may also enter.

  • - Data Scientist - Applied Mathematician/Computer Scientist - Business Intelligence - Analyst - Machine Learning & A.I. Scientist - Solid background to pursue a Ph.D. program.
  • Bachelor
  • Acreditado
  • 1
  • Tiago Candeias
  • Presencial
  • Ciências informáticas
  • 481
  • 71
  • 07/07/2022
  • R/A -Cr 150/2022/AL01 de 8 de junho de 2023
  • Assessment methodology The program offers a strong technical introduction to the student in the areas mentioned, through methodologies: (1) Expository, (2) Experimental, (3) Active, promotes teamwork and (4) Self-Study.
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  • {"errorCode":"0"}
    • Solid, Multidisciplinary Training: Combines computing, applied maths and computer engineering, developing the analytical and practical skills essential for dealing with big data, algorithms and artificial intelligence.
    • Focus on Emerging Areas and Innovative Technologies: Addresses topics such as machine learning, A.I., advanced statistics and data analysis, preparing students to face the technological challenges of the future.
    • Experienced Teaching Staff and Personalised Guidance: Specialised teachers with extensive academic and practical experience guarantee up-to-date teaching and continuous support in the development of projects.
    • Integration of Theory and Practice: Training with a strong practical component, including real projects and teamwork, to apply knowledge to solving real-world problems.
    • Broad Labour Market Insertion: Prepares for careers in high-demand areas such as data science, business analysis, machine learning, business intelligence and technology consulting.
    • Internship and career opportunities: Partnerships with companies and organisations allow you to apply your knowledge in real environments, create a network of contacts and enter the job market.
  • 6
  • https://secure.ensinolusofona.pt/lsm/LusofonaMobileWebService_2_0/UserThumb?user_login=p4492
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