. "Data Science, Data Analysis, Data Mining"@en . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . "Data analysis and statistical modelling"@en . . "6.0" . "Prerequisites\nProbability and Statistics.\n\nObjectives\n- Introduction to Applied Statistics and its relevance in Data Science. - Analyze real data using statistical methods to extract relevant information about them and solve practical problems using statistical software. - Know the advantages and limitations of various statistical methodologies to make out the most of them in solving real problems. - Find statistical evidence in the data based on models adjusted to the observations collected. Infer about hypotheses of interest associated with the selected models. - Solve a real problem using the knowledge accumulated in this course: computational project.\n\nProgram\n1. Exploratory data analysis: (i) Introduction to R. (ii) Visualization of different types of data. (iii) Treatment of missing values. (iv) Outlier detection. 2. Dimensionality reduction: principal component analysis. Covariance and correlation matrices. 3. Regression models: Gaussian, Logistic, Poisson. Variable Selection. Diagnostic Techniques. Model validation. Prediction. 4. Modeling independent data versus time dependent data. 5. Resampling methods: Jackknife, bootstrap, permutation testing and cross-validation. 6. Elements of the Bayesian methodology: a priori representation (conjugate and non-informative distributions), inference by the Bayes theorem and applications to real data problems. 7. Classification: Total probability of misclassification, Fisher linear discriminant analysis, Bayes classification rule. Evaluation of the performance of a classification rule.\n\nEvaluation Methodology\nA Test of 1h30m (50%), with a minimum grade of 8.0, and a Computational Project (50%)\n\nCross-Competence Component\nCritical and Innovative Thinking - Project realization involves components of strategic thinking, critical thinking, creativity, and problem-solving strategies without explicit evaluation. Intrapersonal Competencies - Project realization involves components of productivity and time management, stress management, proactivity and initiative, intrinsic motivation and decision making without explicit evaluation. Interpersonal Skills - In assessing the project report, 10% of the rating is given to the form of the reports and 10% of the rating is given to the oral presentation and discussion of the project.\b\n\nLaboratorial Component\nLaboratory work performed with the help of R (or equivalent).\n\nProgramming and Computing Component\nThe laboratory and project work involve R programming. The evaluation percentage in this component is 50%.\n\nMore information at: https://fenix.tecnico.ulisboa.pt/cursos/lerc/disciplina-curricular/845953938490004" . . "Presential"@en . "TRUE" . . "Bachelor in Telecommunications and Informatics Engineering"@en . . "https://tecnico.ulisboa.pt/en/education/courses/undergraduate-programmes/telecommunications-and-informatics-engineering/ " . "180"^^ . "Presential"@en . "Programme Overview\nTelecommunications and Informatics Engineering is dedicated to “Internet Engineering”, namely the so-called “internet of things”, which allows us to interact with various objects, such as refrigerators, heating our homes or products for sale in a supermarket. As such, a Telecommunications and Informatics Engineer works with complex, fixed or mobile communication networks and related infrastructures. It also develops services or applications, knowing the related security aspects.\n\nEntry Requirements - National Admission to Higher education\n\n* National Admission Exams: Mathematics A + Physics and Chemistry (Minimum grade point: 100 points (out of 200))\n* Application Grade: MS x 50% + PI x 50% (Minimum grade point: 120 points (out of 200))\n - MS: high school final arithmetic average grade | PI: Average of national admission exams’ grades.\n\nhttps://tecnico.ulisboa.pt/en/education/study-at-tecnico/applications/national-admission-for-higher-education/ \n\nAdmissions can also be done through one of the following ways:\n\n* Course Change and Transfer\n* Holders of Middle Level/Higher Education degrees\n* Applicants over the age of 23\n* Special Admission Regime for International Students\n\nMore information about admissions to Técnico (national and international candidates) is available at: https://tecnico.ulisboa.pt/en/education/study-at-tecnico/applications/"@en . . . "3"@en . "FALSE" . . . "Bachelor"@en . "Thesis" . "697.00" . "Euro"@en . "7000.00" . "None" . "Fields:\n\n* Telecommunications companies\n* Information technology companies\n* Government agencies\n* Research and development organizations\n* Consulting firms\n* Start-ups\n\nThe average salary for a telecommunications engineer in Portugal is €35,000 per year. The average salary for an informatics engineer in Portugal is €30,000 per year.\n\nSome of the possible positions:\n\n* Telecommunications engineer\n* Network engineer\n* Systems engineer\n* Software engineer\n* Data scientist\n* Cyber security engineer"@en . "1"^^ . "TRUE" . "Midstream"@en . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .