- C. Petronio, "Geometria e Algebra Lineare," Esculapio.
- E. Schlesinger, Algebra lineare e geometria, Zanichelli, 2011.
- L. Mari, E. Schlesinger, Esercizi di algebra lineare e geometria, Zanichelli, 2013.
- G. Anichini, G. Conti, "Geometria analitica e algebra lineare", Ed. Pearson.
- G. Anichini, G. Conti, R. Paoletti, "Algebra lineare e geometria analitica - Eserciziario", Ed. Pearson.
(For references in other languages other than Italian, contact the lecturer.)
- Notes by the teacher.
- C. Petronio, "Geometria e Algebra Lineare," Esculapio.
- G. Anichini, G. Conti, R. Paoletti, "Algebra lineare e geometria analitica - Eserciziario", Ed. Pearson.
- B. Martelli, "Geometria e algebra lineare", http://people.dm.unipi.it/martelli/alg_lin.html
- M. Manetti, "Algebra lineare, per Matematici", http://www1.mat.uniroma1.it/people/manetti/dispense/algebralineare.pdf.
Further references:
- G. Anichini, G. Conti, R. Paoletti, "Geometria analitica e algebra lineare", Ed. Pearson.
- E. Schlesinger, Algebra lineare e geometria, Zanichelli.
- E. Abbena, A. M. Fino, G. M. Gianella, Algebra lineare e geometria analitica. Volume I, Aracne.
- E. Abbena, A. M. Fino, G. M. Gianella, Algebra lineare e geometria analitica. Volume II, Aracne.
- L. Mari, E. Schlesinger, Esercizi di algebra lineare e geometria, Zanichelli.
- M. Abate, C. De Fabritiis, "
Geometria analitica con elementi di algebra lineare", McGraw-Hill.
- A. Bernardi, A. Gimigliano, Algebra lineare e geometria analitica, Città Studi.
- G. Catino, S. Mongodi, Esercizi svolti di Geometria e Algebra Lineare, Esculapio.
Learning Objectives - Last names A-D
Students are expected to manage the basic tools in analytic geometry (geometric interpretation of systems of equations) and linear algebra (analytic solution of systems of equations; notions of linearity and eigenvectors). They are expected to use the language of linear algebra to descrive linear phenomena in analytic geometry.
Knowledge and understanding of both mathematical principles and the role of mathematical sciences as a tool for the analysis and the problem solving of mechanical engineering problems. Knowledge of the principles of computer science and the algorithmic and numerical approach to problems.
Applying knowledge and understanding related to mathematical methods - with particular reference to differential and integral calculation, geometry, linear algebra, numerical calculation, linear programming and probability and statistical calculation - to model, analyze and solve engineering problems, also with the help of IT tools.
Learning Objectives - Last names E-N
Students are expected to manage the basic tools in analytic geometry (geometric interpretation of systems of equations) and linear algebra (analytic solution of systems of equations; notions of linearity and eigenvectors). They are expected to use the language of linear algebra to descrive linear phenomena in analytic geometry.
Knowledge and understanding of both mathematical principles and the role of mathematical sciences as a tool for the analysis and the problem solving of mechanical engineering problems. Knowledge of the principles of computer science and the algorithmic and numerical approach to problems.
Applying knowledge and understanding related to mathematical methods - with particular reference to differential and integral calculation, geometry, linear algebra, numerical calculation, linear programming and probability and statistical calculation - to model, analyze and solve engineering problems, also with the help of IT tools.
Learning Objectives - Last names O-Z
Students are expected to manage the basic tools in analytic geometry (geometric interpretation of systems of equations) and linear algebra (analytic solution of systems of equations; notions of linearity and eigenvectors). They are expected to use the language of linear algebra to descrive linear phenomena in analytic geometry.
Knowledge and understanding of both mathematical principles and the role of mathematical sciences as a tool for the analysis and the problem solving of mechanical engineering problems. Knowledge of the principles of computer science and the algorithmic and numerical approach to problems.
Applying knowledge and understanding related to mathematical methods - with particular reference to differential and integral calculation, geometry, linear algebra, numerical calculation, linear programming and probability and statistical calculation - to model, analyze and solve engineering problems, also with the help of IT tools.
Prerequisites - Last names A-D
Basic mathematics
Prerequisites - Last names E-N
Basic mathematics
Prerequisites - Last names O-Z
Basic mathematics.
Teaching Methods - Last names A-D
Lessons and exercise classes.
Teaching Methods - Last names E-N
Lessons and exercise classes and/or in streaming, depending on the timeschedule.
Due to the actual situaztion, each lesson will be referred to the text books.
Teaching Methods - Last names O-Z
Lessons and exercise classes and online synchronous classes.
Further information - Last names A-D
For further information, feel free to contact the lecturer.
Further information - Last names E-N
For further information, feel free to contact the lecturer.
Further information - Last names O-Z
For further information, feel free to contact the lecturer.
Type of Assessment - Last names A-D
Written exam, and optional oral exam. Intermediate exams. Each written exam consists of 11 multiple-choice questions.
Type of Assessment - Last names E-N
If the situation will allow it, there will be a written test in presence and an optional oral exam. Each written exam consists of 11 multiple-choice questions.
Each written exam consists of 11 multiple-choice questions on the whole program.
If the examination will be online, there will be a multichoice test released on Moodle platform AND an oral exam (compulsory).
Type of Assessment - Last names O-Z
It possible according to the health emergency: written exam, and optional oral exam. Exams taken by distance require an oral exam. Each written exam consists of 11 multiple-choice questions.
Course program - Last names A-D
0 - Introduction and preliminaries. Complex numbers.
1 - Vector spaces: Vectors, operations on vectors. Generated subspaces, linear dependence, basis, dimension. Numerical vector spaces. Scalar product, vector product, triple product.
2 - Linear systems: Matrices. Operations on matrices and properties, special matrices. Determinant, rank. Linear systems of equations. Solutions of linear systems. Gauss Elimination Method.
3 - Linear analytic geometry: Parametric and Cartesian equations for subspaces. Lines, planes. Parallelism and perpendicularity.
4 - Linear metric geometry: Scalar products. Distance, angle, area, volume. Ortoghonal projection.
5 - Linear maps: Linear transformations. Kernel and image. Matrices associated to linear maps. Change of basis. Eigenvectors and eigenvalues. Diagonalization. Diagonalization of symmetric matrices and spectral theorem. Conics and quadrics.
Course program - Last names E-N
0 - Introduction and preliminaries. Complex numbers.
1 - Vector spaces: Vectors, operations on vectors. Generated subspaces, linear dependence, basis, dimension. Numerical vector spaces. Scalar product, vector product, triple product.
2 - Linear systems: Matrices. Operations on matrices and properties, special matrices. Determinant, rank. Linear systems of equations. Solutions of linear systems. Gauss Elimination Method.
3 - Linear analytic geometry: Parametric and Cartesian equations for subspaces. Lines, planes. Parallelism and perpendicularity.
4 - Linear metric geometry: Scalar products. Distance, angle, area, volume. Ortoghonal projection.
5 - Linear maps: Linear transformations. Kernel and image. Matrices associated to linear maps. Change of basis. Eigenvectors and eigenvalues. Diagonalization. Diagonalization of symmetric matrices and spectral theorem.
Course program - Last names O-Z
0 - Introduction and preliminaries. Complex numbers.
1 - Vector spaces: Vectors, operations on vectors. Generated subspaces, linear dependence, basis, dimension. Numerical vector spaces. Scalar product, vector product, triple product.
2 - Linear systems: Matrices. Operations on matrices and properties, special matrices. Determinant, rank. Linear systems of equations. Solutions of linear systems. Gauss Elimination Method.
3 - Linear analytic geometry: Parametric and Cartesian equations for subspaces. Lines, planes. Parallelism and perpendicularity.
4 - Linear metric geometry: Scalar products. Distance, angle, area, volume. Ortoghonal projection.
5 - Linear maps: Linear transformations. Kernel and image. Matrices associated to linear maps. Change of basis. Eigenvectors and eigenvalues. Diagonalization. Diagonalization of symmetric matrices and spectral theorem. Conics and quadrics.