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        Lecturer(s)
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                    Říha Jan, Mgr. Ph.D.
                
 
            
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                    Smrčka David, Mgr. Ph.D.
                
 
            
         
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        Course content
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        Students will learn the basic elements of the program Mathematica and its use in these areas: 1. Overview    - Calculation    - Import, visualization and data processing    - Screening and filtering data    - Construction and analyzation of statistical data    - Dynamical data manipulation. 2. Introduction to Mathematica    - What is Mathematica?    - Getting started    - Basic operations    - Notebooks    - Exercises 3. Programming I    - Assignments and definitions    - Procedural programming    - Functional programming    - Programming with rules    - Comparing programming styles    - Application for data processing    - Exercises 4. Visualization and graphics    - Function visualization    - Data visualization    - Graphics options    - Displaying graphics    - Dynamic and interactive graphics    - Examples    - Exercises 5. Symbolic computation    - Polynomials    - Solving equations    - Calculus    - Simplifications    - Exercises 6. Numerical computation    - Functions for numerical computation    - Working with numbers    - Large arrays    - Exercises 7. Programming II    - Basic principles    - Functional programming    - Options and messages    - Efficiency    - Exercises 8. Working with data    - Importing and exporting    - Data collections    - Examples    - Exercises 9. Applications in natural sciences
         
         
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        Learning activities and teaching methods
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        Dialogic Lecture (Discussion, Dialog, Brainstorming)
        
            
                    
                
                    
                    - Homework for Teaching
                        - 100 hours per semester
                    
 
                
                    
                    - Attendace
                        - 20 hours per semester
                    
 
                
             
        
        
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                Learning outcomes
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                Knowledge of syntaxe of software Mathematica and its aplication for solving problems in the field of natural sciences.
                 
                
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                Prerequisites
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                Basic knowledge of computer skills, basic mathematics.
                
                
                    
                        
                    
                    
                
                
  
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                Assessment methods and criteria
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                        Student performance
                        
                        
                         
                        
                    
                    
                
                 Students will receive colloquium based on their individual work with software Mathematica.
                 
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        Recommended literature
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                - 
                    Haneberg, W. C. (2004). Computational geosciences with Mathematica. Berlin : Springer. 
                
 
            
                
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                    Hassani, S. (2003). Mathematical methods using Mathematica : for students of physics and related fields. Springer. 
                
 
            
                
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                    Martha L. A. - James P. B. (2009). Mathematica by example. Burlington; San Diego; London : Elsevier. 
                
 
            
                
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                    McMahon, D. - Topa, D. (2006). A Beginner's guide to Mathematica. Boca Raton : Chapman and Hall. 
                
 
            
         
         
         
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