Learning purposes : To learn the computional methods, and conduct such methods and simulation of data to solve various actual problems by using computer. To learn computional methods, and use such methods and simulation of data to solve actual problem. To learn the cases of utility of data science, and the basis skills of statistics.
Course Objectives :
1. To comprehend the basis of simulation of data.
2. To understand the basis of computional methods.
3. To understand the basis of C programming language.
4. To know the problems in massively parallel computing.
Outline:
General or Specialized : Specialized
Field of learning : Information science, Information Engineering and conern subjects, computational science.
Relationship with Educational Objectives :This class is equivalent to "(2) Acquire basic science and technical knowledge".
Course outline :
In this lecture, students learn the basis of simulation and computational methods, and how to apply them on computer to sovle actual problems. In detail, students learn and understand 1) the application of C programming language, 2) basic computitional methods, and 3) solution of typical problems based on such methods. In additional, students learn the manipulation of data, the basis of statistic through actual cases. Artificial Intelligence is also concerned in class.
Style:
Course method :
Classes are conducted in the way of representation and students' exercises. Class focus on giving the image of solution of problem using information devices. In every lesson, representation will be given by professor in the first half(45 minutes), and students will do exercises in the second half (45 minutes). Every time a report will be given as portfolio to students to confirm their understanding.
Grade evaluation method :
Exams (50%) + reports submission (30%) + effort in exercises(20%).
Examinations will be conducted a total of 4 times, and the evaluation ratios will be the same. The students who cannot reach 60 points in every examination, can attend additional examination. If he/she passed, his/her evaluation may be changed not more than 60 points.
Notice:
Precautions on the enrollment :Students must take this class (no more than one-third of the required number of class hours missed) and earn the credit in order to complete the 3rd year course.
Course advice :
1: Prepare the content of next lecture. On the other hand, review the content after every lecture.
2: Ensure that every report is submitted.
Foundational subjects : Foundation of Integrated science and engineering, Information literacy, Calculus I and II, Foundation of mathematic, Foundation of linear algebra
Subjects concerned: All specialized subjects since grade three.
Attendance advice :
1: Computer, network, and information techniques have miracle improvement during recent years. Reading of material that related with computer and network is recommended.
2: Preparation of the content of foundational subjects.
3: Prepare and review the content of every lecture, to improve comprehension.
4: 2 times of late for class will be counted as 1 absence.
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Theme |
Goals |
| 1st Semester |
| 1st Quarter |
| 1st |
Guidance.Introduction of content of this lecture, learning method, and usage of computers. |
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| 2nd |
Review: the basis of C language programming (part 1). |
Understand and complete C programs that include variables, conditional expression.
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| 3rd |
Review: the basis of C language programming (part 2). |
Understand and complete C programs that include array, iteration.
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| 4th |
Review: the basis of C language programming (part 3). |
Understand and complete C programs that include micro, function.
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| 5th |
Equation: Dichotomy and exercise. |
Undertand the principle of Dichotomy, make and run the program of Dichotomy.
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| 6th |
Equation: Newton's method and exercise. |
Undertand the principle of Newton's method, make and run the program of Newton's method.
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| 7th |
Simultaneous linear equations: matrix and Upper triangular simultaneous linear equations, exercise. |
Undertand the principle of Simultaneous linear equations.
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| 8th |
Mid-term examination. |
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| 2nd Quarter |
| 9th |
Explanation of mid-term examination. |
Unerstand the problems of mid-term examination.
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| 10th |
Simultaneous linear equations:Gaussian elimination and exercise. |
Undertand the principle of Gaussian elimination, make and run the program of Gaussian elimination.
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| 11th |
Simultaneous linear equations:Gauss-Jordan method and exercise. |
Undertand the principle of Gauss-Jordan method, make and run the program of Gauss-Jordan method.
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| 12th |
Polynomial method: Lagrange polynomial method and exercise. |
Understand the basis of Lagrange polynomial method, make and run the program of Lagrange polynomial method.
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| 13th |
Polynomial method: Newton polynomial formula and exercise. |
Understand the basis of Newton polynomial formula, make and run the program of Newton polynomial formula.
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| 14th |
Curve fitting: Spline function and exercise. |
Understand the basis of Spline function, make and run the program of Spline function.
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| 15th |
1st semester final exam |
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| 16th |
Return and commentary of exam answers |
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| 2nd Semester |
| 3rd Quarter |
| 1st |
Exercise: C program of Spline function. |
Review of the basis of Spline function, complete the C program of Spline function.
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| 2nd |
Curve fitting: Minimization of squares and exercise. |
Understand the basis of Minimization of squares, make and run the program of Minimization of squares.
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| 3rd |
Exercise: C program of minimization of squares |
Review of the basis of Spline function, complete the C program of minimization of squares.
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| 4th |
Numerical integration: Trapezoidal rule and exercise. |
Understand the basis of Trapezoidal rule, make and run the program of Trapezoidal rule.
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| 5th |
Numerical integration: Simpson's rule and exercise. |
Understand the basis of Simpson's rule, make and run the program of Simpson's rule.
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| 6th |
Differential equation: Runge–Kutta method and exercise(1). |
Understand the basis of Runge–Kutta method, make and run the program of Runge–Kutta method.
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| 7th |
Differential equation: Runge–Kutta method and exercise(2). |
Understand the basis of Runge–Kutta method, make and run the program of Runge–Kutta method.
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| 8th |
2nd semester mid-term exam |
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| 4th Quarter |
| 9th |
Return and commentary of exam answers |
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| 10th |
Basis of statistic (Manipulation of data with Excel), creation of graphs and tables with Excel. |
Understand the basis of statistic, and can create graphs and tables with Excel.
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| 11th |
Basis of statistic (average, variance, standard deviation) |
Understand and calculate average, variance, standard deviation for given data in Excel.
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| 12th |
Basis of statistic (correlation coefficients) |
Understand and calculate correlation coefficients for given data in Excel.
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| 13th |
Basis of statistic (matrix of correlation coefficients) and case study |
Understand and calculate correlation coefficients for given data in Excel. Understand the case of utility of data science skills.
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| 14th |
Review of content, exercise. |
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| 15th |
2nd semester final exam |
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| 16th |
Return and commentary of exam answers |
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