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JOHN CABOT UNIVERSITY
COURSE CODE: "CS 160-2"
COURSE NAME: "Programming Concepts and Applications"
SEMESTER & YEAR:
Spring 2019
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SYLLABUS
INSTRUCTOR:
Walter Arrighetti
EMAIL: [email protected]
HOURS:
TTH 6:00-7:15 PM
TOTAL NO. OF CONTACT HOURS:
45
CREDITS:
3
PREREQUISITES:
OFFICE HOURS:
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COURSE DESCRIPTION:
This course introduces fundamental computer programming concepts using a high-level language and a modern development environment. Programming skills include sequential, selection, and repetition control structures, functions, input and output, primitive data types, basic data structures including arrays and pointers, objects, and classes. Software engineering skills include problem solving, program design, and debugging practices. The goal of this course is to advance students’ computational thinking, educate them to use programs as tools in their own field of study, and to provide them with fundamental knowledge of programming strategies.
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SUMMARY OF COURSE CONTENT:
This course will introduce students to basic fundamental code development concepts. Students will use logics and problem solving skills to write programming code for various tasks.
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LEARNING OUTCOMES:
1. Learn the fundamentals of programming using various data types, expressions, operations, selections, looping constructs and functions.
2. Use Object-Oriented Programming - abstraction, encapsulation, inheritance, modularity and reusability in software development.
3. Deliver interoprable, high- and low-level code that runs on multiple Operating Systems (Windows, macOS, Linux, Android).
4. Fundamentals of data analytics and big data.
5. Fundamentals of GUI (graphical user interface) development.
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TEXTBOOK:
Book Title | Author | Publisher | ISBN number | Library Call Number | Comments | Format | Local Bookstore | Online Purchase |
Python for Data Analysis, 2nd Edition | Wes McKinney | O'Reilly | 978-1491957660 | | Data wrangling with Pandas, NumPy, and IPython | | | |
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REQUIRED RESERVED READING:
Book Title | Author | Publisher | ISBN number | Library Call Number | Comments |
Python Pocket Reference | Mark Lutx | O'Reilly | 978-1449319793 | | |
Python Data Analytics | Fabio Nelli | Apress | 978-1484209592 | | data analysis and science using Pandas, matplotlib and the Python programming language |
RECOMMENDED RESERVED READING:
Book Title | Author | Publisher | ISBN number | Library Call Number | Comments |
Learning Python | Mark Lutz | O'Reilly | 978-1449355739 | | |
Data Science at the command line | Jeroen Janssens | O'Reilly | 978-1491947852 | | Facing the future with time-tested tools |
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GRADING POLICY
-ASSESSMENT METHODS:
Assignment | Guidelines | Weight |
Assignments | | 25 |
Active attendance | | 25 |
Midterm Exam | | 20 |
Final Exam | | 30 |
-ASSESSMENT CRITERIA:
AWork of this quality directly addresses the question or problem raised and provides a coherent argument displaying an extensive knowledge of relevant information or content. This type of work demonstrates the ability to critically evaluate concepts and theory and has an element of novelty and originality. There is clear evidence of a significant amount of reading beyond that required for the course. BThis is highly competent level of performance and directly addresses the question or problem raised.There is a demonstration of some ability to critically evaluatetheory and concepts and relate them to practice. Discussions reflect the student’s own arguments and are not simply a repetition of standard lecture andreference material. The work does not suffer from any major errors or omissions and provides evidence of reading beyond the required assignments. CThis is an acceptable level of performance and provides answers that are clear but limited, reflecting the information offered in the lectures and reference readings. DThis level of performances demonstrates that the student lacks a coherent grasp of the material.Important information is omitted and irrelevant points included.In effect, the student has barely done enough to persuade the instructor that s/he should not fail. FThis work fails to show any knowledge or understanding of the issues raised in the question. Most of the material in the answer is irrelevant.
-ATTENDANCE REQUIREMENTS:
ATTENDANCE REQUIREMENTS AND EXAMINATION POLICY
You cannot make-up a major exam (midterm or final) without the permission of the Dean’s Office. The Dean’s Office will grant such permission only when the absence was caused by a serious impediment, such as a documented illness, hospitalization or death in the immediate family (in which you must attend the funeral) or other situations of similar gravity. Absences due to other meaningful conflicts, such as job interviews, family celebrations, travel difficulties, student misunderstandings or personal convenience, will not be excused. Students who will be absent from a major exam must notify the Dean’s Office prior to that exam. Absences from class due to the observance of a religious holiday will normally be excused. Individual students who will have to miss class to observe a religious holiday should notify the instructor by the end of the Add/Drop period to make prior arrangements for making up any work that will be missed. The final exam period runs until ____________
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ACADEMIC HONESTY
As stated in the university catalog, any student who commits an act of academic
dishonesty will receive a failing grade on the work in which the dishonesty occurred.
In addition, acts of academic dishonesty, irrespective of the weight of the assignment,
may result in the student receiving a failing grade in the course. Instances of
academic dishonesty will be reported to the Dean of Academic Affairs. A student
who is reported twice for academic dishonesty is subject to summary dismissal from
the University. In such a case, the Academic Council will then make a recommendation
to the President, who will make the final decision.
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STUDENTS WITH LEARNING OR OTHER DISABILITIES
John Cabot University does not discriminate on the basis of disability or handicap.
Students with approved accommodations must inform their professors at the beginning
of the term. Please see the website for the complete policy.
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SCHEDULE
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Session | Session Focus | Reading Assignment | Other Assignment | Meeting Place/Exam Dates |
Weeks 1‒2 | Introduction to Computer Science | | | |
Weeks 3‒4 | Introduction to Python and other programming languages | | | |
Weeks 5‒6 | Basic data types, operations and functions | | | |
Weeks 7‒8 | More data types: arrays, strings, lists, sets, dictionaries | | | |
Weeks 9‒10 | Classes and object-oriented constructs | | | |
Week 11 | Operating Systems' interoperability | | | |
Week 12 | Regular expressions | | | |
Week 13 | Data analytics | | | |
Weeks 14‒15 | Graphical User Interfaces ‒ GUIs | | | |
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