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Programming for Data Science Programming Lab - Scheduling Analytics - Programmatically Creating and Optimizing an Airline Schedule
Scenario -
A new startup airline is needing help with creating and optimizing a flight schedule. They have hired you as a data scientist to create and optimize a flight schedule. The airlines will be all business class and cater to business travel. All aircraft are configured exactly the same and can fly any route in the system interchangeably. The airline will serve Dallas Love Field (DAL), Austin Bergstrom (AUS), and Houston Hobby (HOU).
Individual Assignment -
This assignment in an individual assignment. You may consult with other student about general approaches to solving the problem and for asking for help to resolve stack traces, but all coding must be your own work. An electronic comparison for similarities in submissions will be made. Any similarities greater than 70% will be investigated by the instructor, with possible referrals for academic dishonesty.
Python Program -
You will write a single file Python program in Jupyter Notebook format named create_flight_schedule.ipynb to accomplish them. The input data from the charts above may be hard coded into Python data structures. No input files will be required. The program must run successfully and create an output file flight_schedule.csv.
Attachment:- Assignment File.rar
The instructor will award a grade of pass if 65% of the objectives of the assignment have been met. A grade of fail will be given for any one of the following conditions: In the instructor’s sole opinion less than 65% of the objectives of the assignment have not been met. In the instructor’s sole opinion, the solution is not algorithmic in nature (no hard coding!). The assignment is submitted late (1 second late is late). The student emails the instructor the assignment instead of or in addition to submitting it in eLearning. Required files are not submitted with the correct names (case sensitive). Not observing the documentation string and comments ratio detailed previously. Submitting any additional materials other than the explicitly mentioned submission files. If there is a 70% similarity or greater between any part of the submission and another student’s submission from any section in any semester.
The submission time of this assignment may be used in tie breaking for rank grading as detailed in the syllabus. The sooner you submit the assignment, the greater the probability of a higher grade ranking. Late Penalty - No late submissions will be accepted. A grade of fail will be given. Students are strongly recommended to target a completion date 2 or 3 days prior to the deadline. Students may resubmit the assignment prior to the due date and time. Only the last submission will be graded. Prior submissions will not be graded. The last submission time will be counted toward rank grading.
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