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Choose your university right. Overview: In this assignment, you are required to design and implement a mini bot that assists Australian high school (HSC) students

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Choose your university right. Overview: In this assignment, you are required to design and implement a mini bot that assists Australian high school (HSC) students in finding a university course that suits them best. Users will input their desired course(s) of study. In return, your software will return a list of Australian universities that offer this course, along with some information about the university that offers it and its selection criteria, as detailed below. Objectives: 1. Explore different web scraping tools. 2. Learn to design and implement software with practical real-life applications. 3. Present results in a professional setup. Course Learning Outcomes covered: 1. Demonstrate the basic concepts, applications and problems of web and social networks. 2. Apply ethical principles to real life business problems Due date: This assignment is due Fri 24th Feb 2023 - 11:59 PM Sydney time (AEST) (last day before midterms). Deliverables: 1. Source code: Python notebook (* .ipynb file). 2. Standalone executable file (*.exe but compressed to .zip file for Blackboard to accept it). (you may use PyInstaller or your favourite library and make the .exe in headless mode). 3. Documentation: MS-Word file. Project description: Every year, hundreds of thousands of graduating high school (HSC) students in Australia apply to universities. They do so either by sending their applications directly to the universities they wish to enrol in, or through Admission Centres (AC). While many applications are accepted, a sizeable proportion are rejected. According to the statistics of the Department of Education, Skills and Employment (DESE), a total of 295,095 students applied either through a AC or directly to universities in 2021. Out of those, only 241,558 offers were made. This is an offer rate of 81.9%, the lowest since 2011 (80.8\%) [1]. In this project, you are required to further explore the automation process of searching for the suitable universities to apply to. This will help applicants make better informed decisions and, hopefully, free their time to meet other requirements that increase their chances of acceptance. To achieve this purpose, you will develop a software tool that scrapes information from Australian universities websites and finds their selection criteria. For the purpose of this project, we will limit ourselves to five major public universities in Sydney: U Syd, UNSW, UTS, Macquarie and WSU. The users will provide their preferred course of study. Your tool will search the UAC website [2] for the universities (among those five) that offer this course at undergraduate level ( 3 years). You will then return a table with the following information about the universities found: - University name - Guaranteed ATAR (Australian Tertiary Admission Rank guaranteed to secure a place at this university) - Pre-requisites (required high school subjects to join this course) - Location of university - Employability rate (maybe on Google, not UAC) Optional information (bonus): - Ranking (maybe on Google, not UAC) - Assumed knowledge (optional high school subjects) - Accommodation nearby. Code requirements: 1. Read the user input (desired course). 2. Use an appropriate web scraping tool to grab the required information from the Web. 3. Analyse the data and save it to CSV text file Documentation description: Your report should contain the following basic sections: 1. Problem statement: (1/21 page) define the problem you are addressing and your aim in solving it. 2. Implementation details: (1-2 pages) describe your approach, the language you used, the web scraping library you used, etc... Justify your choices. 3. User manual: (2-3 pages) explain the steps I need to follow to be able to run your code on my machine. Include screenshots of your running code. 4. Testing: (2-3 pages) run your code on a variety of test cases. Show the: (i) input, (ii) case description, (iii) output, illustrated with screenshots. 5. Conclusion: (1/21 page) what you did and what you did not do. Ethics, limitations and future work

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