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L2A task suitable for someone who is comfortable helping with implementing features.A task suitable for someone who is comfortable helping with implementing features.
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Overview
We have the scraper and parse for degrees data now. The sample data is as follow:
{
"name": "Systems Engineering and Management",
"school": "Erik Jonsson School of Engineering and Computer Science, Naveen Jindal School of Management",
"degree_options": [
{
"level": "MS",
"public_url": "https://academics.utdallas.edu/fact-sheets/ecs/ms-systems-engineering-and-management/",
"cip_code": "14.2701.00",
"stem_designated": true,
"joint_program": true
},
{
"level": "MS",
"public_url": "https://academics.utdallas.edu/fact-sheets/jindal/master-of-science-in-systems-engineering-and-management/",
"cip_code": "14.2701.00",
"stem_designated": true,
"joint_program": true
}
],
"areas_of_interest": [
"systems engineering",
"engineering",
"technology",
"business",
"management"
]
},
Add the uploader that can push this data to MongoDB.
Special
This might be too ambitious considering the timeline but if we get this done and someone gets the endpoints done for this over the API server, we can have the data available in prod API for HackAI on March 7th.
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L2A task suitable for someone who is comfortable helping with implementing features.A task suitable for someone who is comfortable helping with implementing features.