Teaching data science to team for improving product quality   - Learning launch 

 Challenge :     I am a part of a wealth team in a fintech organization . Our team is supposed deliver a product   which will empower our customers to manage their personal finances better . Our product has   been in the market for a long time , but we realized that we are quickly losing our market share   due to better quality product coming up in the market .   For years we have been working on this   product but we realised that it will not be possible to improve the product further with traditional   technology . Our challenge is to enable our team with advanced data science based technique   so that we can improve our product to meet the customer satisfaction .      Selection :     To solve the challenge above , we are using learning launch as a tool of design thinking .   Learning launch was a perfect suit for us because we had an idea to train our team for data   science but it was something very new for us . We had assumptions that data science will solve   our problems but we were not sure . So as mentioned in the last module of the course , we   can not rely on our own assumptions and we needed to test whether our idea will work or not .   For these kind of scenario , learning launch is perfect tool .     Application :     As , mentioned in the video of learning launch , the key part to validate any idea is to have data   supporting the idea . We needed to go to data science practitioners and figure out whether our   problem can be solved using data science techniques . We needed to find data which supported   our idea . Simply relying on our belief makes us vulnerable to confirmation bias . We contacted   different consultancy firms to find the evidence of our problem being solved by data science   techniques and indeed we found confirming data that our product can be improved with data   science techniques . We then hired corporate trainers and organized 4 week long training for our   team to enable them to implement the solution of our improved product .     We started encouraging team members to attend different data science related workshops and   conferences . We hired few data science experienced people in our team .     Insight & Approach :     By applying the learning launch tool , our team identified the weakness of our team and then   devised solution to strengthen the team . We made several assumptions and using learning   launch , we thoroughly identified those assumptions and validated them . We introduced training   our teams for data science and that made lot of difference not only to quality of our product , but   also to the overall growth and revenue of the company as well . The major insight that we 

 achieved from this experiment is that it is extremely necessary to keep the team updated with   the latest technologies coming to the market .     The alternate solution to our problem would have been to hire a consultancy firm to figure out   the problem with our team and have them fix it . But with learning launch , we were not only able   to identify the problem , but also effectively solve it . 


EMAIL: 
ID_NUM: 
NAME_STUDENT: 
PHONE_NUM: 
STREET_ADDRESS: 
URL_PERSONAL: 
USERNAME: 

### Task: You are a PII (Personal Identity Information) Detection. Given a essays written by students, you have to identify ONLY the following:
NAME_STUDENT - The full or partial name of a student that is not necessarily the author of the essay. This excludes instructors, authors, and other person names.
EMAIL - A student’s email address.
USERNAME - A student's username on any platform.
ID_NUM - A number or sequence of characters that could be used to identify a student, such as a student ID or a social security number.
PHONE_NUM - A phone number associated with a student.
URL_PERSONAL - A URL that might be used to identify a student.
STREET_ADDRESS - A full or partial street address that is associated with the student, such as their home address.
### Input: Teaching data science to team for improving product quality   - Learning launch 

 Challenge :     I am a part of a wealth team in a fintech organization . Our team is supposed deliver a product   which will empower our customers to manage their personal finances better . Our product has   been in the market for a long time , but we realized that we are quickly losing our market share   due to better quality product coming up in the market .   For years we have been working on this   product but we realised that it will not be possible to improve the product further with traditional   technology . Our challenge is to enable our team with advanced data science based technique   so that we can improve our product to meet the customer satisfaction .      Selection :     To solve the challenge above , we are using learning launch as a tool of design thinking .   Learning launch was a perfect suit for us because we had an idea to train our team for data   science but it was something very new for us . We had assumptions that data science will solve   our problems but we were not sure . So as mentioned in the last module of the course , we   can not rely on our own assumptions and we needed to test whether our idea will work or not .   For these kind of scenario , learning launch is perfect tool .     Application :     As , mentioned in the video of learning launch , the key part to validate any idea is to have data   supporting the idea . We needed to go to data science practitioners and figure out whether our   problem can be solved using data science techniques . We needed to find data which supported   our idea . Simply relying on our belief makes us vulnerable to confirmation bias . We contacted   different consultancy firms to find the evidence of our problem being solved by data science   techniques and indeed we found confirming data that our product can be improved with data   science techniques . We then hired corporate trainers and organized 4 week long training for our   team to enable them to implement the solution of our improved product .     We started encouraging team members to attend different data science related workshops and   conferences . We hired few data science experienced people in our team .     Insight & Approach :     By applying the learning launch tool , our team identified the weakness of our team and then   devised solution to strengthen the team . We made several assumptions and using learning   launch , we thoroughly identified those assumptions and validated them . We introduced training   our teams for data science and that made lot of difference not only to quality of our product , but   also to the overall growth and revenue of the company as well . The major insight that we 

 achieved from this experiment is that it is extremely necessary to keep the team updated with   the latest technologies coming to the market .     The alternate solution to our problem would have been to hire a consultancy firm to figure out   the problem with our team and have them fix it . But with learning launch , we were not only able   to identify the problem , but also effectively solve it .
### Output: 