Expert Network : Learning launch     I am using this assignment to demonstrate the application of learning launch tools .     Introduction :     I lead Global Communications at Coursera . ​Coursera was founded by Daphne Koller and   Andrew Ng with a vision of providing life - transforming learning experiences to anyone ,   anywhere . It is now the world ’s largest online learning platform for higher education . 190 of the   world ’s top universities and industry educators partner with Coursera to offer courses ,   Specializations , and degrees that empower over 40 million learners around the world to achieve   their career goals . There are more than 6,000 instructors from these top universities teaching on   Coursera platform .      Challenge :      While Coursera platform has thousands of professors , many of them being world - renowned   voices and subject matter experts , their use of the Coursera platform is often limited to   producing and distributing learning content . In the process , they reach out to thousands of   learners around the world . This is incredibly impactful and gratifying in its own way for both   professors and learners . However , we wanted to create a second - order effect that goes beyond   courses .      Our idea was to create a web destination that houses all the professors on our platform , who   are searchable by their expertise area , and a way for media to connect with them for their   stories . We have these amazing thought leaders on the platform , and Coursera often receives   media requests to connect with these experts , on an average about 10 a month . We now   wanted to create an easy destination and an automated workflow that gets reporters connected   to experts .        Selection :      I found tools proposed in the Learning launch a perfect model to apply . There are a number of   reasons for that : 

 ● Idea validation​ - To ensure professors and university partners feel excited about   participating in the launch , we had to first interview many of them to gauge their pulse .   On the other hand , we also had to talk to various reporters across the world to   understand if they would genuinely appreciate a platform that can help them connect to   expert voices for stories they are working on daily basis . 

 ● Specific Person - ​Two specific personas this idea was meant to serve . One is the   professor who would be interested in sharing their knowledge with the world and growing   their school ’s brand . The second is the everyday reporter who is often on a deadline ,   running around looking for renowned experts to provide credible quotes for his / her story . 

 ● Has a specific need ​- Its not easy for media to navigate through a university system to   connect with professors . Yes , there are certain savvy professors who are accessible , but   the large majority remain inaccessible . In order to meet the demand , we need a system   that scales to many professors , easily searchable , and has built - in requests flow . This   may have limited appeal in the US where reporters are well - connected with academic ,   but imagine a reporter in India wanting to connect with a Stanford professor on machine   learning for a story on biases in machine learning systems . Or a reporter in Argentina   wanting to connect with Rosanna Gonzalez of University of Virginia on a story she is   working on design thinking principles . 

 ● How idea meets the need - ​We created a a website that is accessible worldwide . It has   indexed 300 professors to start with ( from a base of 6,000 ) since we are want to learn   and optimize . We tagged them with their expertise areas and made it searchable . We   also embedded a form through which reporters can submit their requests for connection .   The backend is where the fun starts . Coursera team filters out the requests and sends it   to the professor and university marketing team , which in turn respond to the reporter .   When a reporter is searching for experts , the website shows 3 - 4 options so if one   professor is busy or unresponsive , the reporter can reach out to others . 

 ● Why our solution is better than other alternatives - ​Most alternatives out there are   run as speaker bureaus who offer a limited choice of experts with a varying degree of   expert reputation . They also charge a fee for the service -- one of reasons why media   mostly avoids using them . Our solution is totally free , screens for highest quality experts   from some of the best schools in the world . These are often authority figures in their   domains . 

 Insights :     There are a couple of important insights we discovered while applying the tool . 

 ● It was quite important that we do n't try and boil the ocean by onboarding all 6,000   instructors on our platform . It would have been time - consuming and complex . Instead ,   we prioritized the list to 300 top instructors based on a scorecard we developed for the   highest probability of demand and success . We also wanted to ensure that instructors   we are including in the first round are not only well - known but also enthusiastic about   participating in the Expert network . 

 ● We understood in the hypothesis validation phase that for attention - deficit reporters the   recall of Expert network will start fading after a few weeks of launch . We had to find a   way to keep it top of mind . That is when we adjusted the website architecture to go   beyond a searchable index to also start being a site where professors are commenting   on issues of the day . The site has 3 - 5 mins videos , audio interviews , podcasts with   professors which constantly gets updated with new short - form content . We also push   this out to reporters on a weekly basis . This gives story ideas to reporters , keeps the site   top of mind , and showcases the quality of professors on the site . 

 What I might do differently next time : 

 ● I underestimated the technical challenges of creating a website that draws on data from   different data warehouses . Next time , I ’d have a data engineer on the project from the   start . 

 ● I also discovered that a lot of skills originally tagged to professors in our existing data   systems are not broad enough or simply too technical that a reporter may not   understand them . We had to rewrite many such skills tags to make it comprehensible for   media . Again , it is something that we underestimated in terms of efforts initially . But glad   that we only did the learning launch with 300 , as that allowed us to create a system that   we can now roll - out to thousands in due course . 


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: Expert Network : Learning launch     I am using this assignment to demonstrate the application of learning launch tools .     Introduction :     I lead Global Communications at Coursera . ​Coursera was founded by Daphne Koller and   Andrew Ng with a vision of providing life - transforming learning experiences to anyone ,   anywhere . It is now the world ’s largest online learning platform for higher education . 190 of the   world ’s top universities and industry educators partner with Coursera to offer courses ,   Specializations , and degrees that empower over 40 million learners around the world to achieve   their career goals . There are more than 6,000 instructors from these top universities teaching on   Coursera platform .      Challenge :      While Coursera platform has thousands of professors , many of them being world - renowned   voices and subject matter experts , their use of the Coursera platform is often limited to   producing and distributing learning content . In the process , they reach out to thousands of   learners around the world . This is incredibly impactful and gratifying in its own way for both   professors and learners . However , we wanted to create a second - order effect that goes beyond   courses .      Our idea was to create a web destination that houses all the professors on our platform , who   are searchable by their expertise area , and a way for media to connect with them for their   stories . We have these amazing thought leaders on the platform , and Coursera often receives   media requests to connect with these experts , on an average about 10 a month . We now   wanted to create an easy destination and an automated workflow that gets reporters connected   to experts .        Selection :      I found tools proposed in the Learning launch a perfect model to apply . There are a number of   reasons for that : 

 ● Idea validation​ - To ensure professors and university partners feel excited about   participating in the launch , we had to first interview many of them to gauge their pulse .   On the other hand , we also had to talk to various reporters across the world to   understand if they would genuinely appreciate a platform that can help them connect to   expert voices for stories they are working on daily basis . 

 ● Specific Person - ​Two specific personas this idea was meant to serve . One is the   professor who would be interested in sharing their knowledge with the world and growing   their school ’s brand . The second is the everyday reporter who is often on a deadline ,   running around looking for renowned experts to provide credible quotes for his / her story . 

 ● Has a specific need ​- Its not easy for media to navigate through a university system to   connect with professors . Yes , there are certain savvy professors who are accessible , but   the large majority remain inaccessible . In order to meet the demand , we need a system   that scales to many professors , easily searchable , and has built - in requests flow . This   may have limited appeal in the US where reporters are well - connected with academic ,   but imagine a reporter in India wanting to connect with a Stanford professor on machine   learning for a story on biases in machine learning systems . Or a reporter in Argentina   wanting to connect with Rosanna Gonzalez of University of Virginia on a story she is   working on design thinking principles . 

 ● How idea meets the need - ​We created a a website that is accessible worldwide . It has   indexed 300 professors to start with ( from a base of 6,000 ) since we are want to learn   and optimize . We tagged them with their expertise areas and made it searchable . We   also embedded a form through which reporters can submit their requests for connection .   The backend is where the fun starts . Coursera team filters out the requests and sends it   to the professor and university marketing team , which in turn respond to the reporter .   When a reporter is searching for experts , the website shows 3 - 4 options so if one   professor is busy or unresponsive , the reporter can reach out to others . 

 ● Why our solution is better than other alternatives - ​Most alternatives out there are   run as speaker bureaus who offer a limited choice of experts with a varying degree of   expert reputation . They also charge a fee for the service -- one of reasons why media   mostly avoids using them . Our solution is totally free , screens for highest quality experts   from some of the best schools in the world . These are often authority figures in their   domains . 

 Insights :     There are a couple of important insights we discovered while applying the tool . 

 ● It was quite important that we do n't try and boil the ocean by onboarding all 6,000   instructors on our platform . It would have been time - consuming and complex . Instead ,   we prioritized the list to 300 top instructors based on a scorecard we developed for the   highest probability of demand and success . We also wanted to ensure that instructors   we are including in the first round are not only well - known but also enthusiastic about   participating in the Expert network . 

 ● We understood in the hypothesis validation phase that for attention - deficit reporters the   recall of Expert network will start fading after a few weeks of launch . We had to find a   way to keep it top of mind . That is when we adjusted the website architecture to go   beyond a searchable index to also start being a site where professors are commenting   on issues of the day . The site has 3 - 5 mins videos , audio interviews , podcasts with   professors which constantly gets updated with new short - form content . We also push   this out to reporters on a weekly basis . This gives story ideas to reporters , keeps the site   top of mind , and showcases the quality of professors on the site . 

 What I might do differently next time : 

 ● I underestimated the technical challenges of creating a website that draws on data from   different data warehouses . Next time , I ’d have a data engineer on the project from the   start . 

 ● I also discovered that a lot of skills originally tagged to professors in our existing data   systems are not broad enough or simply too technical that a reporter may not   understand them . We had to rewrite many such skills tags to make it comprehensible for   media . Again , it is something that we underestimated in terms of efforts initially . But glad   that we only did the learning launch with 300 , as that allowed us to create a system that   we can now roll - out to thousands in due course .
### Output: 