# data[].attributes.body
I really enjoyed the ethics discussions we had in class. I felt comfortable learning from the mentors as well as my peers.

# data[].attributes.body
The labs were very helpful with Faith going through what we needed to include in the labs. It was also helpful getting feedback about where we could improve and the opportunities there were to show our advanced knowledge in different areas.

# data[].attributes.body
This is where I learned the most honestly. I was able to put my knowledge to the test here actually apply what we learned in the labs.

# data[].attributes.body
I enjoyed the group project. It was a nice chance to get to know fellow classmates and learn from them. I liked how even though we were online, I could still connect with them and present our findings together. The project was open-ended enough where we could go very advanced or also minimally advanced which I appreciated.

# data[].attributes.body
I would say that it was a little bit harder than I thought it would be, but it was manageable and I could keep up. It was not as introductory because some of the skills we needed were a bit more of coding that I did not know, and I had to learn a bit on my own.

# data[].attributes.body
I found all the admin to be very accessible. They were all nice and supportive and understanding if we were not understanding as well.

# data[].attributes.body
I did end up feeling pretty connected with everyone in the class and I felt like I was with people of similar levels of AI knowledge, but also a vast variety so there was room for me to learn from othes.

# data[].attributes.body
It was a great learning experience. There was a good scope for learning as everyone shared their perspectives.

# data[].attributes.body
This session gave us practical experience. I could bridge a gap between the thereotical and practical knowledge.

# data[].attributes.body
I thought the ethics discussions introduced some really pressing concerns in AI, and it is very important to be mindful of these issues. I loved learning about different AI tools created as well

# data[].attributes.body
I could access myself while working on the assignments. I could address actual doubts.

# data[].attributes.body
Yes, it was difficult to manage at first. But this taught me how to manage the time. The level of difficulty was average.

# data[].attributes.body
The instructor and TA were very nice, helpful, kind and patient. They were quick to respond.

# data[].attributes.body
The project was a wonderful learning experience of team work. I got opportunity to meet new people. As we shared different ideas, I was able to discover various perspectives, applications in AI, ML.

# data[].attributes.body
After this program, I believe AI helps extend the capabilities of online communities and makes management a cake-walk for community managers. To add-on, AI helps moderate community to minimize overall operational cost.

# data[].attributes.body
I really enjoyed the challenge, it was tough, and I needed to dig myself a more than I expected to make all the labs work, but the learning experience was guided which made it great. I always wanted to start coding something that seemed like a ML because all my past courses were just theory and nothing in practice. I really liked them.

# data[].attributes.body
There is no other way to put all the knowledge learnt in practice if you don't suffer a little bit making it work. The cases covered much more than I expected and the more exercises I did the better I understood the concepts.

# data[].attributes.body
In this point I think that it can be improved, I didn't receive any feedback in the comments I made in the discussions and I didn't really feel that I could interact with my classmates thru them.

# data[].attributes.body
Working in teams is always a better way to complete bigger goals, the problem here is that we all had very different schedules, we never met in person and the remote environment didn't help to work better. That is my main feedback, at the end some initiatives we couldn't follow them because of the complexity and the work in the team was not really fair for all the team mates. I did my best to learn the most I could and I really did, at the end with the real case we chose I really felt that I was doing a prototype that had a potential use.

# data[].attributes.body
Definitely much more than expected for a Discover session, I really thought that it was going to be an introductory course, also I didn't understand that there were 2 sessions from the beginning so it was more demanding than was planned, I struggled a lot but learnt the same.

# data[].attributes.body
The instructor is really passionate of this subject which I can feel and a student and encourages me to do it better. Anytime I asked for help I received it.

# data[].attributes.body
I don't really feel that everybody was at the same level, we all thought and expected different things, but with the project I worked together with my team to make it through.

# data[].attributes.body
The lab sessions were a great walkthrough about different ML models. I wish we could have in person lab sessions though.

# data[].attributes.body
The hands-on lab assignments were helpful to build a better understanding about what we talked about. It's cool to apply what we are learning to a real-life scenario.

# data[].attributes.body
I had a great group, and the project went smoothly. It was pretty challenging overall, and I had some trouble splitting up the work.

# data[].attributes.body
It wasn't terribly difficult since a lot of the notebooks were pretty straightforward with a lot of hints in the instructions.

# data[].attributes.body
The instructors were nice and got back to me really quickly if I missed an assignment. Great and supportive staff overall!

# data[].attributes.body
I felt like I belonged, but it was difficult to make new friends because of a lack of an in-person aspect.