Pre-session jitters and apprehensions - Mentor story by Vishal

It was fun working with kids. Teaching them about data science was expected to be fairly difficult task. But it really awesome to see the level  of children and how quickly they could grasp concepts. But at the same time I felt a few weak kids being left behind and were hesitant to raise doubts. Here I guess having a mentor to whom they could ask their doubts had helped a lot.  

In this camp it was interesting to see how I could make kids interact with me. So I tried to ask them their interests and tell them how they could use data science in their field of interest which was sports in my kid's case.  

I felt that little more time should be spent on teaching excel  so that they could try out new things with the data, maybe try out other visualizations and see if they were more intuitive.  I could see that they had no experience with Excel. Initially I wasn’t even sure if I should teach them about filters. But they could grasp it quickly and use it.

In the data that we were analysing all bins had almost same amount of data but slightly more on the lower side given the rubric. When I asked what could be deduced about this kid from the graphs they said looks like the kid is confused and doesn’t want to make a lot of friends.

What I had to specifically take care was that I don’t use jargon and keep it as simple as possible because that would make them stop understanding stuff and simply lose interest. Before this session also I feared that if not done properly children might lose interest in this completely and have a bias against it throughout their lives. Through the end we could see that children were pretty happy and were not bored.

Another interesting thing that I noted while the kids were writing the blog at the end was they were discussing what they had done through the experiment and what was the inference from it. So making them write about what they understood or their experience was a good choice.

Vaibhav's Second Sojourn in Data Land

Vaibhav enjoyed our second workshop and learned a fair bit. Here is what he learned.

Last time, we entered the rating for students on the card for "alpha". We plotted the data against the features and found that alpha likes to make friends with people having new names.

 So we say that alpha is more likely to make friends with people having new names. We will predict that those having new names are likely to be friends with alpha. A simple Excel formula will award 5 points if a given person has a new name and will award 1 for an old name.

Now we must see if our prediction is correct. We give a 1 if our prediction is true i.e. if for a given person alpha has given a score of 4 or 5 and we too have given him a score of 5, we put 1. Otherwise, put a zero.

1's are correct predictions; 0's are incorrect predictions.

To see how accurate we were we will calculate the percentage of 1's or correct predictions. We found that it is 62.5% correct! Not bad!

" ..Once again a lot of fun .." - Tanish on the 2nd Workshop

Tanish, exhilarated at the end of the camp, said

“ I learned to make percentages and once again a lot of fun. I learned more about data science like to make predictor in excel and a new website called blogspot.com.I made a predictor on Beata who likes indoor GAMESVB  . I learned a new method in excel that is =if (c23=”Indoor”,5,1).”

                                                                                                                                    - Tanish

Some of the graphs he made - 

Predicting Kids Preferences - Kushagra

Here's what Kushagra had to say after the second workshop -

“I learned more about data science

How to make predictor in excel

We learned a new formula =if(c2= “indoor”,5,1)”

                                                      - Kushagra

Here are some graphs that Kushagra came up with to infer from the data

'I learn this way of storing data' - Kids Report - Akshat and Veerika

"I learn this way of storing data and come up with different observations on the rule of probability. It was really exiting learning all this with Nishant sir"

- Akshat

"I really enjoyed attending this workshop .I learned about data science and working with MS exel. I learned that foo likes outdoor games more than indoor"

- Veerika

Their work during the workshop as is:

  

Kids Report - Vrinda and Raghav

Vrinda's and Raghav's work:

From the above graph, we conclude that foo makes less friends  . The proportion of friends are more in the 2,3 and 4 columns.

From the above graph we infer that he is not biased relating to new or old names. He is fine with having friends with new or old names.

He makes male friends more than female.

The friends he had made  play outdoor games more as compared to indoor games..



  

Kids Report - Sreshta and Akshat

Inferences by Sreshta and Akshat :

This graph shows that the person wants 5 friends out of 32.

We graded 5 as – wants to really make friends.

We graded 4 as – may make friends.

We graded 3 and 2 as- he has a weak possibility to make friends.

We graded 1 as- that he would definitely will not make friends.

By observing this data we conclude that the person does not make friends frequently.

We conclude that the person makes equal no. of friends as males and females.

From this graph We know that the person makes more new name friends  

From this graph we know that the person likes outdoor games more than indoor games.

"We can understand anyone" - Kids Experience - Parth and Vaibhav

"We learn that we can store anyone’s data. And we can understand anyone. We asked them that whom they want to make friends male or female by their friends name and their hobbies. We compiled it in Microsoft excel. To understand others of their thinking of their friends"

Parth and Vaibhav

One of the graphs they drew while observing their dataset's preferences:

2 implies 'will befriend' and 1 implies 'wont befriend'

Using Data to Get More Gifts from Parents - Kids Report - Tanish and Vaibhav

Vaiabhav : "It was a  very good experience and I loved it. I learned how to predict a stranger’s choices just based on his or her data.  It was very good.  I would like to predict my spending."

How will you use what you learned today?

Vaibhav : "I would like to predict what subjects I study I most, how frequently I study specific subject"

Tanish : "It was amazing and I learned many new things like handling excel and I learned about others and cholera and how to solve cholera"

Vaibhav : ‘Solve? Maths problem thodi hein’

Well technically, we did treat it as a math problem.

How will you what you learned today?

Tanish : "Exams. I would take my exam results, from the report card of every year.  And then I will make it on excel and then I will remember the grades and the one I get more grades I will take a gift"

Their work as is:

A pie chart having an existential crisis.

      

Kids Experience - Kushagra and Pragya

"I learned about data science. I learned about excel. It was a nice workshop. I had fun."

 - Kushagra

"IT WAS A NICE WORKSHOP.I REALLY ENJOYED IT. I LOVED TO LEARN MORE ABOUT DATA SCIENCE."

- Pragya

Their work as is:

Doing something for the first time in the world and the apprehensions! - Mentor experience by Abhishek

The day I came to know about Data Science Camp organised by Aspiring Minds, I was interested to see how Data Science could be taught to these kids. When I came to know about things which are to be taught to students, I was apprehensive about the success of this event because of three major reasons:

1. I was not sure if parents would take this much of pain to drop their kids to a camp which was not related to any of the academic activity of their ward
2. I was not sure if a kid of standard 5th or 6th  would be interested in data science
3. If students were aware about excel, formulae and graphs which were supposed to be used?

Thanks to our mentor Varun Aggarwal for instilling confidence in all of us that we will certainly put up a great show. Moreover, he also mentioned the pros and cons of doing anything which were never tried before.  Saturday, 13th June 2015, it was 10:20, three kids arrived, A, B and C (keeping them anonymous). Two of them were from 8th standard and ‘C’ was in 5th grade.

Me: What do you people expect from this Data Science camp?

Realizing the strength of data! by Nishant

It was a nice experience to make kids familiar with the data science. We believe that experiments are best way to make kids realize the strengths of data. 

Experiment:

Alpha and Beta were given 48 pictures of different faces, with accompanying names, and a favored activity. They were instructed to rate each person on the scale of 1 to 5 points whether they would want to be friends with him. The data set was further divided into 36-12 train-test set.

Then data sets were exchanged among groups. We gave the data collected from Gamma to the Alpha and Beta.

First, they filled ratings of likes and features values in the excel sheet.

Experiences with my alpha and beta by Tushar

A 3 hour camp was organized for students in classes 6th to 8th with the objective of introducing them to the science of data analysis and to teach them how they to play with data to derive meaningful information and use then to make statistically driven decisions.

As a member of the Aspiring Minds data team, I was assigned the task of mentoring two participants and helping them through the exercise designed for this camp. The exercise required the students to use spreadsheets

-          to study the distribution of data,

-          derive inferences on various parameters of information captured,

-          differentiate the stronger patterns from the weaker ones.

Did Marconi really invent the radio? Breaking the ice by Parth

Abhishek and I conducted the ice breaking session for kids. It began with introducing kids to each other by asking them to distribute i-cards to each other. We made pairs by asking them to randomly pick a card which had either a name of a famous Indian scientist or his invention and then they had to pair up with their counter part. It was interactive,engaging and informative - kids learnt something new by looking up these scientists on the internet. Some scientists like Birbal Sahni were hard finds. Kids were asking me what Paleobotany is. Also, the founding father of the modern radio lead them to Marconi- which is the usual perception, instead of the actual answer, which is JC Bose. It was a new learning for them too.

Ice breaking session

The name guessing game we played was also interesting in the sense that it gave us an idea of how kids think and rethink about a problem as you give them more data and more positive feedback. I think our next exercise could involve a similar concept too- assessing accuracy when more data is provided iteratively.

My experience with both the kids assigned to me for the exercise was very good. I think