 Hi, everyone. So I am Konal, founder of Analytics Vidya. Analytics Vidya is world's largest analytics community. And we started this journey about two years back. Before I actually take you through what I wanted to discuss, just a quick show of hands. How many of you know about Analytics Vidya? OK, and how many of you want to be a data scientist or are already a data scientist? Sure, thanks. So as I said, so Analytics Vidya is actually a community of analytics professionals. What we want to do is create a community where people come in, share their knowledge for free, and essentially contribute to learning of the people who are there already as part of community. We reach out to about 3,000 people month on month in various modes. So blog being our most popular mode. So on the blog front, we write various articles. So this is our home page. There are specific resources on Python. For example, we have a comprehensive learning path on Python, which you can come and see. Again, it starts from bare basics, why you should use Python to what are the tools you would need, and then what are the libraries. We do various medias again. So starting from infographics. So this is an infographic on machine learning algorithms. So that's the first part of what we do. The second part, essentially, without which a community cannot work, is discussion portal. So in terms of discussion portal, again, it's a very active discussion portal. Typically, people would get answers to their queries in less than three to four hours. And there is a constant interaction, constant feedback. So this we launched about seven, eight months back, so January to be precise, actually. And it's building up nicely coming along well. These are some Python-related questions again. And finally, lately we have started some data science hackathon. So for those of you who know Kaggle, it's a shorter form of Kaggle. So we run two to seven days competition. And again, the focus is on learning. So even the people who are on top of leaderboard actually share their solutions with the larger audience. And then they learn and they improvise. So at the end of the day, everyone comes out by learning and doing a lot more learning than what you would do in, let's say, a period of 15, 20 days. So why am I here? Why am I sharing this platform? The idea was that I saw a lot of interest in last two days in data science. In all the talks which were related to data science, I could see a lot of interaction. So I thought I'll just come up, show what we have been doing. I would love to interact with you. We would love to take your questions, help you out. Or in any way, we can help spreading data science in India or globally. We will love to do that. Thanks.