This report summarizes the three day workshop conducted and sponsored by Intel and CBSE, where we learnt about the domains of AI and using Python, a programming language to make an AI model.
Day one was all about learning the basics of AI. We were taught how to oversee a problem, and the AI Project Cycle. A board game was played which taught us the 17 Sustainable Development Goals made by the United Nations. Later, we were taught the fundamentals of Python by using Anaconda as the Base shell, while running our code on the Jupyter notebook. The first notebook we got contained all the basic syntaxes of Python. The second notebook gave us a little more to play with. We had to use logic to solve mathematical problems given to us by them. In each problem, we had to device a program to solve the same. We were then given links to Python and Anaconda documentation and were told to brush up on our Python knowledge.
The agenda for the second day was to try out three games based on the three different domains of AI – Data Science, Natural Language Processing and Computer Vision. We were taught data science, and data visualization. We were given another Jupyter notebook in which we had to import a database onto the program, and make different types of graphs while customizing them.
Later on, we explored Computer Vision, where we were taught about different pixel values and the fundamentals of Computer Color- Red,Green and Blue. Image Processing and how a computer understands an image with the help of the parameters given to it were explained. A Python notebook was given in which we had to use Google Colab, a cloud based IDE which enabled us to use a high amount of resources such as RAM, CPU power, and HDD space. In Colab, we had to process an image, crop an image, and convert colors of the same image. The next and final domain of AI, which was Natural Language Processing was then taught, which tells us how computers converted our language into theirs, which was basically converting Text into Numbers. We had to go through several steps such as removal of special characters and stopwords, lemmatization and stemming. We learnt how to make a Document Vector and a Dictionary, in NLP terms, of course. As homework, we had to finish an NLP worksheet.
The final day, Shreyas and Saaswath paired up to make an AI project, which predicted if a certain contagious disease in an area could be passed on to another person living in the same locality. This used Computer Vision (cameras attached to drones) and Data, which we obtained from hospitals. We were asked to give a video testimonial on the workshop as feedback. We received our certificates, made new friends, took a few pics and returned home. We knew that we had learnt a lot, and would continue our journey as developers. But of course, we could not forget the excellent food we got for three days!!