Many beginners intrigued by Data Science/ML/AI behold it in the awe and fear reserved for a hairy monster. Most of it originates in the fear of math, not to mention the overwhelming variety of buzzwords flying past in all directions.

It’s not all dark and gloomy though. If you develop a strong intuition for certain fundamental concepts, you won’t just find your way in this forest, but will also feel confident and equipped to create your own paths.

The instructors aim to aid building that intuition through an immersive, daylong workshop. You will learn machine learning concepts and tools from first principles!

#### Why Attend?:

Today it certainly is imperative for tech professionals of all kind to be, at the very least, initiated on concepts of machine learning and data science. While there is no dearth of material available on the internet to educate yourself, it certainly is too overwhelming for someone who’s just made up the mind to plunge into this seemingly vast, bottomless sea. Needless to say, however, that the journey is extremely satisfying as well as rewar ding, if you are equipped to take it.

Numpy, Scipy, Pandas, scikit-learn etc are emerging as some of the most handy tools for the modern sailors and intuition for concepts like probability theory, functions, differential calculus, gradient descent algorithm are the planks that form the very rafts on which one sails. Let’s build our own and enjoy the first dip !

#### Maths Knowledge Requirements

Part 1 of the workshop will cover all the maths well. So you should know how to do addition, subtraction, multiplication and division. Plus, you need pen, paper and some grit to keep writing as the existential Xs stare back at you asking “Who am I? Why am I here?”

#### Programming Knowledge Requirements

You should know basic programming (reading and writing from/to files, flow controls (if-else), looping constructs like for loop, while, variable assignments). In other words, you should have programmed few hundred lines in any mainstream programming language.