- The specific building location has not yet been confirmed, so please wait on the updated announcement for the exact place.
- Please bring your own food and drinks, as this particular event is not sponsored.
Learn python for Data science by actually writing code. Many people think programming is hard and they fail to learn. In fact, programming is easy but learning how to code is hard.
Let's change that. Bring your laptop and get hands-on with Amit for a fun-filled event.
No boring "hello world" type programming lectures and endless theories. You will actually do things and apply the stuff you learn. Yes, that is the difference.
What You'll Learn:
You will learn how to work with ordered data, structured data, functions, modules and much more and start writing code immediately.
Introduction to NumPy
NumPy arrays – creation, methods, and attributes and how to Vectorize Operations with NumPy.
We'll dive into Pandas, its capabilities, and its importance in the Python data science stack.
We will get real-life data from IBM Watson and use it to create a data frame.
You will be using Matplotlib for visualization. The goal is for you to be actually writing code using real-world data from IBM Watson and Kaggle.
You will be writing jaw-dropping code to create a data frame using data from Kaggle competition (https://www.kaggle.com/competitions.)
About the instructor:
Amit Sarkar -
"For the past 15 years, I worked literally as a hub of the software development process, making sure the right people are given the right information to do their jobs. As a program director, I was responsible for customers’ success on the AWS platform. This is largely a customer facing role with a strong technical angle, including both hands-on and higher-level architecture and thought leadership components. As a result, successfully developed many web application/ mobile app products that collectively created over $20 million revenue stream for the customers.
MY BACKGROUND: I have over 20 years of experience in Aerospace engineering, Cloud program management, Product development, Project management & Software development."