5 sessions starting on Mar 22
What You'll Do:
Python is the world’s leading programming language today and the language of choice when it comes to data science. This introductory but intense course will help you learn how to use the power of Python to analyze data, create beautiful visualizations and use some powerful machine learning algorithms! This course is designed for both beginners with some programming experience or experienced developers looking to make the jump to Data Science!
You will learn to use Numpy for numerical computations, matplotlib for python plotting and pandas for data analysis. In addition you will also learn to use seaborn for statistical plots and scikit-learn for basic machine learning. You will use Google’s Colab environment for coding and do an end-of-course capstone project to demonstrate your learning of various concepts.
No prior programming experience needed. A computer with internet access and a compatible browser needed for accessing and running the code.
Skill Level:No prior programming experience needed
Skills you will learn:Python, programming, Numpy, pandas, matplotlib, seaborn, scikit-learn, data analysis, visualization
About your Facilitator:
Show and Tell (Presentation or Demonstration)
Sheroes is a non-profit organization founded by Bay Area high schooler Kavya Narayan. At Sheroes Tech, qualified instructors teach girls ages 10-18 computer programming. Our classes work in 10 week sessions, each session being an introduction to even deeper programming topics.
Kavya is currently a Junior at Saratoga High School in the Bay Area. She started Sheroes back in 2017 because of her passion to inspire other girls like herself to get into tech. In addition to working as the founder of Sheroes, she also tutors students in preparation for their own AP Computer Science Classes.
Vidya Rangasayee is an experienced software engineer and is deeply passionate about Women in Tech, K-12 and higher education and encouraging girls in STEM. She has years of experience at Google, Amazon and Paypal and also at Bay Area startups and she brings this know-how into the classroom to make it not only educational but also practical and fun. She spent several years as a lecturer of Computer Science at San Jose State University and is now taking her passion for teaching one step further by pursuing a PhD in Music and AI at Stanford University, where she completed her Masters in Computational Mathematics. Her plans are to take up a full time teaching position upon completing her doctorate.