This repository contrains all the resoruces from the fourth sesison of the NYU Data Science Bootcamp. In this session, we covered Exploratory Data Analysis and some basics of Data Visualization.
Instructor: Sagar Patel
The recording of the session can be found here:
NOTE: These tasks are optional and only for your practice. They will not be graded but they can be shared with the instructor for feedback.
- Clone the current repository to the local machine.
- Find your tasks in the
task-week4folder.
NOTE: The solution will be posted in the same folder on before the next session - Move the task-week3 folder to your original repository (
username/data-science-bootcamp) once the tasks have been solved.
DO NOT FORGET TO COMMIT THE CHANGES!
Submission due: Week 09 and Week 10 of the Bootcamp
In the final project, you will apply the tools you have learned in this BootCamp to solve a realistic problem.
Due to shortage in number of sessions and the fact that this BootCamp is beginner centric, it is NOT mandatory to present the project to obtain the certificate. The presentation and demo will be a good practice for you as the ability to present and organize is a fundamental, yet undervalued part of Data Science.
If you choose to present on the last session, fill out this form available here
- A short presentation explaining your workflow and thought process (Should not exceed more than 10 minutes)
- A short demo
- 2-3 questions from the instructor
The source code can be submitted on the GitHub repository for a better profile!
- Performing Exploratory Data Analysis (EDA) on a dataset and showcasing your observations
- Training and deploying a Machine Learning model (Does not have to be too advanced)
Feel free to check out popular websites such as Kaggle, Medium, Towards Data Science or be creative and try something of your own by looking for some open-source data
If you have any questions regarding the Bootcamp, feel free to email datasciencebootcamp@nyu.edu