Learn how to deal with larger-than-memory datasets and also how to format python code using git hooks ABOUT THIS EVENTDealing with large datasets can be a challenge when your computer does not have enough memory. As a data scientist, you might want to use python instead of moving your dataset to a SQL table. In this event, learn how you can optimize a dataframe's memory usage and work with larger-than-memory datasets in python. We will cover pandas memory optimization and tools such as dask, SQL, and the Cloud. Bonus content—Learn how to automatically format your Python notebooks to adhere to PEP8 standards using git hooks. Having a coding style is important when working in a team and making it work automatically is key to adoption. This is an intermediate-level webinar perfect for anyone with basic familiarity with pandas and/or git. Agenda:5:00 - 5:15 PM: NYC Data Science Academy Overview5:15 - 5:50 PM: Creating Clean Jupyter Notebook Presentation5:50 - 6:00 PM: Q&A BIORishi Goutam is a recent graduate of the NYC Data Science Academy's Jan 2022 cohort. He was previously a software engineer at Microsoft and Amazon and has also worked as a technology strategy consultant. About NYC Data Science Academy NYC Data Science Academy provides data science training programs and courses that prepare people for employment opportunities for data science professionals across all industries. NYC Data Science Academy teaches data science, trains companies and their employees to better profit from data, excels at big data project consulting, and connects trained Data Scientists to our industry. We have graduated over 5000 students at this point! Join our Interactive Distance / In-Person Learning Bootcamp, and get ready for the next step in your data science career! (https://nycdatascience.edu/data-science-bootcamp/)

**One of the most important skills of a data scientist is properly communicating concepts. Perhaps, the best way is through visualizations. In this webinar, we will look at multiple types of visualizations and analyze why some work and others do not. This will include an explanation of when to use specific types of visualizations, what are important features to consider when creating them, and best practices in designing them.** **Join us on Tuesday, May 24 at 5-6 PM, to learn how to visualize information like a data scientist. No coding, statistical, machine learning, or visualization experience is required to attend.** **Agenda:****5:00 - 5:15 PM: NYC Data Science Academy Overview****5:15 - 5:50 PM:** * **What is a good visualization?*** **How to decide which visualization to use*** **Best practices when creating visualizations*** **Creating a great visualization** **5:50 - 6:00 PM: Q&A** **Oren is an instructor and bootcamp coordinator at NYC Data Science Academy. He has taught courses on a multitude of topics, in online and in-person environments. He holds degrees in statistics, education, and technology. Prior to joining NYC Data Science Academy, he was a PhD candidate in Cognitive Science in Education at Columbia University. He has a strong opinion about visualizations, specifically pie charts.** **About NYC Data Science Academy** **NYC Data Science Academy provides data science training programs and courses that prepare people for employment opportunities for data science professionals across all industries.** **NYC Data Science Academy teaches data science, trains companies and their employees to better profit from data, excels at big data project consulting, and connects trained Data Scientists to our industry. We have graduated over 5000 students at this point!** **Join our Interactive Distance / In-Person Learning Bootcamp, and get ready for the next step in your data science career! ([https://nycdatascience.edu/data-science-bootcamp/](https://nycdatascience.edu/data-science-bootcamp/))**