Machine Learning Data Prep with Python
Data prep is the cornerstone of any data-driven project, and Python stands as one of the most powerful tools in this domain. In preparation for the ODSC conference, our specially designed course on “Machine Learning Data Prep with Python” offers attendees a hands-on experience to master the essential techniques. From cleaning and transforming raw data to making it ready for analysis, this course will equip you with the skills needed to handle real-world data challenges. As part of a comprehensive series leading up to the conference, this course not only lays the foundation for more advanced AI topics but also aligns with the industry’s most popular coding language.
Upon completion of this short course attendees will be fully equipped with the knowledge and skills to manage the data lifecycle and turn raw data into actionable insights, setting the stage for advanced data analysis and AI applications.
Sheamus McGovern
Founder and Engineer | ODSC
Sheamus McGovern is the founder of ODSC (The Open Data Science Conference). He is also a software architect, data engineer, and AI expert. He started his career in finance by building stock and bond trading systems and risk assessment platforms and has worked for numerous financial institutions and quant hedge funds. Over the last decade, Sheamus has consulted with dozens of companies and startups to build leading-edge data-driven applications in finance, healthcare, eCommerce, and venture capital. He holds degrees from Northeastern University, Boston University, Harvard University, and a CQF in Quantitative Finance.
Module 1
-
Quick refresher on Python data structures
Lessons 1-7:
-
Introduction to Pandas
-
Data Acquisition
-
Data Cleaning
-
Data Transformation
-
Data Manipulation
-
Data Exploration with Visualization
-
Take Home Exercises and Solutions