Data Science Fundamentals, Part I: Learning Basic Concepts, Data Wrangling, and Databases with Python
Course provided by Pearson
About this course
Discover the foundational concepts, theory and techniques you need to know to become an effective data scientist in this Python course, led by industry-expert Jonathan Dinu. From learning how to get up and running with a Python data science environment to mastering the best practices of data validation, this course will definitely kickstart your data science career.This course is ideal for anyone who works with data and conducts analysis, or as a starting point for aspiring data scientists and quantitative researchers. The training videos with prepare you with applied, example-driven lessons in Python and its associated ecosystem of libraries, where you get your hands dirty with real datasets and see real results.
Learning outcomes
- Learn how to get up and running with a Python data science environment.
- Get to grips with the essentials of Python 3, including object-oriented programming.
- Master the basics of the data science process and what each step entails.
- Gain insight on where to find quality data sources and how to work with APIs programmatically.
- Implement best practices of data validation, including common data quality checks.