Exploring and Analyzing Data in Python

Intermediate
Starting at USD 39.00
4 hours duration

Learn how to explore, visualize, and extract insights from data.

This course offers a comprehensive approach to transforming data into meaningful insights. Through exploratory data analysis, participants will learn how to effectively explore datasets, address inquiries, and present results visually. The course equips individuals with the necessary tools to clean and validate data, visualize distributions and relationships between variables, and utilize regression models for prediction and explanation. Participants will have the opportunity to analyze data pertaining to demographics and health, such as the National Survey of Family Growth and the General Social Survey. However, the techniques and methodologies covered in this course are applicable across various fields including science, engineering, and business. Key tools utilized throughout the course include Pandas, a robust data manipulation library, as well as other essential Python libraries such as NumPy and SciPy. Additionally, participants will gain proficiency in StatsModels for regression analysis and Matplotlib for data visualization. By acquiring these tools and skills, participants will be well-prepared to work with real-world data, uncover valuable insights, and effectively communicate compelling results.

About Provider

DataCamp
DataCamp
Online Education Provider ยท 410 courses
Description
DataCamp is an online learning platform that offers interactive courses and tutorials for data science and analytics. It provides a wide range of courses covering topics such as Python, R, SQL, machine learning, data visualization, and more. The platform offers a hands-on learning experience through coding exercises and projects, allowing users to practice and apply their skills in real-world scenarios. DataCamp also offers a personalized learning experience with adaptive learning technology that adjusts the course content based on the user's skill level and progress. It is widely used by individuals, professionals, and organizations to enhance their data science skills and stay up-to-date with the latest trends and technologies in the field.
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