Foundations of Data Analytics
Build a strong foundation in data analytics by learning data collection, cleaning, visualization, and basic statistical techniques.
Foundations of Data Analytics
Build a strong foundation in data analytics by learning data collection, cleaning, visualization, and basic statistical techniques.
Foundations of Data Analytics
Overview
Begin your journey with the essential principles of data analytics. This section covers the entire data pipeline—from gathering and cleaning data to creating basic visualizations and applying descriptive statistics.
What You Will Learn
- Data Collection & Integration: Discover various sources and techniques to collect reliable datasets.
- Data Cleaning & Preprocessing: Learn methods to handle missing values, normalize data, and prepare it for analysis.
- Basic Visualization: Use tools like Python’s Matplotlib and Pandas to craft insightful visual displays.
- Descriptive Statistics: Apply fundamental statistical measures to summarize and interpret data effectively.
Why This Matters
A robust foundation in data analytics is crucial for informed decision-making. Mastery of these basics will enable you to tackle more complex challenges, including those in cybersecurity.
Hands-On Learning
Engage in practical exercises using open datasets and Python libraries to practice cleaning, visualizing, and interpreting data.
🔗 Continue to hands-on projects within this category to start building your skills.