Exploratory Data Analysis (EDA) Online Course
Join our virtual, live instructor-led session and master Exploratory Data Analysis (EDA) Training from anywhere in the world.
Upcoming Virtual Training Schedules
Join from anywhere in the world with our live instructor-led sessions
| Code | Start Date | End Date | Duration | Fee | |
|---|---|---|---|---|---|
| EDA-01 | Mon - Fri (5 Days) | USD 850 | Reserve my seat → Register my team → | ||
| EDA-01 | Weekend (4 Weeks) | USD 850 | Reserve my seat → Register my team → | ||
| EDA-01 | Mon - Fri (5 Days) | USD 850 | Reserve my seat → Register my team → | ||
| EDA-01 | Mon - Fri (5 Days) | USD 850 | Reserve my seat → Register my team → | ||
| EDA-01 | Weekend (4 Weeks) | USD 850 | Reserve my seat → Register my team → | ||
| EDA-01 | Weekend (4 Weeks) | USD 850 | Reserve my seat → Register my team → |
Here's What You'll Learn
Each module tackles real challenges you face in your role
Exploratory Data Analysis Foundations and Frameworks
Data Profiling and Initial Inspection
Univariate Analysis and Distribution Discovery
Bivariate Analysis and Relationship Mapping
Multivariate Interrogation and Dimensionality
Outlier Detection and Anomaly Management
Missing Data Strategies and Imputation
Feature Engineering and Data Transformation
Time-Series and Geospatial EDA
EDA Synthesis and Executive Reporting
Market-specific guidance for Zambia
A country-aware view of the pressures, proof points, and practical tools that shape how this course applies locally.
Tools and platforms relevant to this field
5Field-relevant examples that may be featured in training where they support the confirmed scope. Exact coverage depends on participant needs and delivery format.
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Python Python Software FoundationUsed to clean datasets, compute summary statistics, and automate reproducible EDA workflows.
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pandas pandas development teamUsed for data cleaning, tabular inspection, missing-value checks, and fast aggregation during exploratory analysis.
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NumPy NumPy communityUsed for numerical operations, array handling, and efficient computation of descriptive statistics.
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Seaborn Seaborn projectUsed to produce statistical visualizations such as distributions, correlations, and grouped comparisons.
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Matplotlib Matplotlib projectUsed to create custom plots and communicate findings clearly in reports and dashboards.
Where this course runs
Exploratory Data Analysis (EDA) Training is delivered in the cities below — pick the one that fits your schedule.























