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 Ireland
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
6Field-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 inspect, clean, summarize, and visualize datasets during EDA.
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Pandas The pandas development teamUsed for data profiling, missing-value checks, joins, grouping, and summary statistics.
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NumPy NumPy communityUsed for numerical operations, array handling, and supporting statistical calculations in EDA.
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Seaborn The seaborn development teamUsed for quick statistical visualizations such as distributions, correlations, and category comparisons.
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Matplotlib Matplotlib development teamUsed to produce publication-ready charts and exploratory plots.
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Jupyter Notebook Project JupyterUsed for iterative analysis, visual inspection, and documenting EDA steps in a reproducible format.
Where this course runs
Exploratory Data Analysis (EDA) Training is delivered in the cities below — pick the one that fits your schedule.























