Virtual Training
Data Science, AI, and Advanced Analytics
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.
5 Days
Duration
Live Online
Delivery
7 Dates
Available
Certificate
Included
Master Exploratory Data Analysis to uncover hidden patterns, validate data integrity, and drive evidence-based decision-making through advanced Python visualization and statistical profiling techniques.
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 | 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 | 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 → |
Here's What You'll Learn
Each module tackles real challenges you face in your role
1
Exploratory Data Analysis Foundations and Frameworks
2
Data Profiling and Initial Inspection
3
Univariate Analysis and Distribution Discovery
4
Bivariate Analysis and Relationship Mapping
5
Multivariate Interrogation and Dimensionality
6
Outlier Detection and Anomaly Management
7
Missing Data Strategies and Imputation
8
Feature Engineering and Data Transformation
9
Time-Series and Geospatial EDA
10
EDA Synthesis and Executive Reporting
Market-specific guidance for Hungary
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 for data wrangling, summary statistics, and reproducible EDA workflows.
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Pandas NumFOCUSUsed to clean, reshape, and profile tabular datasets before reporting.
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NumPy NumPy DevelopersUsed for numerical operations, array handling, and efficient data transformations.
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Seaborn Seaborn DevelopersUsed to create statistical graphics that reveal distributions, relationships, and outliers.
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Jupyter Notebook Project JupyterUsed to document exploratory analysis step by step and share results with stakeholders.
Where this course runs
Exploratory Data Analysis (EDA) Training is delivered in the cities below — pick the one that fits your schedule.
