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 | 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
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 Malaysia
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 for data cleaning, profiling, summary statistics, and exploratory visualization workflows.
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Pandas The Pandas Development TeamUsed to inspect tables, handle missing values, reshape datasets, and generate profiling outputs.
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NumPy NumPy DevelopersUsed for numerical operations, array handling, and efficient computation during analysis.
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Seaborn Seaborn DevelopersUsed to create statistical graphics such as distribution plots, box plots, and correlation visuals.
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Matplotlib Matplotlib Development TeamUsed to build custom charts and presentation-ready visualizations for reporting.
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Jupyter Notebook Project JupyterUsed to combine analysis, code, and narrative documentation in a reproducible workflow.
Where this course runs
Exploratory Data Analysis (EDA) Training is delivered in the cities below — pick the one that fits your schedule.
