Data Analytics with Python

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Data Analytics with Python

Course Category : Data Management

Develop practical expertise in Python-based data analytics to transform raw data into actionable insights through statistical analysis, visualisation, and data-driven decision-making.
Duration: 5 Days
Level: Intermediate – Advanced

Introduction

Modern organisations increasingly rely on data as a strategic asset for improving performance and supporting evidence-based decisions. The ability to analyse, interpret, and communicate data effectively has become a core competency across industries.
This course provides a comprehensive approach to data analytics using Python, covering data acquisition, preparation, exploratory analysis, statistical techniques, visualisation, and reporting to enable participants to convert raw datasets into meaningful business insights..

Targeted Audience

  • Data Analysts
  • Business Analysts
  • Junior Data Scientists
  • Software Developers
  • Data Engineers
  • Business Intelligence Professionals
  • Researchers and Academics
  • Anyone interested in Python Data Analytics

Targeted Skills

  • Python Data Analytics
  • Data Cleaning
  • Exploratory Data Analysis
  • Statistical Analysis
  • Data Visualisation
  • Data Manipulation
  • Analytical Reporting
  • Data Interpretation

Expected Outcomes

  • Analyse datasets efficiently using Python.
  • Prepare and clean datasets for analysis.
  • Perform exploratory and statistical analyses.
  • Create professional data visualisations.
  • Interpret analytical results for business decisions.
  • Work with multiple structured data formats.

Training Topics Index

  • Python analytical environment
  • Data structures
  • Importing datasets
  • Working with CSV, Excel, and JSON files
  • Analytical workspace setup

  • Handling missing values
  • Detecting outliers
  • Removing duplicate records
  • Data type conversion
  • Data integration and transformation

  • Descriptive statistics
  • Variable relationship analysis
  • Distribution analysis
  • Pattern identification
  • Correlation analysis

  • Charts and graphs
  • Statistical visualisations
  • Comparative analysis
  • Dashboard concepts
  • Professional presentation of findings

  • Multivariate analysis
  • Analytical reporting
  • Exporting analytical outputs
  • Data analytics best practices
  • Decision support using analytics

Course Features

  • Updated and Interactive Content
  • Hypothetical Examples and Case Studies
  • Pre- and Post-assessments to Measure Impact
  • Verified Certificate with a QR Verification Code