DataOn campusOnlineHybrid

Data Analytics with Python

Students clean a real public dataset, explore it with pandas, visualise what they find and present one clear, evidence-backed recommendation.

Batch size
40–150 students per batch
Delivery
On campus / Online / Hybrid
Audience
Students
Certificates
Included

Who it's for

Students from any engineering or science branch, and MBA / BBA analytics electives

Participants will be able to

  • Load, clean and reshape tabular data with pandas
  • Summarise data with grouping and aggregation
  • Choose the right chart for a question
  • Write SQL queries for common analysis tasks
  • Present findings as a short, defensible story

Agenda

Adjusted to your syllabus, batch and lab setup before the dates are fixed.

  1. 01

    Python for data

    • Notebooks
    • pandas DataFrames
    • Reading CSV and Excel files
  2. 02

    Cleaning and shaping

    • Missing values and duplicates
    • Types and dates
    • Joins and reshaping
  3. 03

    Exploration and visualisation

    • Group-by and aggregates
    • Distributions and trends
    • Charts with matplotlib and seaborn
  4. 04

    SQL for analysts

    • SELECT, WHERE, GROUP BY
    • Joins
    • Window functions in brief
  5. 05

    Case study

    • Team analysis of a public dataset
    • Five-minute findings presentation

What your institution receives

  • Participation certificate for every attendee
  • Notebook-based lab manual and datasets
  • Session recordings for online and hybrid delivery
  • Participation and assessment report for the department

What you'll need

  • No prior programming required; basic spreadsheet familiarity helps
  • One computer per student or per pair, or browser access to hosted notebooks

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Request a proposal

Bring this workshop to your campus

  • Discovery call within two working days
  • Written proposal with agenda and per-batch quote
  • Certificates and an outcomes report included

Request “Data Analytics with Python”

Share a few details and we'll send a tailored proposal with an agenda and a per-batch quote within three working days.

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