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Data engineering & AI · Corporate training

Data analysis with Python

Clean, explore, and communicate data with Python's analytics and visualization tools.

  • Intermediate
  • Live online and in person
  • Duration tailored to your team
Discuss this trainingExplore sample curriculum ↓

Sample curriculum

What your team can learn.

This outline is a starting point. Modules, exercises, and depth are adapted to your team's experience and project requirements.

01Working with datasets
  • Arrays and numerical operations with NumPy
  • Pandas series and dataframes
  • Importing CSV, spreadsheet, and database data
02Cleaning & transformation
  • Missing values and duplicate records
  • Type conversion and date handling
  • Merging, reshaping, and grouped operations
03Exploration & visualization
  • Summary statistics and distributions
  • Charts with Matplotlib and Seaborn
  • Comparisons, relationships, and misleading visuals
04Reproducible analysis
  • Organizing notebooks and reusable functions
  • Validating results and documenting assumptions
  • Communicating findings and limitations

Hands-on capstone

Put the learning into practice.

Analyze a sample business dataset and present a reproducible notebook with visual findings and limitations.

How the training works

Live demonstrations, guided exercises, pair work, and project reviews connect the concepts to practical implementation.

We agree on your learning goals, prerequisites, group size, delivery format, and schedule before shaping the final curriculum and proposal.

Your trainer

I'm Ragav Kumar V, a corporate trainer and mentor with 10+ years of training experience since 2016, 100+ batches delivered, and 3,000+ professionals trained across full-stack development, data engineering, and Cloud & DevOps.

Continue your learning path.