Data Science with Python Course in Jaipur
Develop a practical data foundation using Python for analysis, visualization, statistics and introductory machine-learning workflows.
- Practical learning
- Project practice
- Jaipur
Data Science with Python
Build your foundation in Data Science with Python
Develop a practical data foundation using Python for analysis, visualization, statistics and introductory machine-learning workflows.
The legacy Data Science with Python page emphasized Python, analysis, visualization, statistics and machine-learning applications.
This migrated version turns that broad content into a staged learning path focused on practical data work rather than unsupported outcome claims.
Who can join?
Python learners moving into data science Students interested in analytics and machine learning Professionals who work with data and reporting Learners building a data project portfolio
Skills and tools
Course curriculum
Explore the learning outline below. Confirm the detailed syllabus and module coverage for your chosen batch with the course team.
Python for Data
Python refresher and data structures · Notebook-based workflow · Working with files and datasets
Data Analysis
Tabular data cleaning · Filtering, grouping and aggregation · Exploratory data analysis
Statistics & Visualization
Descriptive statistics · Distributions and relationships · Charts and data storytelling
Machine Learning Foundations
Supervised-learning concepts · Train/test workflow · Evaluation and overfitting fundamentals
Portfolio Project
Problem framing · Data preparation and analysis · Model or analytical output with clear reporting
Project practice ideas
Use these examples to discuss suitable practice work with your trainer.
Exploratory data analysis notebook
Use this as a practical project brief to plan, build, test and document your work.
Data cleaning project
Use this as a practical project brief to plan, build, test and document your work.
Visualization dashboard or report
Use this as a practical project brief to plan, build, test and document your work.
Introductory predictive model
Use this as a practical project brief to plan, build, test and document your work.
End-to-end data science capstone
Use this as a practical project brief to plan, build, test and document your work.
Frequently asked questions
Do I need Python before starting?
Basic Python helps, but the path can begin with a focused Python refresher for data work.
Is machine learning included?
Yes. The roadmap includes machine-learning foundations after analysis and statistics.
Will I work with real datasets?
The practical path is designed around dataset cleaning, exploration, visualization and project work.
Is this the same as a data analytics course?
There is overlap, but this path extends beyond analysis into statistics and introductory machine-learning concepts.
Who is this course for?
Python learners moving into data science Students interested in analytics and machine learning Professionals who work with data and reporting Learners building a data project portfolio
How can I confirm fees, duration and batch timings?
Contact Groot Academy for the current syllabus, fees, duration and available learning modes before enrolling. These details depend on the selected course and batch.