AI & Data

Data Science

Learn to ask better questions of data, build reproducible analyses and evaluate machine learning models.

Beginner → IntermediateClassroom / Live · availability pending

A clear learning outcome.

Learn to ask better questions of data, build reproducible analyses and evaluate machine learning models.

Who should join

Students starting programming or strengthening their fundamentals.

What you’ll learn

Use Python tools to work with structured data.
Collect and query data for a defined question.
Describe patterns and limitations in a dataset.
Measure model performance with appropriate evaluation.
Communicate findings, uncertainty and next steps.

Technologies & concepts

PythonPandasSQLscikit-learn

Inside the syllabus.

Suggested syllabus for academic review. Module allocations are illustrative; confirm the current batch curriculum and total duration before enrolling.

MODULE 01
Python & data toolsSuggested allocation: 3–4 sessions

Python foundations
Git
NumPy
Pandas
Notebooks

Assignment / build: Analyze and transform a tabular dataset.

Learning outcome: Use Python tools to work with structured data.

MODULE 02
SQL & data acquisitionSuggested allocation: 3–4 sessions

SQL queries
Joins
Aggregations
CSV and JSON
APIs
Data quality

Assignment / build: Combine database and API data into one dataset.

Learning outcome: Collect and query data for a defined question.

MODULE 03
Analysis & statisticsSuggested allocation: 3–4 sessions

Cleaning
Exploratory analysis
Visualization
Descriptive statistics
Probability
Sampling

Assignment / build: Write an exploratory report with visual evidence.

Learning outcome: Describe patterns and limitations in a dataset.

MODULE 04
Machine learning foundationsSuggested allocation: 3–4 sessions

Regression
Classification
Trees
Train/test splits
Cross-validation
Metrics
Leakage

Assignment / build: Evaluate baseline and candidate predictive models.

Learning outcome: Measure model performance with appropriate evaluation.

MODULE 05
Data science capstoneSuggested allocation: 3–4 sessions

Feature engineering
Error analysis
Reproducibility
Communication
Responsible data use

Assignment / build: Present an end-to-end analysis and modeling project.

Learning outcome: Communicate findings, uncertainty and next steps.

Build something worth discussing.

Exploratory data report

A suggested project direction. Your mentor will confirm scope and review criteria.

Predictive modeling project

A suggested project direction. Your mentor will confirm scope and review criteria.

UP TO100%SCHOLARSHIP

CAST · YOUR OPPORTUNITY TO LEARN

Your ambition. A scholarship to match.

Apply for CAST — the Coding Blocks Aptitude and Scholarship Test — and earn a scholarship of up to 100% on course fees.

Available for classroom and Live interactive courses, including Sampoorna. Awards are subject to the test’s eligibility and award terms.

Apply for CAST

Your schedule. Your batch.

No upcoming batches

No batches are currently listed for this course. Enquire about the next intake.

Get the current schedule ↗

Learn. Practice. Build.

The suggested methodology connects concept sessions, exercises, reviewed assignments and a practical project. Confirm doubt support, recording availability and mock interview inclusions for your selected batch.

Career relevance

This pathway builds skills for project work and relevant technical discussions. Course completion alone does not guarantee an interview or employment outcome.

A little clarity

Good questions.
Clear answers.

Classroom or live: which learning mode is right for me?

Classroom learning suits students who prefer an in-person routine and peer interaction. Live learning suits those who need to attend remotely. Ask the advisor about center availability, schedules and support for your selected batch.

How long are the programs?

Duration depends on the course, batch and schedule. This source package leaves duration and dates open until the current batch information is confirmed.

Are there projects and doubt sessions?

Project ideas appear on each course page. Project scope, doubt-session format and availability must be confirmed against the selected batch curriculum and support policy.

Continue your journey

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Syllabus & projects insideView course ↗

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can start today.

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