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Technology track

Data Science internship

Answer business questions with statistics and machine learning. Courses from SkillTank Academy, live tasks reviewed by KaizenSpark Tech mentors.

Apply for Data Science Programmes & fees

Prerequisites

Python basics
School-level statistics

Tools you’ll use

PythonPandasscikit-learnJupyter

Roles it prepares you for

Data science intern
Data analyst
ML intern

Syllabus

The Data Science track, week by week.

Shown for the 3-month internship. The 1-month internship covers the first phase in depth; the 6-month internship extends each phase with a specialisation course and module ownership.

Weeks 1–2 · Foundations

Python, NumPy and Pandas
Descriptive statistics
Data cleaning

Weeks 3–6 · Build

Hypothesis testing
Feature engineering
Visualisation

Weeks 7–10 · Own

Regression and classification
Model validation
Interpreting models

Weeks 11–12 · Graduate

Business recommendation
Notebook to report
Presentation

Deliverables

What you’ll hand in.

Every deliverable is reviewed and rated on the 1–5 quality rubric, and approved work is added to your record.

A cleaned and documented dataset
A validated predictive model
A findings report with recommendations

Competencies assessed

Statistics and hypothesis testing
Feature engineering
Predictive modelling
Communicating findings

Sample project

Analyse a real dataset end to end and present a predictive model with its business impact.

Apply for the Data Science track.

Choose your programme level on the form. We confirm your track after a short interview.