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Technology track

AI / ML internship

Turn data into models that make decisions, including fraud detection. Courses from SkillTank Academy, live tasks reviewed by KaizenSpark Tech mentors.

Apply for AI / ML Programmes & fees

Prerequisites

Python basics
School-level statistics
Comfort with spreadsheets

Tools you’ll use

Pythonscikit-learnPyTorchJupyter

Roles it prepares you for

Machine learning intern
Data analyst
Junior data scientist

Syllabus

The AI / ML 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 for data: NumPy, Pandas
Data cleaning and exploratory analysis
Train / validation / test splits

Weeks 3–6 · Build

Classification and regression models
Feature engineering for tabular data
Class imbalance in fraud detection

Weeks 7–10 · Own

Evaluation: precision, recall, ROC-AUC
Threshold tuning against business cost
Model explainability basics

Weeks 11–12 · Graduate

Packaging a model for hand-off
Writing a model card
Presenting results to a non-technical reviewer

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, documented dataset
A tuned classification model with evaluation report
A model card and results presentation

Competencies assessed

Python, Pandas and NumPy
Supervised learning and evaluation
Feature engineering
Presenting model results

Sample project

Train a fraud-detection classifier on real transaction data and explain its precision–recall trade-offs.

Apply for the AI / ML track.

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