Data Science Bootcamp

Intensive, practical program aimed at equipping beginners with the skills to handle the full data science lifecycle.

About the course

Intensive, practical program aimed at equipping beginners with the skills to handle the full data science lifecycle. Delivered via asynchronous modules with live sessions, mentorship calls, and group projects via AI-enhanced LMS, this intensive bootcamp requires a commitment of 20–40 hours per week. Non-accredited bootcamp. For formal qualification, see the Data Science Practitioner (NQF Level 5, SAQA ID: 118708). The course is designed to take you from a complete beginner to a job-ready professional.

Duration and Program Structure

Duration & Intensity

6 months intensive study.
Required effort: 20–40 hours per week.

Cohort Info

Max Seats: 20 seats per cohort.
Format: 100% Online learning with 1-on-1 mentorship.

Accreditation & Certificate

Non-accredited bootcamp. For formal qualification, see the Data Science Practitioner (NQF Level 5, SAQA ID: 118708).

Programme Curriculum

Phase 1: Foundation (Weeks 1–4)Data Fundamentals

Introduction to data science concepts and tools
Python basics
Data environment setup

Phase 2: Core Skills (Weeks 5–12)Data Manipulation & Visualisation

Data Wrangling & Preparation (Python, Pandas, NumPy, SQL)
Data Visualization & Storytelling (Tableau, Power BI, Matplotlib, Seaborn)
Exploratory Data Analysis (SciPy, StatsModels)

Phase 3: Advanced Application (Weeks 13–18)Machine Learning & Analytics

Machine Learning Basics (Scikit-learn, TensorFlow)
Supervised and unsupervised learning
Regression, classification, and clustering

Phase 4: Capstone & Portfolio (Weeks 19–24)Real-World Projects & Career Prep

End-to-end capstone projects
Full lifecycle: data ingestion to model deployment and reporting
AI prompt engineering and ethical data use
Portfolio and career preparation

Skills You'll Gain

Data Wrangling

Clean and organize datasets using Python, Pandas, and SQL.

Data Visualisation

Create compelling dashboards and reports using Tableau and Power BI.

Exploratory Analysis

Uncover patterns and insights using statistical methods and hypothesis testing.

Machine Learning

Build and deploy predictive models to solve real-world business problems.

Data Storytelling

Communicate data insights effectively to non-technical audiences.

Ethical AI Integration

Apply ethical considerations and AI prompt engineering in data workflows.

Career Outcomes

Data Scientist

Data Analyst

Business Intelligence Analyst

Data Practitioner

Applications close in:16:05:20

35 lessons

60 hours, 24 mins duration

234 students enrolled

Level: Advanced

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Payment plans available · Financed by Nedbank & Manati