Data Science in Action
- Next start date : 15 September 2025
- Study Mode : Delivery: Hybrid (Johannesburg Campus + Virtual)
- Campuses : Johannesburg
Overview: From exploratory data analysis to building and deploying production-ready ML models, this programme equips learners with cutting-edge skills in Python, machine learning, and MLOps.
Programme Duration: 40 Weeks
Key Learning Outcomes
✔︎ Analyse and visualise data with Python, pandas, and matplotlib
✔︎ Build predictive models using ML and deep learning
✔︎ Deploy models using Flask, FastAPI, and CI/CD workflows
✔︎ Implement MLOps pipelines using MLflow and Kubeflow
Core Modules
| Module | Key Topics | Weeks |
| 1. Intro to Data Science | Python, Jupyter, statistics | 6 |
| 2. Machine Learning | Classification, regression, pipelines | 8 |
| 3. Deep Learning | Neural nets, CNNs, RNNs, PyTorch | 8 |
| 4. Data Engineering for DS | Pandas, preprocessing, DVC | 6 |
| 5. MLOps & Deployment | MLflow, Docker, CI/CD | 6 |
| 6. Cloud AI Platforms | SageMaker, Vertex AI | 6 |
Certification Pathways
| Certification | Body | Duration | Prerequisites |
| Azure Data Scientist | Microsoft | 6 weeks | Modules 1–6 |
| AWS ML Specialist | AWS | 6 weeks | Modules 1–6 |
| Databricks ML Associate | Databricks | 6 weeks | Modules 1–3 |
Capstone Experience
End-to-end fraud detection ML pipeline
Text classification and sentiment analysis system
Technology Stack
◉ Libraries: scikit-learn, PyTorch, TensorFlow
◉ Workflow: MLflow, DVC, Kubeflow
◉ Deployment: Flask, FastAPI, Docker
Career Acceleration
Roles:
Data Scientist (Avg. salary: R920k)
Machine Learning Engineer (Avg. salary: R1.15M)
Industry Demand: 41% growth in DS/ML roles (OECD 2024)
