Data Science Foundations
Learn how machine learning models actually work, train them on Nigerian datasets, and deploy them as APIs — all in 16 weeks of live, hands-on instruction.
Full payment · Secured by Paystack
What you'll learn
Understand the mathematics and intuition behind ML models
Build regression, classification, and clustering models
Work confidently with pandas, NumPy, and scikit-learn
Train models on real Nigerian economic and financial datasets
Evaluate and tune models: AUC-ROC, GridSearchCV, cross-validation
Deploy a trained model as a live Flask API
Graduate with three end-to-end ML portfolio projects
Target data scientist and ML engineer roles at top companies
Course curriculum
Python for Data Science Refresher
- NumPy arrays and vectorised operations
- pandas: advanced indexing, groupby, merging
- Data wrangling with real-world messy datasets
- Setting up a reproducible project environment
Exploratory Data Analysis
- Statistical thinking: distributions, skew, outliers
- Correlation analysis and feature relationships
- Visualisations with seaborn and Plotly
- EDA on Nigerian housing price dataset
Supervised Learning I
- Linear regression: OLS, gradient descent intuition
- Logistic regression and the sigmoid function
- Train/test splits and holdout evaluation
- Feature engineering and normalisation
Supervised Learning II
- Decision trees: how they split and overfit
- Random forests and ensemble methods
- Bias-variance tradeoff in practice
- Project: loan default prediction model
Unsupervised Learning
- K-means clustering: the algorithm and its limits
- Principal Component Analysis (PCA)
- Anomaly detection for fraud use cases
- Customer segmentation project
Model Evaluation & Tuning
- Confusion matrices, precision, recall, F1
- AUC-ROC curves and threshold selection
- Cross-validation strategies
- GridSearchCV and RandomisedSearchCV
Real-World Projects
- Nigerian housing price prediction (regression)
- Loan default classification (bank dataset)
- Peer code review and iteration
- Writing a project README for GitHub
Model Deployment
- Saving models with joblib and pickle
- Building a prediction endpoint with Flask
- Deploying to Render (free tier)
- Intro to CI/CD with GitHub Actions
Capstone Presentations
- 10-minute live demo to an industry panel
- Q&A with working data scientists
- Portfolio and LinkedIn review session
- Certificate issued on successful presentation
Your instructor
Emeka Ibeanusi
ML Engineer at Paystack · MSc Computer Science (Ibadan)
Emeka builds the fraud detection systems used by millions of Paystack merchants. He holds an MSc in Computer Science from the University of Ibadan and has spoken at PyCon Africa on applying ML to African financial markets.
Frequently asked questions
What Python knowledge do I need before starting?+
You should be comfortable with Python basics — variables, loops, functions, and working with lists and dictionaries. If you're unsure, take Python for Beginners first.
Is there a lot of maths involved?+
Yes, but we teach the intuition before the equations. You don't need a maths degree. You need curiosity and the willingness to ask questions. We go at a pace that works for the cohort.
Will we work on Nigerian datasets specifically?+
Every project uses real Nigerian data: real estate prices, fintech transaction records, and economic indicators. The problems feel familiar, which dramatically accelerates learning.
How is this different from a free YouTube course?+
Live instruction, code review, human feedback on every assignment, and a cohort of people going through it alongside you. That combination of accountability and community is nearly impossible to replicate on your own.
Do I get a certificate?+
Yes. A verifiable Oak Forge Academy certificate is issued after your capstone presentation in Week 16.
How does payment work?+
This course is full payment upfront at ₦350,000 via Paystack. The monthly school-fee plan becomes available on programs priced at ₦300,000 and above — which includes our advanced full-school programmes launching later in 2025.
Will this course prepare me for roles at Nigerian companies?+
That's the explicit goal. The capstone panel includes working data scientists from Nigerian tech companies. Graduates have gone on to roles at Paystack, Interswitch, and several Series A startups.
Ready to start Data Science Foundations?
First 30 students lock in early-bird pricing. After that — full price, no exceptions.
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