Data Science
Become a World-Class Data Scientist
Build predictive models that drive business decisions and power the future
Beginner Friendly
No prior experience required.
Job Pacement Support
Launch your career with internships and job placements.
Flexible Learning
Choose to learn at a pace that fits your schedule.
World-Class Tutors & Mentorship
Learn directly from industry experts.
Certificate
Earn a recognised certificate.
Course Overview
The Data Science course is designed to help students master how to collect, analyze, and interpret complex data to drive business and product decisions.
You’ll learn the full data science process — from data wrangling and exploratory analysis to building predictive models and communicating insights effectively.
This course combines statistics, programming, and practical projects, preparing you for in-demand roles in analytics, AI, and data-driven strategy across industries.
Learning Outcome
- Understand the key concepts and lifecycle of data science, from data collection to model deployment.
- Use tools such as Python, Pandas, NumPy, Matplotlib, and Jupyter Notebooks for data analysis and visualization.
- Apply statistical and machine learning techniques to solve real-world problems.
- Communicate findings effectively through visual storytelling and dashboards.
Career Opportunities
- United States – $85,000 – $120,000 USD
- United Kingdom – £50,000 – £75,000 GBP
- Canada – $70,000 – $95,000 CAD
- Germany – €55,000 – €80,000 EUR
- Nigeria – ₦5.5 million – ₦9 million NGN
- Kenya – KSh 2.2 million – KSh 3.8 million KES
- Remote/Global Roles – $60,000 – $100,000 USD
Career Pathways
- Data Scientist
- Machine Learning Engineer
- Data Analyst / Research Analyst
- Business Intelligence Developer
- AI Product Analyst
| Year | Average Global Salary (USD) |
|---|---|
| 2015 | $85,000 |
| 2016 | $90,000 |
| 2017 | $96,000 |
| 2018 | $103,000 |
| 2019 | $110,000 |
| 2020 | $118,000 |
| 2021 | $126,000 |
| 2022 | $133,000 |
| 2023 | $140,000 |
| 2024 | $148,000 |
What You Will Learn
Go from Idea to Impact, become a Data Scientist in 3-6 Months.
Module 1 - Python for Data Science
- Python Basics: Variables, Data Types, Loops, Conditionals
- Functions & Modules
- File Handling and Exception Handling
- Intro to NumPy Arrays
- Pandas: Reading, Filtering, Aggregation
- Handling Missing Values & Outliers
- Descriptive Statistics
- Visualization with Matplotlib
Module 2 - Data Visualization & Statistics
Advanced Visualization with Seaborn (histograms, boxplots, pairplots)
Correlation & Covariance
Probability Distributions
Hypothesis Testing & p-values
Mini Project: Statistical Insights from Consumer Dataset
Module 3 - Introduction to Machine Learning
- Supervised vs. Unsupervised Learning
- Linear Regression & Logistic Regression
- Train/Test Split & Evaluation Metrics (MAE, RMSE, Accuracy, Confusion Matrix)
- Mini Project: Predict House Prices or Loan Default
Module 4 - SQL & Supervised Learning
- SQL Basics: SELECT, WHERE, ORDER BY, LIMIT
- Joins (INNER, LEFT, RIGHT), GROUP BY, HAVING
- Subqueries and Aggregations
- Integrating SQL with Python (SQLite / SQLAlchemy)
- Mini Project: Query and Analyze Sales or Employee Dataset using SQL + Pandas
Module 5 - Decision Trees & Ensemble Learning
- Decision Trees & Random Forests
- Feature Importance and Cross-Validation
- Avoiding Overfitting
- Mini Project: Customer Churn Prediction
Module 6 - Classification & Model Evaluation
- KNN Classifier
- ROC, F1-Score, Precision-Recall Tradeoff
- Handling Imbalanced Classes (SMOTE, Class Weights)
- Mini Project: Fraud Detection or Medical Diagnosis
Module 7 - Feature Engineering & Hyperparameter Tuning
- Pipeline Creation (Scikit-learn)
- GridSearchCV / RandomizedSearchCV
- Bias-Variance Tradeoff
- Mini Project: Model Optimization Challenge
Module 8: Unsupervised Learning / Clustering
- K-Means & Hierarchical Clustering
- Elbow Method, Silhouette Score
- PCA for Dimensionality Reduction
- Activity: Market Segmentation Using Customer Data
Module 9: Time Series Analysis
- Time Series Components (Trend, Seasonality, Residuals)
- Lag Features & Rolling Statistics
- ARIMA Basics
- Activity: Sales or Stock Price Forecasting
Module 10: Model Deployment with Streamlit
- Model Serialization (Pickle / Joblib)
- Building Streamlit Dashboards
- Deploying Locally
- Activity: Deploy a Trained Model Locally
Module 11: Model Explainability & Ethics
- Feature Importance Visualization
- SHAP & LIME for Interpretability
- Ethical AI & Fairness
- Activity: Explainable Credit Risk Model
Module 12: Capstone Project
- Capstone Project Presentation
- GitHub Portfolio (Notebook, README, Visualizations)
- Optional: Deployed Streamlit App
Flexible and Affordable Payment
Frequently Asked Questions
I don’t have a tech background.
70% of our graduates started with zero tech experiences. Our beginner-friendly approach starts with basics and builds progressively
I can’t afford it
Up to 50-100% scholarship coverage available. You only pay registration and certification fees upfront.
I don't have time
Flexible learning schedules including evenings and weekends. Complete the program while maintaining your current job.
Will I actually get a job?
Guaranteed internship placement + access to exclusive job board with 500+ partner companies actively hiring our graduates
