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School of Data Science
Explore our comprehensive portfolio of professional programmes across Data Science Fundamentals, Data Analytics & Visualization, Machine Learning & AI, Big Data & Cloud Computing, Business Intelligence & Decision Science, Data Engineering & Architecture, Statistical Analysis & Modelling, Data Governance & Ethics, Predictive Analytics & Forecasting, and Data Science Leadership & Strategy. Designed for data professionals, analysts, scientists, and business leaders seeking practical, industry‑focused competencies for career advancement in data science.
Industry-Relevant Curriculum
Programmes designed in collaboration with data science professionals and industry experts to ensure practical, job-ready skills.
Global Recognition
Earn a respected professional qualification valued by employers in data analytics, AI, business intelligence, and data engineering worldwide.
Fast-Track Your Career
Complete programmes in 1–6 weeks with flexible online learning — upgrade your skills without career interruption.
Practical Focus
Develop practical competencies in data analytics, machine learning, big data, business intelligence, statistical modelling, and data leadership.
Ready to Enrol?
Choose your data science programme and take the next step in your data career.
Apply NowSchool of Data Science
A Specialist Professional Learning Division of Ransford Global Professional Development Ltd – advancing careers through practical, industry‑focused professional education in data science.
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Master Data Science from Beginner to Advanced
A progressive, expert-led suite of data science programmes – from Foundation Diploma to Advanced Professional Diploma. 100% online, hands-on projects, and real-world business applications. Master Python, Machine Learning, Deep Learning, NLP, Computer Vision, Big Data, and MLOps.
Designed for Data Science Excellence
Practical, project-based, and globally relevant – build a portfolio of data science projects while you learn from industry experts.
Comprehensive Data Science
Master the full data science pipeline – from data collection and cleaning to advanced machine learning and deployment.
Three Progressive Levels
Advance from Foundation to Professional and Advanced Professional Diploma, building your expertise step by step.
Learn by Doing
Complete practical exercises, real-world case studies, and end-to-end projects throughout the programme.
Machine Learning Mastery
Build regression, classification, and clustering models using scikit-learn and other ML libraries.
Deep Learning & AI
Master neural networks, TensorFlow, Keras, NLP, and Computer Vision for cutting-edge AI applications.
Big Data & Cloud Analytics
Work with large datasets using Apache Spark, cloud platforms, and distributed data processing.
MLOps & Deployment
Learn model deployment, monitoring, CI/CD, and Docker for production-ready AI applications.
Career-Focused Skills
Develop skills relevant to Data Scientist, Machine Learning Engineer, AI Specialist, and more.
Industry-Recognised Certification
Earn a verified diploma upon successful completion – blockchain-secured, globally recognised.
Foundation Diploma in Data Science
Build a strong foundation in data science. Master Python programming, NumPy, Pandas, data manipulation, exploratory data analysis, and data visualization with Matplotlib and Seaborn. Perfect for beginners with no prior data science experience.
Introduction to Data Science
Understand the field of data science, the data science lifecycle, data types and sources, and get started with Python and Jupyter Notebook.
- Unit 1: Introduction to Data Science
- Unit 2: Data Science Lifecycle
- Unit 3: Data Types and Sources
- Unit 4: Python for Data Science
- Unit 5: Jupyter Notebook Fundamentals
- Unit 6: First Data Science Project
Python Programming for Data Science
Master Python fundamentals – variables, data types, operators, conditional statements, loops, functions, and data structures.
- Unit 1: Variables and Data Types
- Unit 2: Operators and Expressions
- Unit 3: Conditional Statements
- Unit 4: Loops and Functions
- Unit 5: Lists, Tuples, Dictionaries, and Sets
- Unit 6: Python Programming Exercises
Data Manipulation with NumPy and Pandas
Learn NumPy for numerical computing and Pandas for data manipulation – Series, DataFrames, data import/export, and data cleaning.
- Unit 1: Introduction to NumPy
- Unit 2: Arrays and Numerical Operations
- Unit 3: Introduction to Pandas
- Unit 4: Series and DataFrames
- Unit 5: Data Import and Export
- Unit 6: Data Cleaning Fundamentals
Exploratory Data Analysis
Apply descriptive statistics, data cleaning, transformation, aggregation, grouping, and EDA techniques to understand and prepare data for analysis.
- Unit 1: Descriptive Statistics
- Unit 2: Data Cleaning and Preparation
- Unit 3: Data Transformation
- Unit 4: Data Aggregation and Grouping
- Unit 5: Exploratory Data Analysis Techniques
- Unit 6: EDA Mini Project
Data Visualization
Create professional visualizations using Matplotlib and Seaborn – bar charts, line charts, pie charts, histograms, box plots, and correlation heatmaps.
- Unit 1: Introduction to Matplotlib
- Unit 2: Data Visualization with Seaborn
- Unit 3: Bar, Line, and Pie Charts
- Unit 4: Histograms and Box Plots
- Unit 5: Correlation Heatmaps
- Unit 6: Visualization Project
Foundation Data Science Project
Apply all your foundation skills to a complete data science project – from problem definition to data collection, preparation, analysis, visualization, and reporting.
- Unit 1: Business Problem Definition
- Unit 2: Data Collection
- Unit 3: Data Preparation
- Unit 4: Data Analysis
- Unit 5: Visualization and Reporting
- Unit 6: Foundation Capstone Project
Upon completion, earn a verified Foundation Diploma in Data Science – blockchain‑secured, globally recognised.
Professional Diploma in Data Science
Take your data science skills to the next level. Master statistics for data science, machine learning fundamentals, regression and classification, feature engineering, SQL and data management, and deliver a professional capstone project.
Statistics for Data Science
Apply statistical methods – probability, descriptive statistics, inferential statistics, probability distributions, and hypothesis testing.
- Unit 1: Probability Fundamentals
- Unit 2: Descriptive Statistics
- Unit 3: Inferential Statistics
- Unit 4: Probability Distributions
- Unit 5: Hypothesis Testing
- Unit 6: Statistical Analysis Project
Machine Learning Fundamentals
Understand the core concepts of machine learning – supervised and unsupervised learning, model training, and model evaluation.
- Unit 1: Introduction to Machine Learning
- Unit 2: Supervised Learning
- Unit 3: Unsupervised Learning
- Unit 4: Model Training
- Unit 5: Model Evaluation
- Unit 6: Machine Learning Project
Regression and Classification
Build predictive models using linear regression, logistic regression, decision trees, random forest, and K-nearest neighbors.
- Unit 1: Linear Regression
- Unit 2: Logistic Regression
- Unit 3: Decision Trees
- Unit 4: Random Forest
- Unit 5: K-Nearest Neighbors
- Unit 6: Predictive Modeling Project
Feature Engineering and Model Optimization
Master feature selection, feature engineering, cross-validation, hyperparameter tuning, and model performance evaluation.
- Unit 1: Feature Selection
- Unit 2: Feature Engineering
- Unit 3: Cross Validation
- Unit 4: Hyperparameter Tuning
- Unit 5: Model Performance Evaluation
- Unit 6: Model Optimization Project
SQL and Data Management
Learn SQL fundamentals, database design, data retrieval, and integrate databases with Python for analytics projects.
- Unit 1: SQL Fundamentals
- Unit 2: Database Design
- Unit 3: Data Retrieval with SQL
- Unit 4: SQL with Python
- Unit 5: Database Integration
- Unit 6: Database Analytics Project
Professional Data Science Project
Apply all your professional skills to a complete data science project – from data collection and cleaning to machine learning model development, evaluation, and business recommendations.
- Unit 1: Data Collection
- Unit 2: Data Cleaning
- Unit 3: Machine Learning Model Development
- Unit 4: Model Evaluation
- Unit 5: Business Recommendations
- Unit 6: Professional Capstone Project
Upon completion, earn a verified Professional Diploma in Data Science – blockchain‑secured, globally recognised.
Advanced Professional Diploma in Data Science
Reach expert-level proficiency in data science. Master deep learning, natural language processing, computer vision, big data and cloud analytics, MLOps and AI deployment, and deliver an enterprise data science capstone project.
Deep Learning
Master artificial neural networks, TensorFlow, Keras, and model optimization for cutting-edge deep learning applications.
- Unit 1: Introduction to Deep Learning
- Unit 2: Artificial Neural Networks
- Unit 3: TensorFlow Fundamentals
- Unit 4: Keras Framework
- Unit 5: Model Optimization
- Unit 6: Deep Learning Project
Natural Language Processing (NLP)
Learn text preprocessing, sentiment analysis, text classification, and language models for NLP applications.
- Unit 1: Introduction to NLP
- Unit 2: Text Preprocessing
- Unit 3: Sentiment Analysis
- Unit 4: Text Classification
- Unit 5: Language Models
- Unit 6: NLP Project
Computer Vision
Master image processing, image classification, object detection, convolutional neural networks, and transfer learning for computer vision.
- Unit 1: Image Processing Fundamentals
- Unit 2: Image Classification
- Unit 3: Object Detection
- Unit 4: Convolutional Neural Networks
- Unit 5: Transfer Learning
- Unit 6: Computer Vision Project
Big Data and Cloud Analytics
Work with large datasets using Apache Spark, cloud data platforms, distributed data processing, and build data pipelines.
- Unit 1: Introduction to Big Data
- Unit 2: Apache Spark Fundamentals
- Unit 3: Cloud Data Platforms
- Unit 4: Distributed Data Processing
- Unit 5: Data Pipelines
- Unit 6: Big Data Project
MLOps and AI Deployment
Learn model deployment, monitoring, Docker for AI applications, and CI/CD for machine learning to productionise AI solutions.
- Unit 1: Introduction to MLOps
- Unit 2: Model Deployment
- Unit 3: Model Monitoring
- Unit 4: Docker for AI Applications
- Unit 5: CI/CD for Machine Learning
- Unit 6: AI Deployment Project
Enterprise Data Science Capstone
Integrate all your advanced skills to deliver an end-to-end enterprise data science solution – from business problem analysis to deployment and executive presentation.
- Unit 1: Business Problem Analysis
- Unit 2: Data Acquisition and Engineering
- Unit 3: Advanced Machine Learning Solution
- Unit 4: Model Deployment
- Unit 5: Executive Presentation and Documentation
- Unit 6: Enterprise Data Science Capstone Project
Upon completion, earn a verified Advanced Professional Diploma in Data Science – blockchain‑secured, globally recognised.
Roles You Can Pursue with Data Science Skills
Develop practical, job-ready data science skills that are highly sought after across technology, finance, healthcare, e-commerce, government, and research sectors.
What Data Science Graduates Say
"The Foundation Diploma gave me the confidence to start my data science journey. The NumPy and Pandas modules were outstanding."
— Adesola O., Nigeria
"The Professional Diploma transformed my understanding of machine learning. I now build predictive models for my organisation with confidence."
— James O., Nigeria
"The Advanced Professional Diploma prepared me for senior AI roles. Deep Learning and MLOps have opened doors to cutting-edge projects."
— Aisha A., Nigeria
Affordable Tuition for Local & International Students
All inclusive: tuition + application fee. Flexible interest‑free instalments available.
Application fee ₦8,220 is included in the total above.
Application fee ₦8,220 is included in the total above.
Unlock the Power of Data Science
Choose your level – Foundation, Professional, or Advanced Professional Diploma. Build real-world projects, earn verifiable credentials, and advance your career in AI and data science.
Questions About Our Data Science Programmes?
Our admissions team is ready to discuss prerequisites, curriculum, and which programme fits your career goals.
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