PGDip in AI-Driven Financial Analytics & Decision Science

About Course

Duration: 12 Months
Fees: N350,000
Format: Hybrid

This Postgraduate Diploma in AI-Driven Financial Analytics & Decision Science
is a one-year advanced programme designed to equip learners with technical,
analytical and strategic capabilities required to thrive in AI-enabled financial
environments.
The curriculum integrates machine learning, data science, econometrics,
behavioural finance, quantitative modelling, optimization techniques,
cloud-based analytics, and decision intelligence within financial contexts.
Learners engage in hands-on labs, industry datasets, algorithmic analysis,
financial modelling, and simulation-based decision-making. The programme
prepares graduates for roles in financial analytics, risk modelling, investment
analysis, corporate decision support, fintech product design, and AI-enhanced
financial strategy.

What Will You Learn?

Financial econometrics
Machine learning in finance
Optimization techniques
Deep learning for market prediction
Natural language processing for sentiment analysis
Cloud data analytics
Risk analytics & forecasting
Decision science modeling
Financial simulation systems
Ethical AI decision systems

Course Curriculum

Financial Systems, Instruments & Decision Environments
Market structures, corporate finance, risk-return principles, capital budgeting, portfolio theory.

Data Science & Statistical Foundations for Finance
Topics: Probability, statistics, hypothesis testing, regression, time-series analysis.

Machine Learning for Financial Analytics
Topics: Supervised/unsupervised learning, model evaluation, feature engineering, ensemble methods.

Advanced ML, Deep Learning & NLP in Finance
Topics: Neural networks, LSTMs, Transformers, NLP for sentiment and document analysis.

Econometrics, Forecasting & Quantitative Modelling
Topics: ARIMA, GARCH, multivariate models, high-frequency data analysis.

Optimization & Decision Science
Topics: Linear/non-linear optimization, decision trees, Monte Carlo simulation, reinforcement learning.

Data Engineering, Cloud Analytics & Big Data Systems
Topics: Data pipelines, ETL, data warehousing, cloud analytics (AWS/GCP/Azure), distributed computing.

Ethical, Regulatory & Governance Issues in AI-Driven Finance
Topics: AI ethics, fairness, transparency, regulatory compliance, finance-specific governance.

Innovation, Decision Intelligence & Strategic Leadership
Topics: Decision frameworks, behavioural finance, scenario planning, fintech strategy, innovation management.

Capstone Project Preparation & Research Methods
Topics: Research design, methodology, data sourcing, proposal writing, project ethics.

Your Instructors

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PGDip in AI-Driven Financial Analytics & Decision Science

About Course

What Will You Learn?

Course Curriculum

Financial Systems, Instruments & Decision Environments
Market structures, corporate finance, risk-return principles, capital budgeting, portfolio theory.

Data Science & Statistical Foundations for Finance
Topics: Probability, statistics, hypothesis testing, regression, time-series analysis.

Machine Learning for Financial Analytics
Topics: Supervised/unsupervised learning, model evaluation, feature engineering, ensemble methods.

Advanced ML, Deep Learning & NLP in Finance
Topics: Neural networks, LSTMs, Transformers, NLP for sentiment and document analysis.

Econometrics, Forecasting & Quantitative Modelling
Topics: ARIMA, GARCH, multivariate models, high-frequency data analysis.

Optimization & Decision Science
Topics: Linear/non-linear optimization, decision trees, Monte Carlo simulation, reinforcement learning.

Data Engineering, Cloud Analytics & Big Data Systems
Topics: Data pipelines, ETL, data warehousing, cloud analytics (AWS/GCP/Azure), distributed computing.

Ethical, Regulatory & Governance Issues in AI-Driven Finance
Topics: AI ethics, fairness, transparency, regulatory compliance, finance-specific governance.

Innovation, Decision Intelligence & Strategic Leadership
Topics: Decision frameworks, behavioural finance, scenario planning, fintech strategy, innovation management.

Capstone Project Preparation & Research Methods
Topics: Research design, methodology, data sourcing, proposal writing, project ethics.

Your Instructors

Hello There!

Information

Follow Us

About Course

What Will You Learn?

Course Curriculum

Financial Systems, Instruments & Decision Environments Market structures, corporate finance, risk-return principles, capital budgeting, portfolio theory.

Data Science & Statistical Foundations for Finance Topics: Probability, statistics, hypothesis testing, regression, time-series analysis.

Machine Learning for Financial Analytics Topics: Supervised/unsupervised learning, model evaluation, feature engineering, ensemble methods.

Advanced ML, Deep Learning & NLP in Finance Topics: Neural networks, LSTMs, Transformers, NLP for sentiment and document analysis.

Econometrics, Forecasting & Quantitative Modelling Topics: ARIMA, GARCH, multivariate models, high-frequency data analysis.

Optimization & Decision Science Topics: Linear/non-linear optimization, decision trees, Monte Carlo simulation, reinforcement learning.

Data Engineering, Cloud Analytics & Big Data Systems Topics: Data pipelines, ETL, data warehousing, cloud analytics (AWS/GCP/Azure), distributed computing.

Ethical, Regulatory & Governance Issues in AI-Driven Finance Topics: AI ethics, fairness, transparency, regulatory compliance, finance-specific governance.

Innovation, Decision Intelligence & Strategic Leadership Topics: Decision frameworks, behavioural finance, scenario planning, fintech strategy, innovation management.

Capstone Project Preparation & Research Methods Topics: Research design, methodology, data sourcing, proposal writing, project ethics.

Your Instructors

Ratings & Reviews

Financial Systems, Instruments & Decision Environments
Market structures, corporate finance, risk-return principles, capital budgeting, portfolio theory.

Data Science & Statistical Foundations for Finance
Topics: Probability, statistics, hypothesis testing, regression, time-series analysis.

Machine Learning for Financial Analytics
Topics: Supervised/unsupervised learning, model evaluation, feature engineering, ensemble methods.

Advanced ML, Deep Learning & NLP in Finance
Topics: Neural networks, LSTMs, Transformers, NLP for sentiment and document analysis.

Econometrics, Forecasting & Quantitative Modelling
Topics: ARIMA, GARCH, multivariate models, high-frequency data analysis.

Optimization & Decision Science
Topics: Linear/non-linear optimization, decision trees, Monte Carlo simulation, reinforcement learning.

Data Engineering, Cloud Analytics & Big Data Systems
Topics: Data pipelines, ETL, data warehousing, cloud analytics (AWS/GCP/Azure), distributed computing.

Ethical, Regulatory & Governance Issues in AI-Driven Finance
Topics: AI ethics, fairness, transparency, regulatory compliance, finance-specific governance.

Innovation, Decision Intelligence & Strategic Leadership
Topics: Decision frameworks, behavioural finance, scenario planning, fintech strategy, innovation management.

Capstone Project Preparation & Research Methods
Topics: Research design, methodology, data sourcing, proposal writing, project ethics.