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Course Details
Course Details
What You'll Learn
Topic 1: Introduction to AI and Agentic AI for Finance
- From Generative AI to Autonomous AI Agents
- How AI Agents Work: LLMs, Tools, Memory and Reasoning
- Agentic AI Use Cases Across the Finance Function
- Overview of AI Agent Platforms and No-Code Tools
- Data Privacy, Governance and Responsible AI in Finance
Topic 2: AI Agents for Financial Data and Analysis
- Extracting and Consolidating Financial Data with AI Agents
- Automating Financial Statement Analysis
- Ratio, Trend and Variance Analysis with AI Agents
- AI-Powered Market and Investment Research
- Human-in-the-Loop Review and Validation
Topic 3: Agentic Workflows for Financial Planning and Reporting
- Building Multi-Step Agentic Workflows
- Automating Budgeting and Forecasting with AI Agents
- Cash Flow Monitoring and Treasury Agents
- Automating Management Reports and Dashboards
- Connecting Agents to Spreadsheets and Finance Systems
Topic 4: Risk, Compliance and Deploying Finance AI Agents
- AI Agents for Risk Assessment and Monitoring
- Fraud and Anomaly Detection with AI Agents
- Compliance and Regulatory Checks with AI Agents
- Deploying, Supervising and Governing AI Agents
- Risks, Ethics and the Future of Agentic Finance
Course Info
Prerequisite
Basic Python and introductory data-analysis concepts are recommended; participants should be able to follow English-language training materials.
Software Requirement
You will need the following for this course:
- Python 3 – free
- Visual Studio Code – free
- Google Colab – free, runs in the browser with a Google account
Install and test the listed software before class. Confirm the required version and account or licence access in your joining instructions. Cloud and AI services may charge subscription or usage fees.
Hardware Requirement
Bring a Windows or Mac laptop supported by the listed software, with a working keyboard and sufficient storage for course exercises.
Bring your own computer and charger, with a reliable internet connection and permission to install the required software. For live online classes, also prepare a microphone or headset.
If you need help arranging a suitable device, contact us before the class to confirm availability.
Job Roles
Job Roles
- Aspiring Software Developer
- Data Analyst
- Web Developer
- Automation Engineer
- Data Scientist
- System Administrator
- Bioinformatics Specialist
- Research Scientist
- Finance Professional
- Machine Learning Enthusiast
- GIS (Geographic Information System) Specialist
- IT Consultant
- Network Engineer
- Database Administrator
- Tech Entrepreneur.
Trainers
Trainers
Dr. Muhammed Siraj is a cybersecurity specialist and academic with 15 years of experience, serving as Senior Lecturer in the Department of Informatics and Director of Graduate and Continuous Education at Academic City University in Accra. He holds a PhD in Security in Computing from Universiti Putra Malaysia, where his research focused on blockchain security, an MSc in Information and Communication Technology from Aalborg University in Denmark, and a degree from the University of Ghana. He is a licensed independent assessor with Ghana's Cyber Security Authority, holds leadership roles in national cybersecurity and privacy professional bodies, and is certified as a Certified Ethical Hacker (CEH), Computer Hacking Forensic Investigator (CHFI) and Certified Data Protection Supervisor (CDPS). Before joining Academic City, he served as Acting Director of ICT and Data Protection Supervisor at Wisconsin International University College. His expertise spans penetration testing, digital forensics, incident response, malware analysis, cryptography, cloud and IoT security, zero trust architecture, cyber threat intelligence, data protection, and governance, risk and compliance.
Dr. Siraj's research interests cover blockchain, cybersecurity, distributed computing, consensus protocols and machine learning, with published work on blockchain consensus security, smart-contract privacy preservation for sensitive records in the cloud, and new consensus mechanisms. This background gives him a distinctive perspective on artificial intelligence: as organisations adopt AI tools, agents and data-driven automation, he helps learners understand how to protect the data these systems depend on, recognise new attack surfaces, and put sound governance, privacy and access controls in place so that AI can be used safely and responsibly. In the classroom he connects technical practice with regulation, privacy and human factors, drawing on real-world security and data-protection cases to show how concepts apply in professional settings, and his experiential, hands-on teaching style has made him a trusted trainer for students and working professionals alike.
Agents that read numbers, reason about them and prepare reports sit at the centre of Dr. Alfred Ang's recent work. Dr. Ang is a full-stack AI developer, Agentic AI solution architect and corporate trainer, and serves as Chief Technology Officer of Tertiary Infotech Academy Pte Ltd, the Singapore training organisation behind Tertiary Courses. Building end to end, from front-end screens and back-end services to databases, cloud deployment and native mobile apps, Dr. Ang has produced several finance-related systems. An HR and accounting platform built in Next.js runs leave accrual, attendance, payroll with payslips and expense claims for the academy, with native iPhone and Android apps for approvals on the go. An ERP prototype on Next.js and Postgres routes purchase orders through human-in-the-loop approvals by email, Asana or Telegram and three-way matches invoices against orders and receipts. A stock analysis dashboard pairs live market charts with an n8n Telegram AI agent that gives Buy, Sell or Hold views, while an investment advisor chatbot answers enquiries through n8n workflows. Dr. Ang also built an inventory forecasting agent that runs on a local language model through Ollama, flags items under reorder thresholds and computes forecasts, and a travel expense tracker app that converts more than 30 currencies using live exchange rates. Together with the rest of a portfolio of more than 300 public repositories on GitHub, these projects show agentic AI applied to real financial workflows with proper controls. Each one keeps a person firmly in charge of the final decision.
AI for Finance reflects that experience of putting agents to work on financial data while keeping people accountable for the result. Dr. Ang begins with an introduction to AI and agentic AI for finance, explaining how agents plan, reason, use tools and act, and how that differs from simply asking a chatbot a question. The second topic applies AI agents to financial data and analysis: extracting figures from statements and invoices, reconciling records, analysing ratios and explaining variances in plain language. Learners then build agentic workflows for financial planning and reporting, such as preparing budget forecasts, generating cash-flow scenarios and drafting management commentary that a finance lead can review and approve. The final topic covers risk, compliance and deploying finance AI agents responsibly, including audit trails, data privacy, access controls, model errors and the approval checkpoints Dr. Ang builds into ERP and accounting systems. Teaching is practical and example-driven; every concept is demonstrated with realistic sample data, and learners complete exercises that mirror day-to-day tasks in accounting, financial planning and analysis, and treasury. Dr. Ang encourages learners to bring their own reporting pain points so the class can explore which parts suit automation and which should remain manual. Participants finish with working workflows, reusable prompts and a practical roadmap for introducing agentic AI in their finance team. Learners also discuss how to present AI-generated analysis to auditors and senior management. To see the finance agents and accounting tools behind this course, visit https://github.com/alfredang
Review
Customer Reviews (9)
- Excellent course Review by Course Participant/Trainee
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Very informative and interactive. The small class size meant we got a lot of personal attention. (Posted on 5/28/2026)1. Do you find the course meet your expectation? 2. Do you find the trainer knowledgeable in this subject? 3. How do you find the training environment - Good course materials Review by Course Participant/Trainee
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Excellent delivery and good balance between theory and practice. Learned a lot in a short time. (Posted on 6/3/2025)1. Do you find the course meet your expectation? 2. Do you find the trainer knowledgeable in this subject? 3. How do you find the training environment - Would attend again Review by Course Participant/Trainee
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Very informative and interactive. The small class size meant we got a lot of personal attention. (Posted on 5/11/2025)1. Do you find the course meet your expectation? 2. Do you find the trainer knowledgeable in this subject? 3. How do you find the training environment - Worth every cent Review by Course Participant/Trainee
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I found the course extremely useful and relevant to my job. Highly recommend it to others. (Posted on 3/25/2025)1. Do you find the course meet your expectation? 2. Do you find the trainer knowledgeable in this subject? 3. How do you find the training environment - Highly recommended Review by Course Participant/Trainee
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A very practical course. The trainer made a complex topic simple and enjoyable to learn. (Posted on 2/23/2025)1. Do you find the course meet your expectation? 2. Do you find the trainer knowledgeable in this subject? 3. How do you find the training environment
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