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Finance, Risk and Compliance

This specialization covers everything from financial automation and predictive analytics to fraud detection, risk modeling, wealth management, and regulatory technology (RegTech). Students gain expertise in tools like Feedzai, Power BI, and ComplyAdvantage, while learning how to manage financial workflows, optimize investment portfolios, and ensure audit-readiness in a data-driven, algorithmically regulated world.

FINANCE, RISK AND COMPLIANCE

Course Series

Explore our course series designed to help you build foundational and intermediate knowledge across key topics. Each course offers curated content tailored to different learning goals.

INTRODUCTORY COURSES

4 courses

  • Why take this course?

    This course introduces learners to Agentic AI - systems that go beyond passive response generation and instead act autonomously toward goals. In contrast to traditional AI tools, agentic systems can plan, make decisions, use external tools, and even reflect on their actions. Designed for learners who have already explored Generative AI, this course bridges the gap between using AI and designing AI-driven workflows that simulate autonomous behavior.
    Through hands-on projects and real-world examples, students will gain foundational knowledge in multi-step reasoning, task decomposition, tool integration, and memory - the building blocks of agentic systems. This course sets the stage for future industry-specific tracks in business, education, finance, and more.

    AI is evolving — and it's learning to take initiative. This course explores the next frontier: Agentic AI. Unlike basic chatbots or assistants, agentic systems can plan, act, and adapt to achieve goals. You’ll learn how these intelligent agents work, how to design them, and how they use tools, memory, and multi-step reasoning to function independently. Perfect for professionals, technologists, or innovators who want to go beyond using AI and start building with it. This course lays the foundation for advanced, industry-specific agentic AI training.

    What will you receive upon completion?

    Certificate of Completion, and Badge to use across Professional Platforms

    What will you learn each week?

    • Session 1: What is Agentic AI?

      • Definitions: Agents vs Assistants vs Tools

      • Agent architecture: Perception → Reasoning → Action

      • Task completion vs goal pursuit

      • Key frameworks: Auto-GPT, BabyAGI, LangChain agents, CrewAI

      • Demos: How agents differ from GenAI tools

      Session 2: Planning and Reasoning in Agents

      • Multi-step reasoning: from LLMs to planning agents

      • Task decomposition and sub-goal generation

      • Prompt-chaining vs autonomous reasoning

      • Case study: An AI that plans a marketing campaign or writes code

    • Session 3: Tool Use and Integration

      • Toolformer and beyond: how agents call APIs, search, use calculators

      • The agent “toolbelt”: defining and assigning tools

      • LLM + plugin architectures (LangChain, OpenAI functions, HuggingFace agents)

      • Hands-on: Design a simple agent to perform web search + summarize

      Session 4: Memory and Context

      • Short-term vs long-term memory in agents

      • Retrieval-augmented generation (RAG) and vector databases

      • Embeddings 101 and memory stores (Pinecone, FAISS)

      • Use case: AI assistant with persistent memory of a client or task

    • Session 5: Reflection and Self-Correction

      • Agentic loops and thinking steps (e.g., ReAct framework)

      • Iterative reasoning, retry logic, and error handling

      • Critic and planner roles in multi-agent systems

      • Use case: Agents that debug or revise their own outputs

      Session 6: Multi-Agent Collaboration

      • Autonomous teams: CrewAI, AutoGen, LangGraph

      • Roles and personas in agentic systems

      • Inter-agent communication

      • Use case: Agent team executes a content pipeline or workflow

    • Session 7: Limitations, Ethics, and Failure Modes

      • Over-reliance and hallucination in agentic behavior

      • Security, misuse, and safety concerns

      • Prompt injections, tool misuse, data privacy

      • Design principles for safe, bounded autonomy

      • What current agentic systems can’t do (yet)

      Session 8: Capstone Workshop — Design Your Own Agent

      • Choose a goal or workflow (e.g., research assistant, business analyst, personal concierge)

      • Define tools, memory, goals, roles

      • Create a prompt-based or low-code agent prototype

      • Demo and feedback: peer review + instructor insights

  • Why take this course?

    This hands-on, beginner-friendly course introduces learners to the fast-evolving field of prompt engineering - the art and science of communicating effectively with Generative AI. In just 24 hours, participants will learn how to craft prompts that produce better, more accurate, and more useful outputs from tools like ChatGPT, Claude, DALL-E, and others. Through real-world examples, interactive exercises, and guided experimentation, learners will gain practical skills to unlock the full potential of AI in creative, professional, and technical contexts.


    No technical or programming background is required - just curiosity and a willingness to experiment!

    Generative AI is powerful—if you know how to ask the right questions. This course teaches you how to speak the language of AI through effective prompt engineering. Over four weeks, you'll learn how to design, refine, and experiment with prompts to unlock smarter, more accurate, and more creative responses from GenAI tools like ChatGPT, Claude, and Midjourney. From writing and coding to design and customer service, prompt engineering is the skill that puts AI to work for you. Perfect for professionals, creators, educators, and anyone curious about working better with AI.

    What will you receive upon completion?

    Certificate of Completion, and Badge to use across Professional Platforms

    What will you learn each week?

    • Session 1: What is Generative AI? A Beginner’s Map

      • What is GenAI? Definitions and context

      • Evolution: From early AI to Generative AI

      • Examples in action: ChatGPT, DALL·E, Midjourney, GitHub Copilot, etc.

      • Real-world applications (business, education, art, software, etc.)

      • What GenAI can do today

      Session 2: How Generative AI Works — The Basics (No Math!)

      • What is a model? What is "training"?

      • Overview of LLMs, diffusion models, GANs, VAEs

      • Why GenAI seems smart (but isn’t conscious)

      • Tokens, prompts, hallucinations explained

      • Limitations of current models and where they break

    • Session 3: Exploring Text-Based GenAI (LLMs like ChatGPT, Claude, Gemini)

      • How LLMs generate language

      • Prompting basics: getting what you want

      • Use cases: summarization, writing, planning, coding

      • Prompt engineering basics and best practices

      • Limitations and risks of text-based GenAI

      Session 4: GenAI for Images, Audio, and Video

      • Overview of image generation tools (DALL·E, Midjourney, Stable Diffusion)

      • Basics of how image GenAI works (diffusion explained simply)

      • Intro to audio and music GenAI (e.g., Suno, ElevenLabs)

      • Video GenAI (e.g., Runway, Sora—emerging tools)

      • Demos and ethical considerations (deepfakes, misuse, bias)

    • Session 5: Real-World Use Cases and Tools

      • Business use: marketing, productivity, customer service

      • Education use: tutoring, writing support, personalized learning

      • Design, art, and creative content

      • GenAI in software development and automation

      • Demo of multi-modal GenAI tools (text+image, text+code)

      Session 6: What GenAI Can’t Do (Yet)

      • Understanding hallucination and misinformation

      • Reasoning, logic, and factual gaps

      • Biases and fairness in GenAI

      • Creativity vs replication: is GenAI truly creative?

      • The future: AGI vs narrow GenAI

    • Session 7: Ethics, Risks, and Responsible Use

      • Copyright and IP issues

      • Deepfakes, misinformation, and manipulation

      • AI safety and alignment challenges

      • Open vs closed-source models

      • Regulatory trends (Canada, EU, US, etc.)

      Session 8: Hands-On Workshop: Build Your Own GenAI Workflow

      • Choose a use case (content creation, customer response, design, etc.)

      • Hands-on with GenAI tools (text, image, audio)

      • Crafting effective prompts and refining results

      • Wrapping up: GenAI literacy for everyday use

      • Final Q&A and resources for continued learning

  • Why take this course?

    This 24-hour introductory course is designed for absolute beginners who want to understand Generative AI (GenAI) and how it is transforming industries. Through 8 engaging sessions, participants will explore how GenAI works, what it's good at (and what it isn't), and how to begin using GenAI tools in real-world scenarios. You’ll gain foundational knowledge of the technologies behind GenAI, including large language models (LLMs), image generation, and audio synthesis. We'll also discuss the risks,
    ethical concerns, and current limitations to using GenAI responsibly. By the end of the course, learners will be confident in using popular GenAI tools, understanding how they work under the hood, and recognizing their potential and boundaries in various applications.


    No prior technical knowledge is required.

    Unlock the power of Generative AI in just four weeks. This hands-on, beginner-friendly course will take you from zero to confident user by exploring how GenAI tools like ChatGPT, DALL·E, and others work—and how they’re being used across industries. Learn what GenAI can (and can’t) do, experiment with leading tools, and understand the ethical, legal, and societal implications of this rapidly evolving technology. Whether you're a business professional, educator, artist, or curious learner, this course offers practical skills and critical insights to help you navigate and apply GenAI effectively.

    What will you receive upon completion?

    Certificate of Completion, and Badge to use across Professional Platforms

    What will you learn each week?

    • Session 1: What is Generative AI? A Beginner’s Map

      • What is GenAI? Definitions and context

      • Evolution: From early AI to Generative AI

      • Examples in action: ChatGPT, DALL·E, Midjourney, GitHub Copilot, etc.

      • Real-world applications (business, education, art, software, etc.)

      • What GenAI can do today

      Session 2: How Generative AI Works — The Basics (No Math!)

      • What is a model? What is "training"?

      • Overview of LLMs, diffusion models, GANs, VAEs

      • Why GenAI seems smart (but isn’t conscious)

      • Tokens, prompts, hallucinations explained

      • Limitations of current models and where they break

    • Session 3: Exploring Text-Based GenAI (LLMs like ChatGPT, Claude, Gemini)

      • How LLMs generate language

      • Prompting basics: getting what you want

      • Use cases: summarization, writing, planning, coding

      • Prompt engineering basics and best practices

      • Limitations and risks of text-based GenAI

      Session 4: GenAI for Images, Audio, and Video

      • Overview of image generation tools (DALL·E, Midjourney, Stable Diffusion)

      • Basics of how image GenAI works (diffusion explained simply)

      • Intro to audio and music GenAI (e.g., Suno, ElevenLabs)

      • Video GenAI (e.g., Runway, Sora—emerging tools)

      • Demos and ethical considerations (deepfakes, misuse, bias)

    • Session 5: Real-World Use Cases and Tools

      • Business use: marketing, productivity, customer service

      • Education use: tutoring, writing support, personalized learning

      • Design, art, and creative content

      • GenAI in software development and automation

      • Demo of multi-modal GenAI tools (text+image, text+code)

      Session 6: What GenAI Can’t Do (Yet)

      • Understanding hallucination and misinformation

      • Reasoning, logic, and factual gaps

      • Biases and fairness in GenAI

      • Creativity vs replication: is GenAI truly creative?

      • The future: AGI vs narrow GenAI

    • Session 7: Ethics, Risks, and Responsible Use

      • Copyright and IP issues

      • Deepfakes, misinformation, and manipulation

      • AI safety and alignment challenges

      • Open vs closed-source models

      • Regulatory trends (Canada, EU, US, etc.)

      Session 8: Hands-On Workshop: Build Your Own GenAI Workflow

      • Choose a use case (content creation, customer response, design, etc.)

      • Hands-on with GenAI tools (text, image, audio)

      • Crafting effective prompts and refining results

      • Wrapping up: GenAI literacy for everyday use

      • Final Q&A and resources for continued learning

  • Why take this course?

    This 24-hour introductory course offers a hands-on, non-technical introduction to the most impactful AI tools available today. Designed for curious beginners from any background, the course showcases real-world applications of AI in writing, image creation, productivity, communication, data analysis, and more. Through guided demos and hands-on practice, learners will discover how to use AI tools to boost creativity, improve efficiency, and solve everyday problems - no programming required. By the end of the course, participants will understand the capabilities, limitations, and best uses of today’s most promising AI tools, and feel empowered to start using them in their personal and professional lives.

    AI is no longer just for coders and data scientists—it’s for everyone. This beginner-friendly course introduces you to today’s most powerful and accessible AI tools, from ChatGPT to Canva AI, and shows you how to use them to write faster, design smarter, automate tasks, create content, and more. Learn by doing through real-world demos and hands-on challenges as you build your own custom AI toolkit. Whether you're a professional, student, entrepreneur, or just curious, this course will show you what’s possible when AI works with you.

    What will you receive upon completion?

    Certificate of Completion, and Badge to use across Professional Platforms

    What will you learn each week?

    • Session 1: Welcome to the AI Tool Ecosystem

      • What are AI tools and why are they everywhere now?

      • Categories of AI tools: text, images, audio, video, productivity, etc.

      • Core concepts: Generative AI, automation, personalization

      • Intro to foundational tools: ChatGPT, DALL·E, Grammarly, Notion AI

      • Hands-on: Try your first AI-assisted task

      Session 2: Text-Based Tools and Assistants

      • ChatGPT, Claude, Gemini: what they can do and how they differ

      • Writing support: GrammarlyGO, Jasper, Notion AI

      • Email, reports, summarization, translation, and rewriting

      • Hands-on: Crafting prompts and workflows for writing tasks 

    • Session 3: Visual AI: From Images to Design

      • Image generators: DALL·E, Canva AI, Adobe Firefly

      • Design help: Layout suggestions, branding ideas, social media content

      • Practical uses: marketing, personal branding, storytelling

      • Hands-on: Create custom visuals with AI

      Session 4: Audio, Video, and Voice AI Tools

      • Voice AI: ElevenLabs, Descript

      • Music generation: Suno AI, Soundraw

      • Video tools: Synthesia, Runway, Pictory

      • Use cases: explainer videos, training, podcasts, voiceovers

      • Hands-on: Generate a short video or podcast clip

    • Session 5: AI Tools for Productivity & Automation

      • Notion AI, Microsoft Copilot, Google Duet, Superhuman

      • Meeting transcription: Otter.ai, Fireflies

      • Scheduling, brainstorming, note-taking, content planning

      • Hands-on: Build a personal productivity stack with AI

      Session 6: AI for Data and Research

      • Tools: ChatGPT (with data plugins), Perplexity AI, Browse AI

      • AI search and research assistants

      • Visualizing data with AI: ChatGPT + charts, Power BI integrations

      • Hands-on: Use AI to analyze or summarize a dataset or research topic

    • Session 7: Responsible Use and Tool Comparison

      • AI hallucination and fact-checking

      • Privacy, data ownership, copyright

      • Free vs paid tools: what’s worth it?

      • Tool longevity and choosing sustainable platforms

      • Hands-on: Compare tool results for the same task

      Session 8: Build Your Own AI Toolkit (Capstone Workshop)

      • Pick your domain: business, education, content creation, etc.

      • Identify useful tools for your goals

      • Build a repeatable AI-powered workflow

      • Final showcase: present your personalized AI toolkit

APPLIED 
COURSES

6 courses

  • Why take this course?

    This 24-hour introductory course explores how AI-driven technologies are transforming financial services, risk management, and regulatory compliance. Designed for business professionals, analysts, and operations managers, the course introduces key AI tools used in finance to streamline processes, enhance accuracy, reduce fraud, and support data-driven decision-making. Through hands-on experience and real-world use cases, students will develop foundational knowledge of AI-enabled financial ecosystems.

    Discover how intelligent tools are reshaping finance. From automating reports to detecting fraud in real time, this course introduces the next-generation platforms driving smarter decisions and regulatory confidence. No programming experience needed – just curiosity and a commitment to innovation.

    What will you receive upon completion?

    Certificate of Completion, and Badge to use across Professional Platforms

    What will you learn each week?

    • Session 1: AI in Financial Services – An Industry Overview

      • Evolution of AI in banking, insurance, and asset management

      • Challenges in finance: accuracy, speed, security, compliance

      • Categories of tools: predictive analytics, automation, NLP, RPA

      • Case studies: JP Morgan COIN, PayPal fraud systems, Klarna credit scoring

      Session 2: Core Tool Categories and Key Platforms

      • Predictive analytics tools (DataRobot, Alteryx)

      • RPA platforms (UiPath, Automation Anywhere)

      • Document intelligence (Hyperscience, Kira Systems)

      • Hands-on: Map tools to common finance tasks (e.g., invoice processing, report generation)

    • Session 3: Financial Data Processing and Reporting Automation

      • Automating financial statements, KPI dashboards, variance analysis

      • Tools: Microsoft Power BI, Rows, Tableau with AI plugins

      • Hands-on: Automate a month-end financial report using templates and AI assistance

      Session 4: Risk Modeling and Fraud Detection

      • AI approaches to risk: pattern recognition, scoring systems, real-time alerts

      • Tools: Feedzai, Darktrace, Scikit-learn-based models

      • Hands-on: Simulate a transaction dataset and apply basic fraud flagging logic

    • Session 5: Compliance Monitoring and Document Review

      • Automating audits, KYC/AML processes, policy flagging

      • Tools: ComplyAdvantage, Alloy, RegTech platforms

      • Hands-on: Use an AI tool to extract key compliance issues from sample policy documents

      Session 6: Natural Language Processing for Finance

      • NLP use cases: earnings call analysis, policy review, financial chatbot assistants

      • Tools: ChatGPT, BloombergGPT, AlphaSense

      • Hands-on: Query an earnings call transcript for insights using AI search

    • Session 7: Ethics, Bias, and Responsible Use in Financial AI

      • Algorithmic bias in credit and underwriting

      • Transparency, fairness, and explainability

      • Industry regulations and governance frameworks (e.g., GDPR, FRTB)

      Session 8: Capstone Activity – AI-Enhanced Financial Operations Scenario

      • Choose a scenario: fraud detection, reporting automation, or compliance audit

      • Use tools covered to build a prototype workflow

      • Peer feedback and discussion

  • Why take this course?

    This 24-hour intermediate course focuses on AI-powered tools that automate financial workflows and improve reporting accuracy. Participants will learn how to build end-to-end automation pipelines for transaction processing, reconciliation, budgeting, and report generation. The course emphasizes hands-on application using popular AI tools and real-world case studies to highlight efficiency, scalability, and compliance.

    Manual finance is outdated. This course teaches you how to automate financial workflows and reporting systems using intelligent tools that work faster, smarter, and around the clock. Gain real-world skills in dashboards, reconciliations, and dynamic budget modeling—without a single line of code.

    What will you receive upon completion?

    Certificate of Completion, and Badge to use across Professional Platforms

    What will you learn each week?

    • Session 1: Automating Routine Finance Operations

      • Invoice processing and payment workflows

      • Vendor onboarding and approval flows

      • Tools: Tipalti, DocuPhase, Zoho Flow

      • Hands-on: Build an automated accounts payable workflow

      Session 2: Intelligent Reconciliation and Error Detection

      • Transaction matching and ledger reconciliation

      • Identifying anomalies and duplicate entries

      • Tools: BlackLine, HighRadius, Excel AI integrations

      • Hands-on: Automate bank reconciliation from multiple data sources

    • Session 3: Budgeting and Forecasting with AI Assistance

      • Scenario-based budget modeling and version control

      • Rolling forecasts and adaptive planning

      • Tools: Anaplan, Workday Adaptive Planning, Cube

      • Hands-on: Create a dynamic budget template powered by forecasting algorithms

      Session 4: Building Financial Reports with Automation Tools

      • Automating income statements, balance sheets, and variance reports

      • Real-time financial dashboards for stakeholders

      • Tools: Power BI, Tableau, Rows

      • Hands-on: Generate and schedule delivery of AI-assisted financial reports

    • Session 5: Financial Workflow Integration Across Systems

      • Connecting accounting systems (e.g., QuickBooks, Xero) to AI tools

      • API integration strategies for finance tools

      • Hands-on: Integrate a workflow between QuickBooks and Power BI

      Session 6: Audit Trails and System Logging in Automation

      • Ensuring traceability and audit compliance in automated workflows

      • Building secure and transparent logs for regulators

      • Tools: UiPath, Smartsheet, Power Automate

      • Hands-on: Design an audit-compliant financial workflow

    • Session 7: Risk and Oversight in Workflow Automation

      • Mitigating automation failures and financial exposure

      • Human-in-the-loop and approval structures

      • Governance policies for scalable financial automation

      Session 8: Capstone Project – Automate a Financial Workflow Scenario

      • Choose from budgeting, reconciliation, or reporting use cases

      • Build and demo a fully automated workflow

      • Peer review and performance reflection

  • Why take this course?

    ​This 24-hour intermediate course focuses on how AI tools are transforming fraud prevention and risk analysis in financial services. Students will explore various data-driven techniques including machine learning, anomaly detection, and real-time transaction monitoring. Emphasis is placed on hands-on experience with leading tools that flag suspicious activities, analyze patterns, and support informed risk decisions across finance and insurance.

    Fraud never sleeps—and neither do AI systems that fight it. This course teaches you how to detect anomalies, predict risk, and create smarter defenses using AI tools. Learn the frameworks behind financial security and how intelligent platforms are rewriting the rules of fraud prevention.

    What will you receive upon completion?

    Certificate of Completion, and Badge to use across Professional Platforms

    What will you learn each week?

    • Session 1: Foundations of Financial Fraud and Risk Analysis

      • Types of financial fraud: transactional, identity, insider, cyber

      • Traditional vs. AI-based detection

      • Introduction to fraud analytics lifecycle

      • Overview of key metrics (false positives, precision, recall)

      Session 2: Machine Learning for Risk Prediction

      • Supervised and unsupervised learning in fraud analysis

      • Feature engineering for financial datasets

      • Tools: Scikit-learn, DataRobot, H2O.ai

      • Hands-on: Train a basic model on a labeled fraud dataset

    • Session 3: Anomaly Detection in Real-Time Systems

      • Time-series and behavioral analysis for unusual activity

      • Online vs. batch detection pipelines

      • Tools: AWS Fraud Detector, Azure Anomaly Detector, Feedzai

      • Hands-on: Detect anomalies in simulated transaction streams

      Session 4: Risk Scoring and Credit Analytics

      • Developing dynamic credit risk models

      • Integrating real-time risk assessments into decision engines

      • Tools: Zest AI, Upstart, FICO AI

      • Hands-on: Simulate scoring for a group of loan applicants

    • Session 5: Natural Language Processing for Risk Signals

      • NLP applied to news feeds, emails, policy violations

      • Detecting insider threats or irregular statements

      • Tools: AlphaSense, BloombergGPT, Custom ChatGPT models

      • Hands-on: Run sentiment analysis on financial disclosures

      Session 6: Designing Explainable Risk Models

      • Interpretability of ML models in regulated industries

      • Tools: SHAP, LIME, model cards

      • Hands-on: Apply SHAP values to explain predictions on fraud dataset

    • Session 7: Governance and Ethics in AI-Driven Risk Systems

      • Risk of overfitting and unintended bias

      • Legal and regulatory expectations (e.g., Basel III, GDPR)

      • Responsible deployment and monitoring frameworks

      Session 8: Capstone Project – Fraud Risk Simulator

      • Design a fraud detection pipeline using one or more tools

      • Create dashboard and reporting elements

      • Present findings with explainability metrics

  • Why take this course?

    This 24-hour course explores how AI and RegTech platforms are revolutionizing regulatory compliance in the financial sector. Participants will learn how intelligent systems support anti-money laundering (AML), know-your-customer (KYC) processes, audit readiness, and ongoing regulatory reporting. Through practical sessions, students will engage with cutting-edge tools that reduce risk exposure, ensure transparency, and keep organizations ahead of changing compliance mandates.

    Meet compliance before it meets you. In this course, you'll explore how RegTech and AI tools automate document reviews, streamline KYC/AML checks, and enhance your regulatory posture. Master the art of staying compliant—smarter, faster, and with fewer manual hours.

    What will you receive upon completion?

    Certificate of Completion, and Badge to use across Professional Platforms

    What will you learn each week?

    • Session 1: Understanding Compliance Challenges in Modern Finance

      • Overview of major regulatory frameworks (e.g., AMLD, GDPR, Dodd-Frank)

      • Key compliance bottlenecks in financial workflows

      • The role of RegTech in transforming compliance

      Session 2: Tools and Technologies in RegTech

      • Document intelligence and data extraction tools

      • Tools: ComplyAdvantage, Alloy, Ayasdi, Hyperscience

      • Hands-on: Use a RegTech tool to extract entities from regulatory documents

    • Session 3: Automating KYC and Customer Onboarding

      • Identity verification, background checks, and risk flagging

      • Tools: Onfido, Jumio, Socure

      • Hands-on: Build an onboarding pipeline for a new customer using RegTech APIs

      Session 4: Anti-Money Laundering and Transaction Monitoring

      • AI pattern recognition in AML workflows

      • Suspicious activity detection and case management

      • Tools: Actimize, Feedzai, SAS AML

      • Hands-on: Monitor transactions and generate alerts for suspicious behavior

    • Session 5: Continuous Compliance and Regulatory Reporting

      • Automating real-time regulatory checks and reporting

      • APIs and integrations with regulatory databases

      • Tools: Ascent, ClauseMatch, Regnology

      • Hands-on: Schedule and simulate a regulatory submission using automation tools

      Session 6: Auditing and Evidence Management

      • Managing audit trails and data lineage

      • Preparing digital documentation for audit-readiness

      • Tools: Smarsh, LogicGate, Hyperproof

      • Hands-on: Organize a digital audit package for a sample financial service

    • Session 7: Ethics and Legal Boundaries in Compliance Tech

      • Privacy, consent, and the limits of data automation

      • AI explainability and the right to contest automated decisions

      • Legal implications of black-box compliance models

      Session 8: Capstone Project – RegTech Simulation

      • Simulate an end-to-end KYC or AML compliance process

      • Integrate multiple RegTech tools

      • Present your solution to a mock regulatory board

  • Why take this course?

    This 24-hour course focuses on how AI and digital tools are transforming personal finance, wealth management, and institutional portfolio management. It equips learners with a practical understanding of robo-advisors, algorithmic investment platforms, portfolio optimization models, and tools for risk-adjusted decision-making. Designed for finance professionals and innovators, the course bridges traditional financial principles with next-generation AI capabilities.

    Grow smarter. From automated advisors to intelligent portfolio design, this course introduces the tools redefining wealth management. Learn to personalize strategies, simulate outcomes, and make data-backed investment decisions with AI at your side.

    What will you receive upon completion?

    Certificate of Completion, and Badge to use across Professional Platforms

    What will you learn each week?

    • Session 1: The Evolution of Wealth Management

      • Overview of personal and institutional wealth management

      • Role of digital transformation in investment services

      • Tools: Betterment, Wealthfront, Ellevest, Vanguard Digital Advisor

      Session 2: Robo-Advisors and Automated Investment Platforms

      • AI-powered asset allocation and risk profiling

      • Behavioral nudging and personalized recommendations

      • Hands-on: Simulate onboarding with a robo-advisor platform

    • Session 3: Portfolio Construction and Optimization

      • Principles of diversification, rebalancing, and risk-return trade-offs

      • Tools: QuantConnect, Ziggma, Smartleaf

      • Hands-on: Construct a diversified portfolio and run optimization scenarios

      Session 4: Predictive Tools for Market Trends and Alerts

      • Using AI to identify investment signals and alerts

      • Natural language processing in financial news and sentiment

      • Tools: AlphaSense, Atom Finance, FinChat.io

      • Hands-on: Build an alert system based on news sentiment shifts

    • Session 5: ESG and Thematic Investing with AI Support

      • Integrating environmental, social, and governance (ESG) data

      • Using AI to filter and score impact investments

      • Tools: Clarity AI, Morningstar ESG Screener, Arabesque S-Ray

      • ​Hands-on: Score and filter an ESG-focused portfolio

      Session 6: Risk Management and Hedging Strategies

      • Dynamic risk modeling and predictive volatility measures

      • Tools: Portfolio Visualizer, BlackRock Aladdin, Riskalyze

      • ​Hands-on: Simulate hedging for a market downturn

    • Session 7: Hybrid Models and the Human-AI Wealth Advisor

      • Combining AI models with human advice

      • Trust, transparency, and ethical considerations in wealth tech

      Session 8: Capstone Simulation – Portfolio Lab

      • Design a client portfolio strategy using multiple AI tools

      • ​Present optimization decisions and risk mitigation plans

  • Why take this course?

    This 24-hour course focuses on how AI and decision intelligence systems enable smarter, data-driven forecasting and strategic planning in the financial sector. Students will learn to leverage predictive models, simulation tools, and scenario-based analysis to guide investment decisions, budget planning, and financial resilience. The course integrates practical tools with core principles of financial modeling and uncertainty analysis.

    From intuition to intelligence—this course puts the future of finance in your hands. Learn how to use AI forecasting, predictive simulations, and strategic analytics to drive decisions that stand up to uncertainty. This is financial modeling reimagined for the next era.

    What will you receive upon completion?

    Certificate of Completion, and Badge to use across Professional Platforms

    What will you learn each week?

    • Session 1: Foundations of Decision Intelligence in Finance

      • What is decision intelligence and why it matters

      • Comparing BI, AI, and DI for strategic insight

      • Tools: Google Cloud Vertex AI Forecast, Microsoft Fabric

      Session 2: Predictive Modeling in Financial Contexts

      • Linear and nonlinear models for revenue forecasting

      • Time-series analysis and regression use cases

      • Tools: Prophet, DataRobot, Amazon Forecast

      • Hands-on: Build a 12-month revenue forecast

    • Session 3: Scenario Planning and Sensitivity Analysis

      • Creating dynamic financial models with inputs and assumptions

      • Testing the impact of economic shocks or policy changes

      • Tools: Causal, Excel with AI plugins, Monte Carlo tools

      • Hands-on: Simulate 3 financial outcomes based on interest rate shifts

      Session 4: Decision Trees and Strategic Recommendations

      • Using AI-generated decision paths

      • Trade-off analysis in budgeting, investing, and resource allocation

      • Tools: Akkio, MindFoundry, IBM Decision Optimization

      • Hands-on: Build a decision tree for corporate investment options

    • Session 5: Visualization and Dashboarding for Strategic Finance

      • Turning forecasts into stakeholder-friendly reports

      • Designing dynamic and real-time views

      • Tools: Tableau, Power BI, Datawrapper

      • Hands-on: Create a forecasting dashboard for executive review

      Session 6: Combining Human Judgment with AI Insights

      • Human-in-the-loop decision systems

      • Avoiding overreliance on machine-generated recommendations

      • Cognitive bias in data interpretation

      • Case study: augmenting CFO decision-making with AI

    • Session 7: Risk-Aware Forecasting and Compliance

      • Incorporating compliance triggers and regulations into modeling

      • Risk scoring and early-warning simulations

      • Tools: Riskified, SAS Risk Modeling, Quantexa

      Session 8: Capstone Project – Future-Proofing Financial Strategy

      • Build a full decision intelligence model for a business case

      • Integrate forecasting, dashboards, and decision logic

      • Present a strategy roadmap based on simulated scenarios

ARTS, MEDIA, & ENTERTAINMENT

Course Registration

Ready to take the next step? Browse our available and upcoming courses below and secure your spot today. Don’t miss out—enroll now to unlock new opportunities!

COURSE NAME
COURSE DURATION
COURSE FEE
REGISTRATION

Foundations of Agentic AI: Building Intelligent, Goal-Directed Systems

Month Year - Month Year

Session / Time

$xxxx

Registration Opens Month Year

Prompt Engineering for Beginners: Mastering the Language of AI

Month Year - Month Year

Session / Time

$xxxx

Registration Opens Month Year

Introduction to Generative AI

Month Year - Month Year

Session / Time

$xxxx

Registration Opens Month Year

Introduction to AI Tools: Exploring What’s Possible

Month Year - Month Year

Session / Time

$xxxx

Registration Opens Month Year
FINANCE, RISK AND COMPLIANCE

Experential Learning

By completing a Conifer 2C course, students gain exclusive access to upcoming charrettes, research projects, and pilot placement opportunities - bridging learning with real-world innovation.

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Charrette

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Research Project

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Pilot Placement

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