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Training Courses

AI for Deal Sourcing & Due Diligence in PE-VC

Course Code
FA27
Category
FINANCE AND ACCOUNTING
Course ID
2266
Course Outline

Course Overview

Artificial Intelligence is reshaping how private equity and venture capital firms identify, evaluate, and monitor investment opportunities. This course dives into AI powered tools and frameworks that support smarter deal sourcing, automated screening, predictive analytics, and deep due diligence. Participants will gain practical experience with modern platforms and algorithms used to uncover high potential targets and streamline risk evaluation processes.

TRAINING TOPICS

  •  AI applications in PE/VC deal sourcing and screening
  •  Machine learning models for startup and company scoring
  •  Natural Language Processing (NLP) for market scanning and news analysis
  •  Web scraping and automated pipeline building
  •  Predictive analytics for company growth and valuation estimation
  •  Red flag detection through anomaly and fraud analysis
  •  Sentiment analysis for founder and team profiling
  •  AI platforms for financial and operational due diligence
  •  Integration of alternative and unstructured data sources
  •  Risk management using AI in pre-investment evaluation

BY THE END OF THIS TRAINING COURSE, DELEGATES WILL BE ABLE TO:

  •  Leverage AI to automate and prioritize deal sourcing
  •  Build predictive models to score and rank investment targets
  •  Apply NLP techniques to monitor news, reports, and market signals
  •  Extract, clean, and analyze private company data at scale
  •  Conduct due diligence using AI assisted financial and operational reviews
  •  Detect red flags and inconsistencies in data using anomaly detection
  •  Integrate structured and alternative data for comprehensive insights
  •  Enhance investment decisions with AIbacked scenario analysis

TRAINING IS TAILORED TO

  •  Private Equity and Venture Capital professionals
  •  Investment analysts and portfolio managers
  •  M&A teams and deal originators
  •  Financial data scientists and AI engineers
  •  Strategy and innovation leaders in financial firms
  •  Startup accelerators and incubator managers

TRAINING METHODOLOGY

  •  Interactive labs using Python, financial APIs, and AI models
  •  Real-world VC/PE case studies and platform demos
  •  Handson NLP and sentiment analysis with market data
  •  Group exercises on company scoring and due diligence modeling
  •  Peer-reviewed AI model design for investment screening
  •  Final project: Build an AI enhanced deal sourcing pipeline

DAY ONE:

FOUNDATIONS OF AI IN PEVC DEAL SOURCING

  • Overview of private equity and venture capital lifecycle
  •  The AI transformation of sourcing and screening
  •  Key data sources: Crunchbase, PitchBook, CB Insights, LinkedIn
  •  Introduction to deal flow automation and scoring
  •  Data scraping and structuring private company profiles
  •  Case study: AI deal screening from news feeds and databases

DAY TWO:

MACHINE LEARNING FOR COMPANY SCORING & PREDICTIVE ANALYTICS

  •  Supervised learning for founder and company ranking
  •  Early signals: churn, burn rate, market traction indicators
  •  Company valuation prediction with regression models
  •  Training and testing startup scoring models
  •  Feature engineering and dataset curation
  •  Lab: Predicting startup success from historical datasets

DAY THREE:

NATURAL LANGUAGE PROCESSING FOR MARKET SIGNALS

  •  NLP fundamentals for investment analysis
  •  Market trend analysis using keyword and topic modeling
  •  Founder sentiment profiling from media and interviews
  •  Event extraction: acquisitions, funding rounds, lawsuits
  •  Lab: Building a pipeline for real-time startup signal tracking
  •  Case: Comparing NLP models on tech sector intelligence

DAY FOUR:

AI FOR DUE DILIGENCE AND RED FLAG DETECTION

  •  Red flag detection using anomaly and outlier models
  •  AI in operational and financial risk analysis
  •  Sentiment mining in user and client reviews
  •  Fraud detection algorithms and forensic checks
  •  Visualizing due diligence risk dashboards
  •  Lab: AI-powered due diligence for a sample company

DAY FIVE:

DEPLOYING AI FOR SMART INVESTMENT DECISIONS

  •  Scenario modeling and stress testing investment theses
  •  Evaluating model explainability and bias in PE/VC contexts
  •  Building custom investment scoring dashboards
  •  Integrating AI workflows with human-in the loop systems
  •  Final presentations of AI powered sourcing pipelines
  •  Wrap up: Future of AI in institutional investing

 

Course Schedule

From 05-Jan To 09-Jan 2026London 4300GBP Register
From 09-Feb To 13-Feb 2026Bacelona 4800EUR Register
From 16-Mar To 20-Mar 2026MUNICH 4800EUR Register
From 20-Apr To 24-Apr 2026Kuala Lumpur 4300 GBP Register
From 01-Jun To 05-Jun 2026London 4300GBP Register
From 13-Jul To 17-Jul 2026Amsterdam 4950EUR Register
From 24-Aug To 28-Aug 2026MUNICH 4800EUR Register
From 05-Oct To 09-Oct 2026Kuala Lumpur 4300 GBP Register
From 16-Nov To 20-Nov 2026London 4300GBP Register
From 28-Dec To 01-Jan 2027Bacelona 4800EUR Register
From 04-Jan To 08-Jan 2027Kuala Lumpur 4300 GBP Register
From 15-Feb To 19-Feb 2027London 4300GBP Register
From 29-Mar To 02-Apr 2027Amsterdam 4950EUR Register

Discounts and Registration

Group & Corporate Discounts:
Available for companies enrolling multiple participants to help maximize ROI.
Individual Discounts:
Offered to self-sponsored participants who pay in full and upfront.
Registration Process:
Corporate nominations must go through the client’s HR or Training department.
Self-nominations must be prepaid via the “payment by self” option.
Confirmation:
All registrations are subject to DIXONTECH’s approval and seat availability.
Refunds:
Provided in case of course cancellation or no seat availability.
Tax Responsibility:
Clients are responsible for any local taxes in their country.