ElevateAI: 12-Week AI Education Program for North Forge Founders
Exclusive no-cost program for North Forge founders to explore and apply AI.
In partnership with CGI
North Forge is excited to launch the first cohort of ElevateAI, a 12-week education program created exclusively for our founders. Developed in partnership with CGI, this initiative will equip entrepreneurs with both foundational and applied knowledge to integrate AI into their businesses, strengthen decision-making, and spark innovation. CGI is a global IT and business consulting services firm that helps organizations design, implement, and scale technology solutions, including AI, to drive growth and competitiveness.
Spots are limited and will be offered first to North Forge founders.
There is no cost to participate.
Program Overview
Format: Asynchronous online modules with 4 live Master Classes
Duration: 12 weeks, first cohort began October 20th, 2025
Schedule: New modules released every Monday
Master Classes: Weeks 3, 6, 9 and 11 (live expert-led sessions)
Delivery: Via a dedicated Learning Management System (LMS)
Who Should Apply?
This program is tailored for early-stage founders who are ready to explore AI’s potential in their startup. Participants should:
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Have a live product or MVP with some data to work from
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Be tackling a specific business challenge AI could help solve
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Be open to budgeting for future AI tools and implementation
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Have a basic go-to-market plan and target customers in mind
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Be eager to learn by doing through hands-on modules and the capstone project
Core Modules
Participants will gain both theoretical grounding and practical skills through 12 modules. Modules include:
1
Foundations of AI & Machine Learning
At the end of this module, learners will be able to:
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Define AI and Machine learning
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List the events that shaped AI history
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Explain what an AI Agent is and their value
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Identify AI tools in the market
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Describe how businesses apply AI in their daily operations
2
Prompt Engineering & Conversational AI
At the end of this module, learners will be able to:
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Define prompt engineering and its usage with conversational AI
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Describe how Large Language Models use prompts
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Develop prompts to generate various outputs using best practices
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Compare prompt engineering tools and outline their strengths across diverse applications
3
AI 2025 Trends and Augmented Intelligence
LIVE EXPERT SESSION
At the end of this module, learners will be able to:
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Outline key trends in AI and other forms of augmented intelligence in 2025
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Describe how these trends apply to the needs of startups
4
AI Ethics and Data Governance
At the end of this module, learners will be able to:
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Define the basic elements of a responsible use of AI
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Define common AI guardrails and governance elements
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Describe techniques and approaches for monitoring and removing bias in the use of LLM AI
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Describe a basic approach to their own organization/product Responsible Use of AI Policy
5
AI Powered Market Research and Intelligence
At the end of this module, learners will be able to:
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Explain how AI technologies are transforming the traditional market research process
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Differentiate between human-driven, hybrid and AI automated research methods and their pros and cons for start ups
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Identify leading AI tools for competitor analysis, customer insights and trend forecasting
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Describe how AI can help transform raw data into meaningful insights using summarization, sentiment analysis and data visualization
6
Data Scientists on Getting Started with AI
LIVE EXPERT SESSION
At the end of this module, learners will be able to:
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Identify common AI use cases in startups (e.g., customer service, market research, product features, personalization).
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Describe how to find a good AI partner to support their start up
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Explore and test beginner-friendly AI tools (like ChatGPT, Notion AI, or Midjourney) to solve specific startup challenges.
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Evaluate whether and where to apply AI in their own startup (e.g., using a simple opportunity checklist or canvas).
7
Real World Use Cases for Startups
LIVE EXPERT SESSION
At the end of this module, learners will be able to:
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Identify real-world examples of AI being used in marketing, product, sales, operations, customer service, and finance.
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Understand how AI is transforming key business processes and customer experiences in early-stage startups.
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Compare use cases by function, business model, and stage of growth.
8
Developing AI Cost Structures, Performing ROI Analysis and Financial Strategy
At the end of this module, learners will be able to:
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Identify key cost drivers in AI initiatives (e.g., data acquisition, tools/platforms, talent, compute, integration).
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Compare different AI development options (build vs. buy vs. partner) and their financial implications.
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Break down the total cost of ownership (TCO) for a specific AI use case in their startup.
9
Machine Learning Operations Roundtable
LIVE EXPERT SESSION
At the end of this module, learners will be able to:
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Explain the role of MLOps in bridging data science and production environments.
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Describe the core components of MLOps (model development, deployment, monitoring, retraining, governance) in plain, founder-friendly language.
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Recognize the risks of skipping MLOps—like model drift, technical debt, and failed adoption.
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Identify what an end-to-end ML lifecycle looks like in early-stage startups.
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Compare lightweight vs. enterprise MLOps approaches, and understand what’s right-sized for a startup.
10
Managing an AI Implementation
At the end of this module, learners will be able to:
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Clarify the problem an AI initiative is solving and the expected outcomes.
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Set clear success metrics and KPIs for the implementation (e.g., accuracy, efficiency, cost savings, adoption).
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Align the AI project with business goals, user needs, and product strategy.
11
Future Trends, Regulatory Frameworks, and Risk Management
LIVE EXPERT SESSION
At the end of this module, learners will be able to:
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Summarize key regulatory developments in AI (e.g., EU AI Act, U.S. Executive Orders, global policy trends).
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Differentiate between high-risk vs. low-risk AI applications under emerging laws.
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Recognize legal and compliance implications for startups (e.g., data sourcing, model transparency, explainability).
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Identify major categories of AI risk (e.g., technical, operational, reputational, ethical, legal).
12
Multi-Modal AI and Human in the Loop Design
At the end of this module, learners will be able to:
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Explain what multi-modal AI is (e.g., combining text, image, video, audio inputs) in plain terms.
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Identify real-world startup use cases for multi-modal AI (e.g., voice assistants, medical imaging, content generation).
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Differentiate between uni-modal, multi-modal, and cross-modal systems.
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Describe the concept of HITL and why it’s critical for responsible AI adoption.
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Recognize scenarios where human input is essential (e.g., safety, bias correction, edge cases, training data refinement).
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Explore real-world HITL workflows and examples across industries.
Capstone Project: Founders x AI – Build Your First Agent
The ElevateAI program culminates in a two-week capstone experience where founders put their learning into action by prototyping an AI agent tailored to their business.
What to Expect
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Live Expert Session: AI Agents and the Future of Startups – explore how startups are leveraging AI agents to scale.
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Workshop: AI Agent 101 – hands-on ideation jam with service designers.
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Toolkit: Practical resources to support agent prototyping.
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TechSessions: Ask an Agent Expert – office hours with AI experts to solve technical challenges.
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Demo Showcase: Founders present their AI agent prototype, covering:
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The business problem tackled
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The AI agent solution
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A live or simulated demo
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Future roadmap and key takeaways
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By the end of ElevateAI, every participant will walk away with a tangible prototype and the confidence to pursue AI-powered innovation in their business.
