- Level: Beginner
- Prerequisites: None
- Assessments: Weekly Micro Assessments; Full Assessment in the Final Week
Week 1: Understanding AI and Innovation
Learning Outcome: Understand how AI fosters innovation.1.1 Overview of AI-driven innovation.
1.2 Identifying gaps for innovation using AI.
1.3 Examples of groundbreaking AI solutions.
Practical Component
Brainstorm innovative AI ideas.
Week 2: Building Blocks of AI Innovation
Learning Outcome: Explore key components of innovative AI solutions.1.4 Understanding AI frameworks and tools.
1.5 Data collection and processing for innovation.
1.6 Prototyping new AI solutions.
Practical Component
Prototype a simple AI idea (e.g., sentiment analysis).
Week 3: Problem-Solving with AI
Learning Outcome: Learn to use AI to solve unique problems.1.7 Identifying problems AI can solve.
1.8 Developing algorithms for unique challenges.
1.9 Evaluating the feasibility of AI ideas.
Practical Component
Develop an AI solution for a real-world challenge.
Week 4: Implementing AI Innovations
Learning Outcome: Take AI ideas from concept to reality.1.10 Testing and validating AI solutions.
1.11 Scaling AI solutions for broader applications.
1.12 Tools for deploying AI projects.
Practical Component
Deploy a simple AI innovation in a test environment.
Week 5: Ethics and Sustainability in AI Innovation
Learning Outcome: Develop responsible AI innovations.1.13 Ethical considerations in AI development.
1.14 Ensuring sustainability of AI solutions.
1.15 Balancing innovation with social impact.
Practical Component
Analyze the sustainability of an AI project.
Week 6: Final Project
Learning Outcome: Develop and pitch an innovative AI solution.1.16 Ideate and prototype a unique AI solution.
1.17 Refine and validate the solution.
1.18 Present the project to a panel of peers or experts.
Practical Component
Deliver a working AI innovation.