DURATION: 1 Day
Course Objective
- Introduction to Artificial Intelligence
- Definition and Scope of AI
- Historical Evolution of AI
- Key Concepts and Terminologies
- Types of AI: Narrow, General, and Superintelligent AI
- AI in Practice
- How AI Algorithms Work: An Overview
- Machine Learning vs. Deep Learning
- Natural Language Processing (NLP)
- Computer Vision
- Use Cases and Applications Across Industries
- Effective and Ethical Utilization of AI
- Understanding AI Ethics and Its Importance
- Bias in AI: Detection and Mitigation
- Transparency and Explain ability in AI
- Regulatory Compliance and Standards – Case Studies on Ethical AI Implementation
- Managing AI Projects
- Project Life Cycle in AI Development
- Stakeholder Management and Communication
- Resource Allocation and Budgeting
- Risk Management in AI Projects
- Success Metrics and Performance Evaluation
- AI Governance and Oversight
- Frameworks for AI Governance
- Role of AI Ethics Committees
- Data Governance and Privacy Concerns
- Continuous Monitoring and Auditing AI Systems
- Legal and Policy Implications
- AI in Business Strategy
- Aligning AI Initiatives with Business Goals
- Building a Data-Driven Culture
- Integrating AI into Business Processes
- Change Management for AI Adoption
- Measuring Return on Investment (ROI) for AI
- Launching and Scaling AI-based Start-ups
- Ideation and Validation of AI Start-ups
- Building an AI-Driven Business Model
- Funding and Investment Strategies
- Assembling the Right Team
- Challenges and Solutions in AI Start-ups
- Future Trends in AI
- Emerging Technologies in AI
- The Impact of AI on Jobs and Society
- Future Ethical Considerations
- Predictions for AI Development
- Preparing for the Future of AI