AI, Machine Learning, LLM, and Generative AI for Managers and Leadership Short Course by Tonex
This course introduces managers and leadership personnel to the key concepts, applications, and strategic considerations of Artificial Intelligence (AI), Machine Learning (ML), Large Language Models (LLMs), and Generative AI. It focuses on their impact on organizational decision-making, operational efficiency, and innovation, helping leaders make informed decisions about adopting and managing these technologies.
Learning Outcomes
By the end of the course, participants will:
- Understand the fundamental concepts of AI, ML, LLMs, and Generative AI
- Recognize the strategic applications and value these technologies can bring to their organization
- Be aware of the ethical, operational, and governance challenges associated with AI adoption
- Develop confidence in evaluating and leading AI-driven initiatives
Course Agenda:
- Introduction to AI and Machine Learning
- What is AI?
- Definition and types of AI: Narrow AI, General AI, and Artificial Superintelligence
- How AI is transforming industries
- Understanding Machine Learning (ML)
- Key concepts: supervised, unsupervised, and reinforcement learning
- The ML lifecycle: data collection, training, validation, and deployment
- Real-world applications: predictive analytics, fraud detection, and personalization
- Large Language Models (LLMs) Overview
- What Are LLMs?
- Definition and role in AI advancements
- Examples: OpenAI’s GPT series, Google’s PaLM, and Meta’s LLaMA
- How LLMs process and generate natural language
- Applications of LLMs in Organizations
- Customer support automation, content generation, and decision support
- Ethical and operational considerations
Break (10:30 AM – 10:45 AM)
- Generative AI: Transforming Creativity and Productivity
- What is Generative AI?
- Techniques: generative adversarial networks (GANs), diffusion models, and transformer-based models
- Applications: text, image, video, and audio generation
- Generative AI Use Cases in Business
- Enhancing marketing and content creation
- Automating design and prototyping
- Personalized customer experiences
Afternoon Session (1:30 PM – 5:00 PM)
- Leadership and Strategic Considerations for AI Adoption
- Building an AI Strategy
- Identifying opportunities for AI/ML implementation
- Aligning AI initiatives with organizational goals
- Balancing innovation with operational challenges
- Risk and Governance
- Data privacy, security, and ethical considerations
- Mitigating bias and ensuring fairness in AI systems
- Regulatory compliance and transparency
Break (3:00 PM – 3:15 PM)
- Future Trends and Challenges in AI
- Emerging Trends
- AI in autonomous systems, healthcare, and climate solutions
- Advances in multimodal models and real-time AI
- Challenges for Leadership
- Preparing for disruptions in labor markets and organizational structures
- Navigating the intersection of AI and human creativity
- Staying competitive in an AI-driven economy
- Wrap-Up and Key Takeaways (4:30 PM – 5:00 PM)
- Recap of key concepts and strategic insights
- Actionable steps for leaders to evaluate and adopt AI solutions
- Open Q&A session
- Certificate presentation