Length: 2 Days
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Introduction to AI and Generative AI Essentials Training by Tonex

generative-ai

This training provides a foundational understanding of artificial intelligence, machine learning, and generative AI. Participants explore AI fundamentals, large language models, and ethical considerations. The course includes hands-on exercises with open-source AI tools to enhance learning. By the end, attendees will understand AI applications, capabilities, and best practices for responsible AI adoption.

Audience:

  • AI and data professionals
  • Software developers
  • Business analysts
  • IT managers
  • Innovation leaders
  • Technology consultants

Learning Objectives:

  • Understand AI, ML, and generative AI fundamentals
  • Learn how large language models work
  • Explore real-world AI applications
  • Address ethical concerns in AI development
  • Apply AI tools for practical use cases

Course Modules:

Module 1: Foundations of AI and Machine Learning

  • Definition and scope of AI and ML
  • Historical evolution of AI technologies
  • Key AI applications in various industries
  • AI vs. traditional software development
  • Basic AI terminologies and concepts
  • Limitations and challenges of AI

Module 2: Introduction to Generative AI

  • Understanding generative AI models
  • ChatGPT, DALL-E, and other AI tools
  • Key components of generative models
  • Real-world use cases of generative AI
  • Strengths and weaknesses of generative AI
  • Responsible use of generative AI

Module 3: Large Language Models (LLMs)

  • What are LLMs and how they function
  • Training and fine-tuning LLMs
  • Open-source LLMs and their applications
  • Performance and scalability considerations
  • Common challenges in LLM deployment
  • Future advancements in LLM technology

Module 4: Hands-on with Open-Source AI Tools

  • Exploring GPT-J and Hugging Face models
  • Fine-tuning AI models for specific tasks
  • Using AI for text and image generation
  • Evaluating model performance and accuracy
  • Challenges in deploying open-source models
  • Best practices for AI model customization

Module 5: Ethical Considerations in AI

  • Bias and fairness in AI decision-making
  • Privacy and security concerns in AI
  • Ethical AI development and governance
  • Transparency and explainability in AI
  • Social impact of AI advancements
  • Strategies for responsible AI adoption

Module 6: Future Trends and AI Integration

  • Emerging AI trends and innovations
  • AI in business and digital transformation
  • AI-powered automation and optimization
  • Human-AI collaboration strategies
  • Preparing for AI-driven workplaces
  • Future challenges in AI development

Join this course to gain essential AI knowledge and practical insights. Learn how to apply AI tools responsibly and effectively. Enhance your expertise in AI and generative models today!

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