Artificial intelligence

Generative AI

Master the basics of Generative AI tools and their applications in real-world scenarios.Enhance productivity with practical techniques…

Master the basics of Generative AI tools and their applications in real-world scenarios.
Enhance productivity with practical techniques for automating workflows.
Develop skills in creating high-quality AI-generated text, images, and designs.
Learn ethical and responsible AI usage to align with business values.
Stay ahead of industry trends with expert-led, actionable training.

What you will learn

  • Analytical and problem-solving skills to design AI-driven solutions.
  • Proficiency in AI tools for text generation, image creation, and automation.
  • Development and documentation of AI use cases and workflows.
  • Application of machine learning principles and project management methodologies.
  • Techniques for training, fine-tuning, and deploying generative AI models.
  • Data analysis and processing to uncover patterns and optimize AI outputs.
  • Ethical considerations and responsible AI practices.
  • Technical skills to integrate generative AI solutions into business systems.

How you’ll learn

  • Skill-based, hands-on learning
  • Practice new skills by completing job-related tasks.
  • Expert guidance
  • No downloads or installation required
  • Access the tools and resources you need in a pre-configured cloud workspace.
  • Receive training from industry experts.
  • Gain hands-on experience solving real-world job tasks.
  • Build confidence using the latest tools and technologies.

Why choose us?

  • Best price in the industry
    You won’t find better value in the marketplace. If you do find a lower price, we will beat it.
  • Trusted & Approved trainers
  • Many delivery methods
    Flexible delivery methods are available depending on your learning style.
  • High quality resources
    Resources are included for a comprehensive learning experience.
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What Will You Learn?

  • Feature engineering
  • Implementation and training ML models
  • Model evaluation techniques: accuracy, precision, recall, and F1-score
  • Model optimization techniques: cross-validation and hyperparameter tuning

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