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Course Outline
Introduction to Generative AI and Large Language Models
- Overview of generative AI and its historical development.
- Introduction to LLMs: Examining GPT, BERT, and their key capabilities.
- Comparing generative models with traditional NLP methodologies.
Transformer Architecture and Model Training
- Deep dive into the transformer architecture used in LLMs.
- Understanding self-attention mechanisms and language modeling.
- Training large language models and understanding the fine-tuning process.
Prompt Engineering for Effective Interaction
- Designing prompts to ensure accurate and valuable outputs.
- Refining prompt strategies for diverse applications.
- Experimenting with different prompt variations to enhance response quality.
Applications of LLMs in Business
- Automating customer service through conversational AI.
- Generating content for marketing and media purposes.
- Utilizing LLMs for data analysis and automated report generation.
Ethical Considerations and Bias Management
- Detecting potential biases within LLM-generated content.
- Addressing ethical issues inherent in generative AI applications.
- Implementing strategies for the responsible deployment of LLMs.
Advanced Techniques in LLMs
- Fine-tuning LLMs for domain-specific requirements.
- Integrating LLMs with other AI systems to boost functionality.
- Exploring multilingual and cross-lingual capabilities.
The Future of Generative AI in Business
- Emerging trends in generative AI and LLM research.
- Opportunities and challenges associated with scaling LLM solutions.
- Preparing organizations for AI-driven business transformation.
Summary and Next Steps
Requirements
- Fundamental knowledge of machine learning and natural language processing principles.
- Proficiency in Python programming.
Target Audience
- Data scientists and AI specialists keen on exploring generative AI technologies.
- Business professionals investigating automation and content creation tools.
- Technical managers and executives aiming to integrate LLMs into their operational workflows.
14 Hours
Testimonials (2)
The interactive style, the exercises
Tamas Tutuntzisz
Course - Introduction to Prompt Engineering
A great repository of resources for future use, instructor's style (full of good sense of humor, great level of detail)
