Getting Started with Generative AI
Skills:
LLM Foundations80%
Key Takeaways
Introduces generative AI concepts and techniques
Original Description
This course introduces the foundational concepts and advanced techniques in Generative AI, covering key topics such as model architectures, data preparation, prompt engineering, and deployment strategies. Learners will gain practical experience with cutting-edge tools and methodologies to effectively design, fine-tune, and deploy generative AI solutions.
By the end of this course, you will be able to:
- Define the core principles of generative AI, including models, algorithms, and applications.
- Apply data pre-processing and vectorization techniques to enhance generative AI models.
- Evaluate the strengths and weaknesses of GANs, autoencoders, transformers, and LLMs.
- Analyze and optimize prompting techniques for improved model performance.
- Design evaluation methods using metrics like BLEU and ROUGE to assess model outputs.
This course is suitable for the aspiring AI practitioners, software developers, data scientists, and ML engineers who want to enhance their skills in building, deploying, and optimizing generative AI solutions.
Join us to establish a solid foundation in generative AI and take your career to the next level with hands-on expertise in this transformative technology!
Watch on External: Coursera ↗
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