This course offers a comprehensive introduction to large language models (LLMs) and the challenges businesses face in adopting them. You’ll first explore the fundamentals of LLMs, their architecture, and core prompt engineering principles. Next, you’ll learn how to customize LLMs through fine-tuning, training from scratch, and in-context learning. The course will also delve into enterprise-specific challenges, including complex datasets, legal risks, and the costs associated with LLM adoption. By the end of the course, you’ll have the knowledge to interact with, optimize, and deploy LLMs in real-world applications.
What you'll learn
- Understand the basic structure and capabilities of large language models (LLMs).
- Learn how to customize LLMs by training from scratch and fine-tuning pre-existing models.
- Discover the benefits of in-context learning and its applications.
- Understand cost considerations and the complexities of integrating LLMs into businesses.
- Recognize challenges and risks, including hallucinations and prompt injection.
- Optimize prompt reliability while addressing ethical, privacy, and security concerns in business.
Begin your professional career by learning data science skills with Data Science Dojo, a globally recognized e-learning platform where we teach students how to learn data science, data analytics, machine learning and more.
Our programs are available in the most popular formats: in-person, virtual instructor-led, and self-paced training. This means that you can choose the learning style that works best for you! From the very beginning, our focus is on helping students develop a think-business-first mindset so that they can effectively apply their data science skills in a real-world context. Enrol in one of our highly-rated programs and learn the practical skills you need to succeed in the field.
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