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course discount

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pages/course.en.mdx
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import { Callout } from 'nextra/components'
<Callout type= "info" emoji="🎉">
We are excited to launch our brand new [course website](https://dair-ai.thinkific.com/pages/courses) and releasing our first course on Introduction to Prompt Engineering.
We are excited to launch our brand new course website and releasing our first course on [Introduction to Prompt Engineering](https://dair-ai.thinkific.com/courses/introduction-prompt-engineering).
[Join Now](https://dair-ai.thinkific.com/bundles/pro)!
Use code PROMPTING20 to get an extra 20% off.
IMPORTANT: The discount is limited to the first 500 students.
[Join Now](https://dair-ai.thinkific.com/courses/introduction-prompt-engineering)!
</Callout>

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pages/index.en.mdx
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@ -15,8 +15,12 @@ Motivated by the high interest in developing with LLMs, we have created this new
## Want to learn more?
<Callout type= "info" emoji="🎉">
We are excited to launch our brand new [course website](https://dair-ai.thinkific.com/pages/courses) and releasing our first course on Introduction to Prompt Engineering.
We are excited to launch our brand new course website and releasing our first course on [Introduction to Prompt Engineering](https://dair-ai.thinkific.com/courses/introduction-prompt-engineering).
[Join Now](https://dair-ai.thinkific.com/bundles/pro)!
Use code PROMPTING20 to get an extra 20% off.
IMPORTANT: The discount is limited to the first 500 students.
[Join Now](https://dair-ai.thinkific.com/courses/introduction-prompt-engineering)!
</Callout>

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pages/techniques/cot.en.mdx
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@ -94,7 +94,9 @@ Finally, you ate 1 apple, so you would remain with 10 apples.
It's impressive that this simple prompt is effective at this task. This is particularly useful where you don't have too many examples to use in the prompt.
<Callout type= "info" emoji="🎓">
Want to learn more about advanced use cases of Chain-of-Thought? Check out our [new cohort-based course](https://maven.com/dair-ai/prompt-engineering-llms?cohortSlug=). Use promo code MAVENAI20 for a 20% discount.
Want to learn more about advanced use cases of Chain-of-Thought? Check out our [new prompt engineering course](https://dair-ai.thinkific.com/courses/introduction-prompt-engineering). Use promo code PROMPTING20 for an extra 20% discount.
IMPORTANT: The discount is limited to the first 500 students.
</Callout>
## Automatic Chain-of-Thought (Auto-CoT)

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pages/techniques/fewshot.en.mdx
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@ -116,5 +116,7 @@ That didn't work. It seems like few-shot prompting is not enough to get reliable
Overall, it seems that providing examples is useful for solving some tasks. When zero-shot prompting and few-shot prompting are not sufficient, it might mean that whatever was learned by the model isn't enough to do well at the task. From here it is recommended to start thinking about fine-tuning your models or experimenting with more advanced prompting techniques. Up next we talk about one of the popular prompting techniques called chain-of-thought prompting which has gained a lot of popularity.
<Callout type= "info" emoji="🎓">
Want to learn more about how to effectively apply few-shot prompting? Check out our [new cohort-based course](https://maven.com/dair-ai/prompt-engineering-llms?cohortSlug=). Use promo code MAVENAI20 for a 20% discount.
Want to learn more about how to effectively apply few-shot prompting? Check out our [new prompt engineering course](https://dair-ai.thinkific.com/courses/introduction-prompt-engineering). Use promo code PROMPTING20 for an extra 20% discount.
IMPORTANT: The discount is limited to the first 500 students.
</Callout>