Congratulations!
1. Congratulations!
Congratulations on making it to the end of the course! You've come a long way!2. Chapter 1
In Chapter 1, you began accessing and prompting DeepSeek models via an API. You learned that these models weren't just any old LLM, but could "think" or "reason" about complex problems, which makes them much more accurate on coding, research, and analysis tasks.3. Chapter 2
In Chapter 2, you learned to prompt DeepSeek's models to solve a range of tasks, including question-answering, text transformation, content generation, categorization tasks like sentiment analysis, and code debugging. You even learned how to control the model's behavior by tweaking the max_tokens and temperature parameters.4. Chapter 3
In Chapter 3, we unleashed the full potential of DeepSeek's models by utilizing system and assistant roles. You used the system role to steer the model towards more desirable outputs and to add guardrails, or restrictions, to how the model could respond. You used the assistant role to provide few-shot prompts in a more structured way, so the model has a better understanding of how to continue the conversation. Finally, you created a conversation history and a mechanism to add new model messages back into the history, so the conversation can continue to go on in both chat and reasoning modes!5. What next?
In this course, you've started to use AI models via an API. This is a small, but very important part of the sorts of AI applications you might have interacted with on phones or computers. If you'd like to learn more about how to create AI applications, like chatbots, recommendation systems, and search engines, check out the tracks shown to continue your journey!6. Let's practice!
Congratulations, again! I hope you enjoyed learning about DeepSeek models. Have fun applying your newly-learned skills!Create Your Free Account
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