Introduction to DeepSeek

Understanding DeepSeek's capabilities can be complex. This course will teach you to effectively evaluate, deploy, and optimize DeepSeek models for real-world AI applications through hands-on implementation.
What you'll learn
DeepSeek's open-source models are revolutionizing AI accessibility, but understanding their architecture and implementation can be challenging. In this course, Introduction to DeepSeek, you'll learn to effectively evaluate and deploy these powerful models for real-world applications. First, you'll explore the innovative Mixture-of-Experts architecture that makes DeepSeek efficient, understanding how only 37B parameters are active during inference despite the model's 671B total parameters. Next, you'll discover how DeepSeek-R1's reasoning capabilities compare against proprietary models through comprehensive benchmark analysis and practical demonstrations. Finally, you'll learn how to implement DeepSeek models in production environments and calculate the total cost of ownership for different deployment strategies. When you're finished with this course, you'll have the skills and knowledge of DeepSeek's capabilities and limitations needed to make informed decisions about integrating these models into your AI workflow and applications.
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