The AI Development with DeepSeek for Developers course is a hands-on guide to building real-world AI applications using DeepSeek's open-source models鈥攏o prior experience required. Designed for developers, students, ML engineers, and tech enthusiasts, this course combines conceptual overviews with practical projects, delivered through Jupyter notebooks and popular Python libraries like LangChain, Streamlit, Promptify, DSPy, and DeepEval.
AI Development with DeepSeek for Developers
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Gain insight into a topic and learn the fundamentals.
Beginner level
Recommended experience
2 weeks to complete
at 10 hours a week
Flexible schedule
Learn at your own pace
What you'll learn
Build Q&A, chatbot, and code generation apps using DeepSeek models and practical Python tools.
Apply DeepSeek for document summarization, long-context analysis, and mathematical reasoning in real-world projects.
Create task-specific AI agents, compare DeepSeek鈥檚 performance and pricing with OpenAI, Claude, and Gemini, and interpret benchmark results.
Customize, fine-tune, and evaluate DeepSeek models using advanced features like GRPO, MoE, quantized models, and DeepEval metrics.
Skills you'll gain
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Recently updated!
July 2025
Assessments
16 assignments
Taught in English
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There are 4 modules in this course
In the first module, you鈥檒l get introduced to DeepSeek鈥檚 open-source model ecosystem and learn how to access and use the models via the web interface and API. You鈥檒l explore the differences between DeepSeek-V3, R1, and Coder, and build your first simple app using Promptify and Streamlit. This module builds your foundation for hands-on work with the models.
What's included
13 videos4 readings4 assignments1 discussion prompt2 plugins
This module focuses on applying DeepSeek to solve real-world tasks. You鈥檒l use DeepSeek models for document retrieval, summarization, code generation, and building interactive Q&A systems. This module blends conceptual understanding with implementation using LangChain, DSPy, and Jupyter notebooks.
What's included
9 videos3 readings4 assignments1 plugin
In the third module, you鈥檒l build practical task-based agents using DeepSeek and LangChain. You鈥檒l also evaluate how DeepSeek compares with other leading models like GPT-4o, Claude, and Gemini in terms of pricing, benchmark performance, and capabilities. This module gives you insight into model selection and real-world deployment tradeoffs.
What's included
9 videos3 readings4 assignments1 plugin
In the final module, you鈥檒l explore DeepSeek鈥檚 unique innovations 鈥� from Guided Roleplay Optimization (GRPO) and Mixture-of-Experts to fine-tuning and quantized models for efficient inference. You鈥檒l also use tools like DeepEval to assess model output quality and benchmark performance. This module helps you understand DeepSeek鈥檚 strengths and customization potential.
What's included
11 videos3 readings4 assignments1 plugin
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Frequently asked questions
Yes, this course is designed for beginners and intermediates. You鈥檒l get step-by-step guidance on using DeepSeek鈥檚 models and tools, with no prior AI or coding experience required.
You鈥檒l learn to build Q&A and chatbot apps, summarize documents, generate code, create AI agents, and compare model performance鈥攁ll using open-source DeepSeek models and popular Python libraries.
You鈥檒l work with DeepSeek-V3, R1, and Coder models, as well as LangChain, Streamlit, Promptify, DSPy, DeepEval, and Jupyter notebooks for hands-on projects.
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Financial aid available,