Want to build smarter applications faster? This hands-on course will teach you how to develop, integrate, and scale AI-powered solutions using DeepSeek. With tools like VS Code, Cursor, and DeepSeek APIs, you'll gain practical skills to streamline code generation, testing, documentation, and agent-based workflows—no prior AI experience required.
Building Applications with DeepSeek
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Building Applications with DeepSeek
This course is part of Mastering DeepSeek.ai: From Fundamentals to Advanced Skills Specialization
Instructors: Board Infinity
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Intermediate level
Recommended experience
2 weeks to complete
at 10 hours a week
Flexible schedule
Learn at your own pace
What you'll learn
Build AI-powered applications using DeepSeek’s API, local setup, and developer tools for real-world software solutions.
Create intelligent agents and bots using embeddings, RAG pipelines, and task-based automation workflows.
Apply DeepSeek across the software development lifecycle to generate code, fix errors, and enhance test coverage.
Implement end-to-end AI development workflows using DeepSeek by combining setup, generation, evaluation, and deployment strategies.
Skills you'll gain
Details to know
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Recently updated!
June 2025
Assessments
13 assignments
Taught in English
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This course is part of the Mastering DeepSeek.ai: From Fundamentals to Advanced Skills Specialization
When you enroll in this course, you'll also be enrolled in this Specialization.
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There are 3 modules in this course
This module lays the groundwork for developers to begin working with DeepSeek, offering a clear understanding of the platform’s key capabilities, model offerings, and integration pathways. It begins with an introduction to DeepSeek's position in the AI ecosystem, highlighting its performance advantages, cost efficiency, and transparency compared to other AI solutions. Learners will explore how to access DeepSeek through various channels—such as web apps, APIs, and local instances—and gain insight into different model types like V3, R1, and Janus Pro. The module also addresses common misconceptions around DeepSeek’s origin, security, and licensing, enabling developers to make informed decisions. By the end of this module, learners will be fully equipped to explore and engage with DeepSeek for technical use.
What's included
10 videos4 readings4 assignments1 discussion prompt2 plugins
This module guides learners through the process of integrating DeepSeek into real-world applications, showcasing its adaptability across a range of development environments. Beginning with a breakdown of how to interact with DeepSeek models programmatically, the module dives into use cases like text generation, summarization, and agent-based workflows. Learners will explore how to connect DeepSeek with mobile apps, web services, automation platforms, and custom toolchains. The lessons focus on API usage, prompt engineering techniques, latency considerations, and design best practices. By the end of this module, developers will be equipped to confidently embed DeepSeek’s capabilities into end-to-end application workflows and deliver AI-powered functionality at scale.
What's included
13 videos3 readings4 assignments1 plugin
This final module focuses on extracting strategic value from DeepSeek through real-world case studies and high-impact implementation patterns. Learners will explore how organizations across industries—from finance to education—are using DeepSeek to drive innovation, automate workflows, and enhance user experiences. The module emphasizes practical insights, such as overcoming integration challenges, measuring ROI, and aligning AI solutions with business goals. In addition, it addresses frequently asked questions and offers guidance for continued learning and experimentation. By the end, learners will have a clear roadmap for applying DeepSeek effectively in diverse contexts and driving measurable outcomes.
What's included
15 videos3 readings5 assignments1 plugin
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Frequently asked questions
Basic familiarity with programming concepts and APIs is helpful, but no advanced coding is required. The course uses tools like DeepSeek, n8n, LMStudio, Cursor AI, VS code and Google Colab with guided examples and no-code/low-code options.
DeepSeek is an open-source LLM that developers can run locally or via API, offering more control, customization, and privacy. Unlike ChatGPT, it’s designed for deeper integration into dev workflows like debugging, testing, and RAG-based applications.
The course is designed to be completed in 3-4 weeks with 2-4 hours of learning per week. It’s self-paced, so you can adjust based on your availability.
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Financial aid available,