Dive deep into DeepSeek’s architecture, core capabilities, and real-world applications with this advanced deepseek course designed for developers and AI professionals. You’ll explore the foundational DeepSeek AI models, groundbreaking innovations like Efficient Mixture of Experts (MoE) and Multi-Head Latent Attention (MLA), and gain hands-on experience with practical integration via API and local deployment.
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推荐体验
推荐体验
初级
Ideal for developers, data scientists, and AI enthusiasts looking to explore and deploy DeepSeek in real-world applications.
推荐体验
推荐体验
初级
Ideal for developers, data scientists, and AI enthusiasts looking to explore and deploy DeepSeek in real-world applications.
您将学到什么
Understand DeepSeek’s architecture, training strategies, and key innovations for scalable AI solutions.
Deploy and integrate DeepSeek AI models through APIs and local hosting for real-world applications.
Build and fine-tune DeepSeek models for advanced reasoning, text generation, and intelligent automation.
Apply DeepSeek in diverse domains, from workflow automation to RAG systems and custom AI-powered apps.
您将获得的技能
要了解的详细信息

添加到您的领英档案
15 项作业
了解顶级公司的员工如何掌握热门技能

该课程共有5个模块
This module lays the groundwork for understanding DeepSeek’s capabilities, technical innovations, and practical access methods. It starts by introducing the strategic importance of DeepSeek in the broader AI landscape and provides a comparative look at its core models like V3, R1, and Janus Pro. Learners will gain a deeper appreciation for what sets DeepSeek apart in terms of performance, transparency, and cost-effectiveness. The module also walks through access methods—including web, local, API, and third-party interfaces—and addresses widespread myths related to DeepSeek’s origin, development cost, and security concerns. By the end, learners will have a clear understanding of how to access, evaluate, and use DeepSeek effectively and responsibly.
涵盖的内容
13个视频3篇阅读材料3个作业1个讨论话题1个插件
13个视频•总计69分钟
- Introduction to the Course•3分钟
- Meet your Instructor•1分钟
- Introduction to DeepSeek and Its Significance for AI•2分钟
- What is DeepSeek.ai? An Overview•9分钟
- Key DeepSeek Models: V3, R1, and Janus Pro•6分钟
- DeepSeek.ai vs. OpenAI: A Comparative Analysis•5分钟
- Debunking Common Myths About DeepSeek•10分钟
- DeepSeek’s Real Impact on the Open-Source AI Movement•7分钟
- Accessing and Using DeepSeek Effectively•2分钟
- Access Methods: Web, API, and Local Options•5分钟
- Web/Mobile App, Local Hosting, and API Setup•6分钟
- Alternative Hosting Platforms: GrokAPI, Cursor AI, Perplexity•8分钟
- Integration with Automation Tools and Platforms•5分钟
3篇阅读材料•总计40分钟
- Syllabus•10分钟
- Read more about DeepSeek.ai: What It Is, How It Compares, and Why It’s Shaping the Future of Open AI•15分钟
- Read more about How to Use DeepSeek Anywhere: Web, Mobile, API, and Automation Tools for Every Workflow•15分钟
3个作业•总计90分钟
- Graded Quiz: Exploring DeepSeek and Its Core Capabilities•60分钟
- Practice Quiz: Introduction to DeepSeek and Its Significance for AI•15分钟
- Practice Quiz: Accessing and Using DeepSeek Effectively•15分钟
1个讨论话题•总计10分钟
- Meet and Greet•10分钟
1个插件•总计5分钟
- Quick Course Check-In•5分钟
This module dives deep into the architectural design and technical innovations that define DeepSeek. It begins by explaining the high-level architecture of DeepSeek models and highlights their unique reasoning-centric training methodology, including the use of Reinforcement Learning from Human Feedback (RLHF). Learners will explore how DeepSeek models evolve from R1 to R1-Zero and understand the role of components like Multi-Head Latent Attention (MLA) and Mixture of Experts (MoE). By the end of this module, learners will have gained insight into how these innovations contribute to enhanced performance, scalability, and contextual understanding in AI outputs.
涵盖的内容
10个视频2篇阅读材料3个作业
10个视频•总计45分钟
- Architectural Overview and Training Techniques•1分钟
- High-Level Architecture of DeepSeek•5分钟
- Reasoning-Centric Training Approach in R1•7分钟
- Reinforcement Learning from Human Feedback (RLHF) Focus•5分钟
- Introduction to Key Innovations and Technical Advancements•1分钟
- Overview of DeepSeek’s Technological Innovations•2分钟
- Efficient Mixture of Experts (MoE) & Multi-Token Prediction•6分钟
- Pure RLHF in R1-Zero•10分钟
- Multi-Head Latent Attention (MLA) Mechanism•4分钟
- Summary: How DeepSeek’s Design Enhances Performance•2分钟
2篇阅读材料•总计30分钟
- Read more about DeepSeek's Architecture: From Model Design to Reasoning and Human-Centered AI•15分钟
- Read more about DeepSeek's Innovations: MoE, Multi-Token Prediction, MLA, and Pure RLHF•15分钟
3个作业•总计90分钟
- Graded Quiz: DeepSeek Under the Hood – Architecture and Innovations•60分钟
- Practice Quiz: Architectural Overview and Training Techniques•15分钟
- Practice Quiz: Key Innovations and Technical Advancements•15分钟
This module focuses on giving learners hands-on skills to deploy and integrate DeepSeek in both cloud and local environments. Learners will explore how to work with the DeepSeek API—from generating keys to integrating with automation tools such as N8N and Make.com. The second half of the module guides learners through self-hosting DeepSeek using tools like LMStudio, with step-by-step instructions on building local RAG (Retrieval-Augmented Generation) systems. Practical demonstrations ensure that learners can independently set up, manage, and troubleshoot deployments for varied use cases.
涵盖的内容
11个视频2篇阅读材料3个作业
11个视频•总计57分钟
- DeepSeek API – Integration and Use Cases•2分钟
- Introduction to DeepSeek API Access•3分钟
- Generating and Managing API Keys•5分钟
- Practical API Call Demonstrations•10分钟
- Usage Through Automation Platforms (N8N, Make.com)•11分钟
- Hosting DeepSeek Locally: Overview•1分钟
- Self-Hosting Overview for DeepSeek Models•4分钟
- Setting up DeepSeek locally with LMStudio•8分钟
- Best Practices for Local Deployment•4分钟
- Building a Local RAG - Model setup and document indexing•4分钟
- Building a Local RAG - Retrieval and response generation•6分钟
2篇阅读材料•总计30分钟
- Read more about DeepSeek API: Security, First Call, and Automation Integration•15分钟
- Read more about Self-Hosting DeepSeek: Local Deployment, Optimization, and RAG Pipelines•15分钟
3个作业•总计90分钟
- Graded Quiz: Hands-On with DeepSeek – API & Local Deployment•60分钟
- Practice Quiz: DeepSeek API – Integration and Use Cases•15分钟
- Practice Quiz: Hosting DeepSeek Locally•15分钟
This module highlights the wide-ranging real-world use cases where DeepSeek excels. It starts by categorizing the types of tasks DeepSeek can handle—from simple content generation and classification to advanced problem-solving and reasoning. Learners will then explore how DeepSeek supports downstream tasks using embeddings and powers applications like Retrieval-Augmented Generation (RAG) and AI agents. The module wraps up with workflow automation, web/mobile app integration, and best practices for aligning DeepSeek with business or technical objectives.
涵盖的内容
11个视频2篇阅读材料3个作业
11个视频•总计58分钟
- Task-Specific Capabilities of DeepSeek•1分钟
- Types of tasks for DeepSeek•1分钟
- Text Completion and Content Generation Tasks•7分钟
- Advanced Reasoning and Problem-Solving Tasks•10分钟
- Using DeepSeek for Classification and Inference•10分钟
- Harnessing DeepSeek Embeddings for Downstream Tasks•9分钟
- Industry Applications and Workflow Integration•1分钟
- Retrieval-Augmented Generation (RAG) Use Cases•8分钟
- Building AI Agents with DeepSeek Models•4分钟
- Workflow Automation and AI Integration•3分钟
- Web and Mobile Development with DeepSeek•3分钟
2篇阅读材料•总计30分钟
- Read more about DeepSeek in Action: Core Tasks, Reasoning, and Real-World Applications•15分钟
- Read more about Deploying DeepSeek: RAG, AI Agents, and Intelligent Integrations•15分钟
3个作业•总计90分钟
- Graded Quiz: Practical Applications of DeepSeek•60分钟
- Practice Quiz: Task-Specific Capabilities of DeepSeek•15分钟
- Practice Quiz: Industry Applications and Workflow Integration•15分钟
This final module focuses on empowering developers with tools and techniques to enhance, adapt, and customize DeepSeek for specific software development needs. Learners will explore how to use DeepSeek for intelligent code generation, debugging, and test creation. The module also provides an end-to-end guide to fine-tuning DeepSeek models on custom datasets for specialized applications. By the end, learners will have both the foundational understanding and the practical skills to extend DeepSeek’s capabilities through customization and development-centric workflows.
涵盖的内容
10个视频2篇阅读材料3个作业
10个视频•总计39分钟
- Enhancing Software Development with DeepSeek•1分钟
- Intelligent Code Generation•3分钟
- Code Review, Analysis, and Debugging•4分钟
- Generating Unit Tests with DeepSeek•3分钟
- Automating Technical Documentation•4分钟
- Fine-Tuning DeepSeek Models•1分钟
- Overview of the Fine-Tuning Process•7分钟
- Fine-Tuning your own DeepSeek model•10分钟
- Utilizing the Fine-Tuned Model•4分钟
- Course Closure - Gratitude !•1分钟
2篇阅读材料•总计30分钟
- Read more about DeepSeek for Developers: Code, Testing, and Documentation at Scale•15分钟
- Read more about Fine-Tuning DeepSeek: Customization, Deployment, and Best Practices•15分钟
3个作业•总计90分钟
- Graded Quiz: DeepSeek for Developers and Customization•60分钟
- Practice Quiz: Enhancing Software Development with DeepSeek•15分钟
- Practice Quiz: Fine-Tuning DeepSeek Models•15分钟
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提供方

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常见问题
This course offers a deep dive into DeepSeek’s architecture, training methods, and real-world applications. You’ll gain hands-on experience with API integration, local deployment, workflow automation, and advanced fine-tuning techniques.
It’s ideal for AI developers, software engineers, data scientists, product managers, and automation architects who want to apply DeepSeek to scalable, AI-powered solutions.
Yes. If you're new to DeepSeek, start with DeepSeek Essentials: From Foundations to Real-World Use. It covers core concepts and basic integrations before you move on to this advanced course for deeper technical mastery.
You’ll explore DeepSeek’s reasoning-centric design, Efficient Mixture of Experts (MoE), Multi-Head Latent Attention (MLA), and RLHF training—all of which contribute to its performance and flexibility.
Yes. You’ll deploy DeepSeek models using APIs and also set them up for local execution using LMStudio and open-source tools.
Absolutely. You’ll be guided through the full fine-tuning process—training, deploying, and applying your own customized models for real-world use.
You’ll learn to implement DeepSeek for RAG systems, intelligent agents, automated workflows, classification, and embeddings across industries like finance, education, and tech.
Yes. Each module has hands-on exercises and scenario-based tasks, including building a local RAG system and deploying AI agents.
You’ll explore DeepSeek APIs, LMStudio, Hugging Face, Cursor AI, Perplexity, GrokAPI, and no-code tools like Make.com and N8N.
The course is self-paced and typically takes 2–3 weeks to complete, depending on your schedule and learning pace.
To access the course materials, assignments and to earn a Certificate, you will need to purchase the Certificate experience when you enroll in a course. You can try a Free Trial instead, or apply for Financial Aid. The course may offer 'Full Course, No Certificate' instead. This option lets you see all course materials, submit required assessments, and get a final grade. This also means that you will not be able to purchase a Certificate experience.
When you purchase a Certificate you get access to all course materials, including graded assignments. Upon completing the course, your electronic Certificate will be added to your Accomplishments page - from there, you can print your Certificate or add it to your LinkedIn profile.
Yes. In select learning programs, you can apply for financial aid or a scholarship if you can’t afford the enrollment fee. If fin aid or scholarship is available for your learning program selection, you’ll find a link to apply on the description page.
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