Packt

Applied DeepSeek: Building Intelligent Systems

Packt

Applied DeepSeek: Building Intelligent Systems

Access provided by Xavier School of Management, XLRI

Gain insight into a topic and learn the fundamentals.
Intermediate level

Recommended experience

4 hours to complete
Flexible schedule
Learn at your own pace
Gain insight into a topic and learn the fundamentals.
Intermediate level

Recommended experience

4 hours to complete
Flexible schedule
Learn at your own pace

What you'll learn

  • Learn to design prompts and evaluate responses using DeepSeek in various domains.

  • Understand the process of building and deploying AI-powered applications with DeepSeek.

  • Develop skills to integrate DeepSeek into agent workflows for intelligent systems.

Details to know

Shareable certificate

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Assessments

3 assignments

Taught in English
Recently updated!

June 2026

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Build your subject-matter expertise

This course is part of the DeepSeek in Practice Specialization
When you enroll in this course, you'll also be enrolled in this Specialization.
  • Learn new concepts from industry experts
  • Gain a foundational understanding of a subject or tool
  • Develop job-relevant skills with hands-on projects
  • Earn a shareable career certificate

There are 3 modules in this course

This module explores real-world applications of DeepSeek-R1 through industry case studies, focusing on benchmarking, prompt engineering, and performance evaluation. Learners will gain hands-on experience in designing prompts, analyzing extraction errors, and comparing DeepSeek-R1 with other document parsing tools. Best practices for hybrid approaches and strategies for financial document extraction are also covered.

What's included

1 video10 readings1 assignment

This module guides learners through the practical implementation of DeepSeek models to solve real-world problems, including preparing health data, building and deploying APIs, and running inference both in the cloud and locally. Learners will gain hands-on experience with Docker, FastAPI, and various inference backends to operationalize AI solutions.

What's included

1 video9 readings1 assignment

This module introduces learners to building LLM-powered agents using DeepSeek, focusing on the integration of tools, workflows, and agentic applications. Through practical examples, such as summarizing scientific papers and orchestrator-worker patterns, learners will explore the challenges and solutions in developing effective AI agents.

What's included

1 video6 readings1 assignment

Earn a career certificate

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Instructor

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