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Build Intelligent Agents Using DeepSeek & N8N
Board Infinity
and
Mirza Rahim Baig
4.0
Based on 25 ratings
Board Infinity
and
Mirza Rahim Baig
We begin with the first module, where you’ll set up your automation environment and get familiar with the basics of n8n, DeepSeek, and AI-driven workflow planning.
The next module, the second module, covers building visual workflows using triggers, email nodes, and DeepSeek-powered agents to automate decisions and content generation.
In the third module, you’ll extract insights from PDFs and emails, classify them using AI, and organize outputs in Google Sheets with tools like Poppler.
In the final module, you'll test, debug, and deploy intelligent agents that are robust and production-ready.
Read more
We begin with the first module, where you’ll set up your automation environment and get familiar with the basics of n8n, DeepSeek, and AI-driven workflow planning.
The next module, the second module, covers building visual workflows using triggers, email nodes, and DeepSeek-powered agents to automate decisions and content generation.
In the third module, you’ll extract insights from PDFs and emails, classify them using AI, and organize outputs in Google Sheets with tools like Poppler.
In the final module, you'll test, debug, and deploy intelligent agents that are robust and production-ready.
Read more
We begin with the first module, where you’ll set up your automation environment and get familiar with the basics of n8n, DeepSeek, and AI-driven workflow planning.
The next module, the second module, covers building visual workflows using triggers, email nodes, and DeepSeek-powered agents to automate decisions and content generation.
In the third module, you’ll extract insights from PDFs and emails, classify them using AI, and organize outputs in Google Sheets with tools like Poppler.
In the final module, you'll test, debug, and deploy intelligent agents that are robust and production-ready.
By the end, you will:
- Understand the fundamentals of workflow automation using n8n and how to structure intelligent projects.
- Build end-to-end workflows using triggers, nodes, and real-world data sources such as Gmail and Google Sheets.
- Integrate DeepSeek into workflows to extract insights, classify data, and automate responses using large language models.
This course is ideal for:
-Business professionals automating repetitive tasks
-Startup founders looking to build AI-driven processes
-Product managers exploring no-code AI tools
-Enthusiasts interested in automation and intelligent systems
-Start building automation that works smarter—no code, just results.
Disclaimer: This course is an independent educational resource developed by Board Infinity and is not affiliated with, endorsed by, sponsored by, or officially associated with Deepseek & n8n or any of its subsidiaries or affiliates. This course is not an official preparation material of deepseek & n8n. All trademarks, service marks, and company names mentioned are the property of their respective owners and are used for identification purposes only.
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What's inside
Syllabus
Foundations of Workflow Automation and Project Setup
This module establishes the foundational understanding required to begin building intelligent agent workflows using N8N and DeepSeek. It starts by introducing the core concepts of workflow automation, emphasizing how automation platforms like N8N can orchestrate tasks across systems efficiently. Learners will explore the architecture, benefits, and use cases of N8N, gaining clarity on its node-based interface, trigger mechanisms, and integration capabilities. The module also guides learners through the complete setup process—installing N8N locally or on the cloud, connecting it to external services, and preparing it to interface with DeepSeek models.
By the end of this module, learners will have a working automation environment, a clear mental model of how intelligent agents operate within workflows, and the foundational skills to begin designing their own AI-powered automation projects.
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Syllabus
Foundations of Workflow Automation and Project Setup
This module establishes the foundational understanding required to begin building intelligent agent workflows using N8N and DeepSeek. It starts by introducing the core concepts of workflow automation, emphasizing how automation platforms like N8N can orchestrate tasks across systems efficiently. Learners will explore the architecture, benefits, and use cases of N8N, gaining clarity on its node-based interface, trigger mechanisms, and integration capabilities. The module also guides learners through the complete setup process—installing N8N locally or on the cloud, connecting it to external services, and preparing it to interface with DeepSeek models.
By the end of this module, learners will have a working automation environment, a clear mental model of how intelligent agents operate within workflows, and the foundational skills to begin designing their own AI-powered automation projects.
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Career center
Learners who complete Build Intelligent Agents Using DeepSeek & N8N will develop knowledge and skills
that may be useful to these careers:
Business Process Automation Specialist
Business Process Automation Specialist
A Business Process Automation Specialist designs, implements, and maintains systems that automate repetitive and routine business tasks, significantly enhancing operational efficiency across an organization. This course offers a comprehensive foundation for this career, specifically demonstrating how to "automate real-world business tasks using n8n, DeepSeek.ai, and prompt engineering—without writing code." Learners gain direct experience in "building end-to-end workflows using triggers, nodes, and real-world data sources" like Gmail and Google Sheets. For aspiring Business Process Automation Specialists, this course is tremendously valuable, equipping you to "structure intelligent projects," understand the "fundamentals of workflow automation" from setup to deployment, and deliver concrete, automated business solutions efficiently.
AI Workflow Designer
AI Workflow Designer
An AI Workflow Designer crafts intricate automation sequences that leverage artificial intelligence for dynamic decision-making and intelligent responses, creating adaptive and smart operational frameworks. This course equips you with the precise skills needed, focusing on "designing intelligent workflows with N8N and LLMs." You will learn to integrate large language models like DeepSeek to enable "dynamic decision-making, content generation, data transformation, and human-like interaction." The practical exercises in "architecting intelligent agents that can analyze inputs, respond intelligently, and trigger further actions" make this course ideal for anyone aspiring to master the creation of sophisticated, AI-powered automation solutions.
No Code Automation Developer
No Code Automation Developer
A No Code Automation Developer builds robust and efficient automated solutions using visual interfaces and pre-built components rather than traditional programming. This career path is perfect for those who seek to create functional applications and workflows rapidly. This course aligns perfectly, enabling you to "create intelligent, no-code workflows that extract, process, and respond to data using AI tools." You will learn to "set up your automation environment and get familiar with the basics of n8n," mastering its node-based interface to construct complex systems. For a No Code Automation Developer, the course's emphasis on "no code, just results" and practical deployment of "production-ready" intelligent agents offers a direct pathway to success in this quickly growing field.
Prompt Engineer
Prompt Engineer
A Prompt Engineer specializes in designing, refining, and optimizing inputs for large language models to elicit desired outputs and behaviors, which is critical for maximizing AI effectiveness. This course dives deep into the practices of a Prompt Engineer, explicitly covering "prompt engineering within workflows" and how to achieve "precise information extraction—without relying on agent nodes—by mastering prompt engineering." Through the course, you will learn to integrate DeepSeek into workflows to "extract insights, classify data, and automate responses using large language models," making you proficient in guiding AI for diverse tasks. This specialized focus renders the course exceptionally beneficial for this emerging and in-demand career.
Automation Engineer
Automation Engineer
An Automation Engineer designs, implements, and maintains automated systems and software to streamline processes and improve efficiency, requiring a systematic approach to developing resilient and scalable solutions. This course provides a strong foundation for an Automation Engineer by focusing on "building end-to-end workflows" and ensuring they are "robust and production-ready." The module on "Error Handling, and Deployment" is particularly relevant, covering "techniques for logging, monitoring, and testing workflows to ensure operational resilience" and guiding deployment to various environments. This hands-on experience in building and deploying intelligent agents, combined with a focus on reliability, is a tremendous asset for this demanding engineering role.
Solutions Architect Automation
Solutions Architect Automation
A Solutions Architect Automation designs comprehensive and scalable automation solutions, outlining the technical framework and components required to meet specific business needs, merging strategic planning with deep technical understanding. This course provides a robust skill set for a Solutions Architect Automation, teaching how to "structure intelligent projects" and "architect intelligent agents that can analyze inputs, respond intelligently, and trigger further actions." You will gain experience in setting up automation environments and integrating AI tools, which is fundamental to designing coherent and effective automation landscapes. The ability to build "end-to-end workflows" using various data sources equips you to design holistic automation strategies.
AI Operations Specialist
AI Operations Specialist
An AI Operations Specialist is responsible for the reliable deployment, monitoring, and maintenance of artificial intelligence systems and automated workflows in production environments, ensuring optimal and consistent function. The course offers highly relevant skills for an AI Operations Specialist, particularly through its "Error Handling, and Deployment" module. Learners understand "techniques for logging, monitoring, and testing workflows to ensure operational resilience" and learn to "move workflows from development to production environments." This practical knowledge regarding "delivering stable, maintainable, and production-ready automation solutions powered by LLMs" is essential for managing the full lifecycle and performance of intelligent agents in real-world settings.
Digital Transformation Consultant
Digital Transformation Consultant
A Digital Transformation Consultant advises organizations on adopting new technologies and strategies to modernize operations, enhance customer experiences, and achieve strategic goals, often integrating innovative AI and automation solutions. This course may be useful for an aspiring Digital Transformation Consultant as it empowers individuals to "build AI-driven processes" and "automate real-world business tasks using n8n, DeepSeek.ai, and prompt engineering—without writing code." Understanding how to deploy "intelligent agents that are robust and production-ready" provides a valuable perspective on the practical implementation of transformative technologies, enabling you to guide clients with concrete, deployable solutions for modern business challenges.
Product Manager No Code AI
Product Manager No Code AI
A Product Manager No Code AI champions the development and lifecycle of products that leverage no-code platforms and artificial intelligence, involving market understanding, product vision, and execution oversight. The course may be useful for a Product Manager No Code AI, as it is explicitly designed for "Product managers exploring no-code AI tools." By learning to "build AI-driven processes" and "create intelligent, no-code workflows," you will gain a deep understanding of the capabilities and limitations of such technologies. This hands-on knowledge is invaluable for defining feasible product roadmaps and communicating effectively with development and business teams about the potential of no-code AI solutions.
Data Integration Specialist
Data Integration Specialist
A Data Integration Specialist designs and implements systems that combine data from disparate sources, ensuring data consistency, accessibility, and reliability for analysis and operational use. The role is foundational for data-driven organizations. This course may be useful for a Data Integration Specialist, offering practical experience in handling varied data inputs and outputs. You will learn to "build end-to-end workflows using ... real-world data sources such as Gmail and Google Sheets." Specifically, the course covers "extracting insights from PDFs and emails, classify them using AI, and organize outputs in Google Sheets," which directly applies to connecting and transforming data streams into organized, actionable information for various business applications.
Operations Process Improvement Specialist
Operations Process Improvement Specialist
An Operations Process Improvement Specialist analyzes existing operational workflows, identifies inefficiencies, and designs and implements solutions to enhance productivity, quality, and cost-effectiveness, driving significant organizational gains. This course may be useful for an Operations Process Improvement Specialist as it provides practical tools to "automate real-world business tasks" and "build AI-driven processes" without writing code. You will learn to "create intelligent, no-code workflows that extract, process, and respond to data using AI tools," directly equipping you to implement tangible improvements. By understanding how to deploy "robust and production-ready" intelligent agents, you can strategically identify and execute automation initiatives that optimize operational performance.
Business Analyst Automation
Business Analyst Automation
A Business Analyst Automation identifies business needs, analyzes existing processes, and recommends automation solutions to improve efficiency and effectiveness, bridging the gap between business requirements and technical implementation. This course may be useful for a Business Analyst Automation by providing a tangible understanding of what is achievable with no-code AI and automation. By learning to "automate real-world business tasks" and "build intelligent agents that extract, process, and respond to data," you will be better equipped to identify opportunities for process improvement. The ability to design and conceptualize "end-to-end workflows" empowers you to define clear, impactful, and implementable automation strategies for various business functions.
AI Content Creator
AI Content Creator
An AI Content Creator leverages artificial intelligence tools to generate, optimize, and manage various forms of digital content, from text to creative assets, as AI capabilities advance. This course may be useful for an AI Content Creator, as it introduces how to integrate Large Language Models like DeepSeek into workflows for "content generation." You will explore "designing workflows that combine traditional automation logic with generative AI capabilities," enabling dynamic content creation tailored to specific needs. This foundational understanding of orchestrating AI for automated content processes allows you to explore innovative methods for producing and distributing content efficiently and at scale.
Technical Support Automation Tools
Technical Support Automation Tools
A Technical Support Automation Tools professional provides expert assistance and troubleshooting for users of automation platforms and intelligent agent systems, vital for ensuring smooth operation and user adoption. This course may be useful for a Technical Support Automation Tools professional. The "Error Handling, and Deployment" module specifically covers "techniques for logging, monitoring, and testing workflows to ensure operational resilience," which are essential skills for diagnosing and resolving issues effectively. Understanding the architecture of n8n workflows and how DeepSeek integrates allows for more effective technical guidance and problem-solving, making you a more proficient and insightful support provider for complex automation challenges.
Knowledge Management Analyst
Knowledge Management Analyst
A Knowledge Management Analyst focuses on identifying, organizing, storing, and disseminating information within an organization to improve efficiency and decision-making, ensuring valuable insights are accessible and utilized. This course may be useful for a Knowledge Management Analyst because it teaches how to "extract insights from PDFs and emails, classify them using AI, and organize outputs in Google Sheets." This direct experience in automating the collection, classification, and structuring of information is highly relevant. The ability to build intelligent agents that can process and categorize data efficiently helps to streamline the creation and maintenance of organizational knowledge bases, enhancing overall information governance.
For more career information including salaries, visit:
OpenCourser.com/course/70dajc/build
Reading list
We haven't picked any books for this reading list yet.
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This foundational textbook in the field of deep learning, covering a wide range of topics from basic concepts to advanced techniques. It is essential for gaining a broad understanding of the neural networks and architectures that underpin models like DeepSeek. While published in 2016, its comprehensive nature makes it a valuable reference and is often used as a textbook in academic institutions.
A widely recognized and comprehensive textbook covering the fundamentals of Natural Language Processing (NLP). Understanding NLP is crucial for comprehending how models like DeepSeek process and generate human language. provides a strong theoretical foundation and is often used in both undergraduate and graduate NLP courses.
Provides a practical, hands-on approach to understanding and implementing Transformer models, which are the core architecture behind most large language models, including DeepSeek. Co-authored by Hugging Face engineers, it's highly relevant for anyone looking to work with or understand the technical underpinnings of modern LLMs. The revised edition valuable and up-to-date resource.
Focusing specifically on generative models, this book is highly relevant to understanding the capabilities of DeepSeek in generating text and potentially other forms of content. It covers various generative techniques, including Transformers, providing insights into the models that enable creative AI applications. The second edition recent publication.
A very popular and practical guide to machine learning and deep learning. While not exclusively focused on LLMs or generative AI, it provides essential hands-on experience with key libraries and concepts necessary for working with and understanding the models that power DeepSeek. The third edition recent and widely used reference.
This concise book offers a high-level overview of essential machine learning concepts. It's excellent for quickly gaining a broad understanding of the field without getting bogged down in excessive detail, making it suitable for those new to ML or seeking a rapid review of fundamentals relevant to AI technologies like DeepSeek.
Dives into the details of Transformer models and their application in NLP. It covers building models from scratch, providing a solid technical understanding of the architecture that is fundamental to large language models like DeepSeek. Suitable for those with a strong technical background wanting to master Transformers.
This textbook presents AI as the study of designing intelligent computational agents, offering a coherent and updated overview of the field. The third edition includes recent AI advances. It provides a solid foundation in AI concepts relevant to building intelligent systems, including those involving language processing.
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Written by the creator of Keras, this book offers a practical introduction to deep learning using Python. It's known for its clear explanations and hands-on examples, making complex concepts accessible. The second edition is updated and a valuable resource for practitioners.
Focuses on applying machine learning using the scikit-learn library in Python. While not covering deep learning in detail, it provides a strong foundation in fundamental ML concepts and practical skills that are useful prerequisites for understanding and working with more complex models like LLMs.
A widely used introductory book to NLP using the NLTK library in Python. It covers fundamental NLP concepts and techniques with a practical approach. While some topics might be more basic than the advanced models like DeepSeek, it provides a necessary foundation in text processing.
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Focuses on Generative Adversarial Networks (GANs), a type of generative model relevant to creating realistic data. While LLMs primarily use transformer architectures, understanding GANs provides broader context in generative AI and practical guide for implementation.
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Written by a leading AI researcher, this book explores the long-term future of AI and the challenge of ensuring that increasingly intelligent systems remain beneficial to humanity. It's a thought-provoking read on the potential risks and challenges associated with advanced AI.
Examines the technical challenges and approaches to building algorithms that are fair, accountable, and transparent. It's relevant for understanding the ethical considerations in developing and deploying AI systems, including LLMs, and provides insights into designing responsible AI.
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Co-authored by a co-founder of DeepMind and Inflection AI, this book explores the transformative impact of AI and other frontier technologies on society. It discusses the challenges of controlling powerful technologies like advanced AI, offering a contemporary perspective on the broader implications of developments like DeepSeek.
Offers a unique perspective by guiding the reader through the process of building an LLM from the ground up. This hands-on approach provides a deep understanding of the internal workings of these models, which is highly relevant to comprehending how DeepSeek is built and trained.
Focuses specifically on Transformer architectures and their applications in NLP. It covers various Transformer models and provides practical guidance on using them. It's a good resource for understanding the specific architecture that makes LLMs powerful.
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As AI becomes more integrated into society, understanding the ethical implications is crucial. provides an accessible overview of the ethical considerations surrounding AI, including LLMs. It's important for developing a responsible approach to using powerful models like DeepSeek.
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Offers a critical perspective on the broader societal impact of AI, examining its political and environmental costs. While not technical, it provides essential context for understanding the larger implications of powerful AI models and the industry surrounding them.
For more information about how these books relate to this course, visit:
OpenCourser.com/course/70dajc/build
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Rating
4.0
Effort
4 weeks of study, 5 Hours/ Week
Level
Introductory
Via
Coursera
Institution
Board Infinity
Instructors
Board Infinity
Mirza Rahim Baig
Session
November 3, 2025
- December 8, 2025
Language
English
Transcript
Español
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