Coyotiv

Cohort 1

This immersive four-week program equips developers and tech professionals with the practical skills to architect and deploy cutting-edge generative AI applications. Moving beyond theoretical concepts, participants will build functional AI systems spanning text generation, multimodal applications, intelligent knowledge retrieval, and multi-agent architectures. By the end of this hands-on course, you'll have developed your own AI application while mastering the latest frameworks, ethical considerations, and architectural patterns that define the emerging field of generative AI engineering. The landscape of software development is undergoing a paradigmatic shift with the emergence of generative AI technologies. This course provides a structured pathway into this revolution, beginning with the fundamental mechanics of Large Language Models and progressing to sophisticated multi-agent systems. Throughout the program, participants will engage with both the theoretical underpinnings and practical implementations of generative AI, gaining hands-on experience with industry-standard tools and frameworks. Week 1 establishes a foundation in text generation, exploring the mathematical principles behind vector embeddings, token prediction, and emergent behaviors in LLMs. Participants will implement their first AI applications using OpenAI's APIs, learning to craft effective system prompts and protect against prompt engineering attacks. Through practical exercises, students will understand how to structure AI conversations and implement function calling to expand AI capabilities beyond language generation. Week 2 expands into multimodal AI applications, focusing on voice generation and real-time voice-to-voice agents. The course examines technical implementations of text-to-voice technologies through platforms like 11Labs, along with ethical considerations surrounding voice cloning and authentication. Participants will explore real-world applications across accessibility, education, and content creation while building their own multimodal AI projects. Week 3 introduces Retrieval Augmented Generation (RAG) and vector search technologies, addressing the limitations of traditional LLMs through external knowledge integration. The curriculum covers vector embeddings, similarity measures, and the nuanced challenges of document chunking. Students will learn advanced techniques like Generation Augmented RAG (GARAGE) for multi-dimensional categorization and searching, applying these concepts to practical challenges like resume parsing and knowledge base construction. Week 4 culminates with multi-agent systems, exploring how networks of specialized AI agents can collaborate to solve complex problems. The course examines advanced reasoning techniques, including Chain of Thought, Tree of Thoughts, and Graph of Thoughts, alongside memory management strategies for agent persistence. Through demonstration of frameworks like Autogen, participants will understand the coordination models and communication patterns that enable truly autonomous systems, preparing them to design their own multi-agent architectures.

Shape the Future with Generative AI. Build. Innovate. Lead.

Course syllabus

Once a week, 1.5 hours per session

Choose Tuesdays or Wednesdays

Start Date

Learn while building with peer-to-peer project sessions

Weekly projects

Course schedule

AI-Curious Devs and Engineers with third-party REST API experience who want to build advanced AI-driven applications

Ambitious Career-Changers with basic coding knowledge and API experience who are eager to break into AI development

CTOs, Team Leads, and Managers who see AI as a tool for their teams to stay ahead by learning how to build and deploy better AI-powered apps

Product Manager or Designers seeking technical AI fluency to make generative AI a crucial part of their product vision

Who this course is for

What you’ll get out of this course

You'll work on real-world projects, pushing the limits of AI and gaining hands-on experience implementing architectures that follow emerging best practices and design patterns for enterprise-grade AI systems.

Hands-On AI Engineering with Production-Ready Patterns

Work directly with APIs and GPT models, vector databases, and multi-agent frameworks. Gain hands-on experience with prompt engineering, function calling, multimodal integration, vector embedding, and agent coordination that translates directly to production environments.

Practical Implementation Experience

Develop a nuanced understanding of the implications, limitations, and challenges in deploying genAI systems. Learn strategies for addressing concerns on voice cloning, information accuracy and environmental impact while designing systems that responsibly leverage AI capabilities.

Ethical and Practical Considerations

Whether you're coming from a traditional dev background or already experimenting with AI, you'll master the essential&nbsp;glossary&nbsp;of AI development terms and learn how to translate your existing coding skills into powerful AI implementations that solve real business problems.

Bridge the Gap from Code to AI Engineering
 

Develop a comprehensive portfolio piece under expert guidance, demonstrating your ability to architect and implement sophisticated AI systems. This tangible asset will showcase your capabilities to employers or clients, or guide your current team towards new possibilities.

Build Your AI Portfolio with Guided Projects

Showcase your creativity by presenting your AI-powered project live to the cohort. Get valuable feedback, share insights, and celebrate what you've built with fellow developers.

Peer-Led Demo Day

Join our dedicated Slack community and level up your learning together. The course structure encourages open-source collaboration and knowledge sharing. Celebrate your progress, collaborate on challenges, and build relationships with fellow AI buiders.

Community Support

Earn your certification from <a href="https://www.coyotiv.com/" rel="noopener noreferrer" target="_blank">Coyotiv School of Software Engineering</a>—proof of what you've built and what you’ve learned.

Certify Your Learning

Build AI apps that matter. Learn fast, launch quickly and scale for lasting impact.

Armagan Amcalar

Speaker, Leader, Mentor

Not Every App Needs AI. Does Yours?

Armağan Amcalar

Founder of Coyotiv. CTO at Neol and OpenServ. 20+ years building tech platforms.

Discover when AI creates real value, and how to align it with what your product actually needs.

Find the Right Fit for AI

Learn clear, practical methods to evaluate your use case and make confident tech choices.

Use Smart Decision Frameworks

Learn how to focus your AI efforts on features that drive real value for your users and your product.

Prioritize What Really Matters

Can't make it this week? Signup to get a recording of the live event.

⚡ Join live to get 25% off the full course! ⚡

Founder of Coyotiv. CTO at Neol and OpenServ. 20+ years building tech platforms

Can't make it on Wednesday? I'll host this session at the same time again on Friday the 27th.

Turn GenAI Into Real ROI: Speed vs Quality vs Cost

Learn why speed, quality and cost can’t all be optimized at once, and how understanding these dynamics gives you an edge

Understand What Trade-Offs Look Like In GenAI

Not every GenAI solution needs to be perfect. Let's talk about where to invest for maximum impact and ROI

Know When to Sacrifice and When to Double Down

Walk away with practical strategies to make better decisions, whether you build side projects or deploy enterprise AI

Learn More About How to Build Frameworks That Scale With You

Can't make it on Tuesday? 
I'll host this session at the same time again on Thursday the 26th.

Can't make it on Monday? I'll host this session at the same time again on Wednesday 25th and at 13:00 CET Friday 27th.

Building Real-World Apps With GenAI

Founder of Coyotiv. Fractional CTO. 20+ years building tech teams and platforms.

Get the opportunity to get to know me and how I can help you become a confident builder of AI applications.

Build Real-World GenAI Apps With A Guide Who's Been There

Let's talk about what it *really* takes to launch an app in just four weeks.

Learn What Separates GenAI Tinkering From GenAI Shipping

We'll get into solving real problems for real people + understanding how you can evaluate the usefulness of your ideas.

Want to Build Something People Care About? Start Here.

Q&A: Building Real-World Apps With GenAI

Get your questions answered on things like contextual prompting, debugging, code co-creation, and output evaluation.

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