Build real AI-powered automations, workflows, and agents β from APIs to RAG to full production systems.
β±οΈ Length: 3.2 total hours
π₯ 5 students
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- Course Overview: Rapid AI Deployment Strategy – This intensive 18-day sprint is meticulously engineered to transform you from a traditional developer or business analyst into a high-functioning AI Automation Engineer. Over the course of less than three weeks, you will move beyond basic chatbot interactions to architecting complex, multi-layered systems that bridge the gap between static data and dynamic, intelligent action.
- Course Overview: The Agentic Evolution – We focus heavily on the shift from simple automation to autonomous agents. You will explore how to build digital workers that do not just follow linear instructions but can reason, plan, and self-correct using advanced feedback loops and iterative logic structures.
- Course Overview: Production-Grade Engineering – Unlike introductory tutorials, this course emphasizes the “Production” aspect of AI. You will learn the rigorous standards required to move a script from your local machine into a scalable, cloud-hosted environment where it can serve real users and handle high-volume data streams reliably.
- Course Overview: Hybrid Architecture Focus – The curriculum balances the use of low-code orchestration platforms for speed and high-code Python environments for ultimate flexibility. This dual-track approach ensures you can choose the most cost-effective and efficient tool for any specific business problem you encounter in the wild.
- Requirements / Prerequisites: Foundational Logic Proficiency – Students should possess a strong grasp of logical sequencing and “if-this-then-that” thinking. While deep programming knowledge is not a hard barrier, an understanding of variables, loops, and data types will significantly accelerate your ability to keep up with the fast-paced 18-day schedule.
- Requirements / Prerequisites: API Ecosystem Access – To follow the practical builds, you must have active accounts and available credits for essential AI providers, primarily OpenAI and Anthropic. The course relies on live API calls to demonstrate real-world latency, cost management, and response variations that cannot be simulated through theoretical study alone.
- Requirements / Prerequisites: Toolset and Environment – A modern computing environment capable of running Python and a code editor like Visual Studio Code is required. Additionally, a willingness to work with middleware platforms like Make.com or Zapier is essential for the modules focused on rapid workflow prototyping and third-party application connectivity.
- Skills Covered / Tools Used: Vector Database Management – Master the art of high-dimensional data storage using industry-leading tools like Pinecone or Weaviate. You will learn how to transform raw text into embeddings, store them efficiently, and retrieve them with high precision to fuel context-aware AI applications.
- Skills Covered / Tools Used: Advanced RAG Pipelines – Beyond simple document retrieval, you will build Retrieval-Augmented Generation systems that utilize reranking algorithms, query expansion, and semantic chunking to ensure the AI provides the most accurate and relevant information possible from your private datasets.
- Skills Covered / Tools Used: Orchestration Frameworks – Deep dive into the mechanics of LangChain and LlamaIndex. These tools are the backbone of modern AI development, and you will learn how to use them to manage state, memory, and complex chains of thought within your automated workflows.
- Skills Covered / Tools Used: Webhook and Event-Driven Logic – Learn to create reactive systems that respond instantly to external stimuli. Whether it is a new CRM entry, a Slack message, or an incoming email, you will build listeners that trigger your AI agents to perform specific tasks without manual intervention.
- Skills Covered / Tools Used: Performance Monitoring and Logging – Implement observability tools to track how your AI agents are performing. You will learn to monitor for “hallucinations,” track token consumption for budget control, and log interactions to continuously improve the accuracy of your models over time.
- Benefits / Outcomes: Exponential Productivity Gains – By the conclusion of the 18 days, you will have the skills to automate hundreds of hours of manual labor. This allows you to scale your output or your business’s operations without the linear cost of hiring more staff, effectively “cloning” yourself through digital agents.
- Benefits / Outcomes: Proprietary Knowledge Monetization – You will gain the ability to turn static company wikis, PDF libraries, and internal databases into interactive, intelligent assets. This skill is highly sought after by enterprises looking to leverage their private data safely and effectively with LLMs.
- Benefits / Outcomes: Professional Portfolio Development – Every student leaves with a suite of functional, production-ready AI tools. These projects serve as a powerful proof-of-concept for potential employers or freelance clients, demonstrating your ability to build real-world solutions rather than just theoretical toys.
- Benefits / Outcomes: Strategic Technological Advantage – In an era of rapid AI disruption, this course provides you with the “builder’s edge.” You will not just be a consumer of AI tools but a creator, capable of custom-building the exact automation solutions required to solve unique and complex competitive challenges.
- PROS: Project-Centric Learning – The course skips the fluff and focuses on building real systems from day one, ensuring that every hour spent translates directly into a tangible technical asset.
- PROS: Cutting-Edge Tech Stack – The curriculum is updated to include the latest models and libraries (2024/2025 standards), meaning you won’t waste time on deprecated techniques or outdated API versions.
- PROS: Rapid Skill Acquisition – The 18-day format is designed for maximum retention and momentum, making it ideal for professionals who need to upskill quickly without committing to a multi-month academic program.
- CONS: High Intensity – The condensed timeframe and technical depth of the production-level workflows may prove overwhelming for absolute beginners who lack basic familiarity with web technologies or data structures.
Learning Tracks: English,IT & Software,Other IT & Software
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