Advanced GEN AI
Become a Certified GenAI Architect! This advanced, hands-on
At a Glance
8
Modules
40
Hours of Training
∞
Frameworks & Insights
Learn how to Design GenAI Architecture for Scalable Business Solutions
Ready to lead with GenAI? This course is designed for professionals who want to move beyond the basics and start building real, scalable AI solutions. You’ll learn how to create smarter, more reliable AI systems, integrate them into your workflows, and bring them to life in real business environments. It’s a hands-on, practical program that gives you the confidence and skills to turn GenAI from a concept into a competitive advantage.
Get Certified
CERTIFICATE OF COMPLETION UPON COURSE COMPLETION
DURATION
5 WEEKS
Training Type
ON DEMAND TRAINING
What to Expect
HANDS ON GEN AI FRAMEWORKS AND USE CASES
Info & About
About
Curriculum
Training Benefits
About
The Gen AI Architecture Certificate is an advanced, hands-on program designed for developers and technical teams who want to move beyond basic AI experimentation and build robust, production-ready Generative AI applications. This course is ideal for professionals aiming to architect, implement, and deploy intelligent systems that combine the latest advances in language models, retrieval-augmented generation (RAG), and knowledge-augmented generation (KAG).
As organizations increasingly demand scalable, secure, and explainable AI solutions, this program delivers practical frameworks, real-world coding exercises, and architectural best practices—without unnecessary jargon or abstract theory. Participants gain a deep understanding of how to design, build, and maintain GenAI systems that are not only powerful but also reliable and enterprise-ready.
The curriculum bridges the gap between cutting-edge AI technology and real business needs by focusing on:
- Advanced prompt engineering and reasoning strategies,
- Hybrid architectures that combine unstructured and structured knowledge,
- Multimodal AI development (text, images, audio, and more),
- Building and deploying scalable, secure, and observable AI systems,
- Creating intelligent agents and autonomous workflows,
- And designing user interfaces for effective AI interaction and prompt management.
By the end of the course, participants are not just familiar with GenAI concepts—they are equipped to architect, build, and deploy advanced AI applications, critically evaluate AI tools and frameworks, and drive real business value through intelligent automation and innovation.
Who does it Concern:
- Software Developers looking to transition into AI engineering
- Full-Stack Engineers seeking to integrate AI capabilities into applications
- Technical Leads responsible for AI implementation strategies
- Product Managers with technical backgrounds wanting hands-on AI experience
- Enterprise Development Teams modernizing with AI technologies
Desired Proficiency Level
Technical Skills
- Solid programming experience, ideally in TypeScript (preferred) or Python
- Familiarity with modern software development tools (e.g., code editors, version control, package managers).
- Understanding of core data structures (arrays, objects/dictionaries, lists, sets).
- Experience working with APIs (RESTful or similar) and handling JSON data.
AI & Machine Learning Background
- Basic knowledge of AI or machine learning concepts (such as embeddings, language models, or vector search).
- Prior exposure to large language models (LLMs), retrieval-augmented generation (RAG), or knowledge graphs (KAG) is highly recommended.
- Comfort with using AI/ML libraries or frameworks (e.g., Hugging Face, LangChain, or similar) is a plus.
Development Practices
- Ability to set up and manage development environments (installing dependencies, using virtual environments or containers).
- Familiarity with deploying applications (locally or to the cloud) is helpful but not required.
Other Skills
- Comfort reading and understanding technical documentation.
- Willingness to engage in hands-on coding exercises and collaborative project work.
Technology Stack
- Core Technologies: – TypeScript, Node.js, Express – React, Next.js for frontend development
- AI Frameworks & SDKs: – OpenAI SDK, Anthropic SDK (Claude), Google GenAI SDK (Gemini) – Vercel AI SDK, LangChain, Mastra, VoltAgent, LLM-EXE
- Vector Databases & Knowledge Systems: – pgvector, Pinecone, Weaviate, Qdrant, Milvus
- AI Models: – GPT-4, Claude, Gemini, LLaMA, Mistral
AI Transformation Through Practical
Team Training
Organizations investing in this training can expect faster and more confident AI adoption, with teams capable of delivering production-ready AI features in weeks rather than months. By developing multi-provider expertise across leading platforms such as OpenAI, Anthropic, and Google, organizations significantly reduce vendor lock-in and retain strategic flexibility. The program builds a strong foundation in cost optimization, enabling teams to understand token economics and design efficient, scalable AI usage patterns. A TypeScript-first, type-safe development approach enhances quality assurance by minimizing runtime errors and improving system reliability.
Ultimately, organizations gain a competitive advantage through the ability to design and deploy sophisticated AI agents and multimodal systems tailored to real business needs.
Become a GenAI-Ready Expert
Take your career to the next level with production-grade GenAI engineering skills designed for real-world impact. The course adopts a TypeScript-first approach, leveraging strong typing, enterprise-grade tooling, and seamless web ecosystem integration—moving beyond Python-only workflows. With a production-ready mindset, every module focuses on real implementation challenges, including error handling, streaming architectures, cost optimization, and security.
Hands-on learning is at the core, with over 67% of the program dedicated to practical labs and projects, ensuring you build, test, and refine working GenAI systems. You’ll gain exposure to multiple AI frameworks, enabling confident technology selection, while advanced enterprise modules prepare you to design scalable, monitored, secure, and deployable AI solutions built for modern business environments.
FAQ
What will I learn in this course?
You’ll learn production-grade techniques that separate hobbyist projects from enterprise systems:
- Advanced prompt patterns (Chain-of-Thought, ReAct, Self-Ask) with injection protection
- RAG+KAG hybrid systems combining retrieval with knowledge graphs
- Multimodal AI processing text, images, audio, and video
- Autonomous agents that reason, plan, and execute complex tasks
- Enterprise architecture with monitoring, security, and scalability
- Prompt engineering UI patterns for building AI-powered interfaces
What will I be able to build after completing this course?
Advanced projects include:
- Chain-of-Thought reasoning system with prompt injection protection
- Hybrid RAG+KAG system with knowledge graph integration
- Multimodal search application (text, image, audio)
- Autonomous agent with tool use and memory
- Enterprise-grade AI system with monitoring and security
- Prompt engineering platform with version control
- Final project: Production-ready AI system of your choice
Why does this course use TypeScript instead of Python?
TypeScript offers superior type safety, better tooling, and seamless integration with modern web applications and enterprise systems. Most production AI applications require full-stack integration—TypeScript allows you to build end-to-end AI solutions without switching languages. You’ll learn to work with AI SDKs and APIs in the same language used by your frontend and backend teams, making you immediately valuable in real-world development environments.
Who is this course designed for?
This program is tailored for full-stack developers, TypeScript/JavaScript engineers, technical product managers, and ambitious professionals who want to master AI engineering using modern web technologies. It’s ideal for those already working in TypeScript ecosystems who want to add GenAI capabilities to their skillset without learning Python.
What topics and technologies will be covered?
The curriculum covers core GenAI concepts, integrating with LLM providers (OpenAI, Anthropic, Google), building RAG systems with TypeScript, advanced prompting techniques, semantic search, vector databases, AI agent development, and production deployment patterns. You’ll work with industry-standard TypeScript libraries and frameworks used in enterprise AI development.
Will I receive a certificate of completion?
Yes! Upon successfully completing the Gen AI Foundations course, you will receive a Certificate of Completion recognizing your hands-on expertise in Generative AI. This certificate demonstrates your ability to work with LLMs, build RAG systems, and deploy real-world AI applications, making it a valuable addition to your professional credentials.
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