Future is Agentic. Be Ready.

Agentic AI Developer Certification Program

A free, self-paced certification that teaches you to design, build, and deploy agentic AI systems.

You’ll complete three hands-on projects; each finished project earns a micro-certificate.

Finish all three to earn the Agentic AI Developer Certificate.

Stack: LangChain, LangGraph, vector databases/RAG, guardrails & testing, and production-readiness.

Certification is Free — Including Expert Feedback

The certification program is completely free. All participants who complete the requirements will receive an official Agentic AI Developer Certificate.

You’ll have access to lectures, articles, project instructions, and templates — all at no cost.

Project submissions are reviewed by experts. You'll receive feedback based on practical, industry-based expectations.

How to Join the Free Agentic AI Certification Program

New to Ready Tensor?

1. Create your free account here.

2. After signup, complete the quick onboarding:

• Add your name (plus optional location, organization, short bio)

• Select topics you’re most interested in

• On the “What brings you to Ready Tensor?” page, find Join our certification program and click Join the Program under Agentic AI Developer Certification Program

3. You’ll be enrolled immediately and taken to the Welcome & Orientation page.

Already have an account?

1. Log in to your account.

2. Go to the Ready Tensor Certifications hub.

3. Click Join Hub at the top of the page to enroll. (If you don’t see the button, you’re already enrolled.)

What You’ll Learn

Module 1: Foundations of Agentic AI

• Master core agentic concepts: planning, tool use, memory, and when agents beat workflows

• Build modular prompts, structured outputs, and semantic retrieval with vector databases

• Create your first RAG-powered assistant with LangChain and conversation memory

• Project: Deploy a question-answering AI with custom document knowledge

Module 2: Architecting Multi-Agent Systems

• Design stateful agent workflows using LangGraph with loops, tools, and observability

• Build collaborative multi-agent systems with specialized roles and coordination patterns

• Integrate external tools via MCP protocol and evaluate system performance with RAGAS/DeepEval

• Project: Create a multi-agent system with 3+ specialized agents solving real problems

Module 3: Real-World Readiness

• Implement testing strategies, security guardrails, and safety validation for production AI

• Deploy with FastAPI/Streamlit, add monitoring/logging, and design resilient failure handling

• Master observability tools and compliance considerations for enterprise deployment

• Project: Transform your multi-agent system into a production-ready application with full testing suite

Who Is This For?

This program is ideal for technically inclined learners who want to build real-world agentic AI systems.

Whether you're a data scientist, AI engineer, or product builder, if you want to go beyond prompting and start designing AI systems with memory, tools, and autonomy — this program is for you.

Ideal for:

• AI/ML Developers and Software Engineers

• Data Scientists and NLP Enthusiasts

• Students in AI, ML, or Analytics Programs

• Technical Product Builders and PMs

⚠️ Note: This is a code-driven program. Programming experience is required.

Why This Matters (Right Now)

We’re entering the age of autonomous agents. LLMs are no longer just chatbots — they’re software components.

If you want to stay relevant in tech and AI, you need to learn how to build agentic systems that plan, reason, use tools, and act autonomously.

Benefits:

• Future-proof your skills by learning cutting-edge agentic AI concepts

• Build real-world systems that employers care about

• Master the tools behind today’s most advanced AI applications

How Certification Works

You’ll get free, full access to all program lessons, video walkthroughs, and code repositories.

The program is self-paced and divided into 3 modules, each ending with a hands-on project.

To earn a micro-certificate for a module, you must:

• Complete that module’s project

• Work solo or in a team of up to 5 people

• Publish your project publicly on Ready Tensor with a write-up and GitHub repo link

• Submit it by the monthly deadline for expert review (feedback within 2 weeks)

• Score at least 70% based on the evaluation rubric

• If a project doesn’t meet the bar, you can revise and resubmit — just like in a real AI team.

After completing the project successfully, you’ll earn the micro-certificate and badge for that module.

Complete and pass all 3 modules to earn the full Agentic AI Developer Certificate.

Flexible, Modular, and Built Around You

The certification program is built around three standalone modules, each focused on a specific set of skills and ending in a hands-on project.

The three certification modules:

• 🧠 Module 1 – RAG Systems Expert

• 🤖 Module 2 – Agentic AI Builder

• 🔒 Module 3 – Agentic AI Engineer

You can join the program anytime and complete one, two, or all three modules — depending on your goals. Each module culminates in a hands-on project. You're free to move at your own pace and submit each project whenever you're ready for review.

For each successfully completed project, you’ll earn a micro-certification and badge, which can be shared on your profile and resume as proof of specific capabilities.

To earn the full Agentic AI Developer Certification, you must complete and submit all three module projects, meet the 70% threshold on each, and publish your work on the Ready Tensor platform.

Project submissions are reviewed monthly. To be included in a given month’s review cycle, simply submit your project before the posted deadline for that month. View upcoming dates in the Program Guide.

Program Prerequisites

This is a technical program. You should be comfortable writing Python code and working with APIs.

Required Skills:

• Intermediate Python programming (functions, classes, modules)

• Familiarity with APIs and HTTP requests

• Understanding of basic AI/ML concepts (embeddings, inference)

• Experience with LLMs (ChatGPT, Claude, etc.)

• Comfort with the command line, GitHub, and Python environments

Recommended Skills:

• LangChain, LangGraph, or agentic libraries

• Vector DBs (FAISS, Chroma, Pinecone)

• LLM tools or assistants built via APIs

• FastAPI, Gradio, or Streamlit experience

Why Choose Ready Tensor

At Ready Tensor, we don’t just teach agentic AI — we build with it. Our team is actively developing real-world systems that use Gen AI and agentic architectures, including projects in conversational AI, generative authoring, and automated assessment.

The projects in this certification program aren’t classroom exercises — they are modeled after the actual R&D work happening at Ready Tensor. You will be solving real problems with real tools, following an industry-style workflow.

For each module, a Ready Tensor lead (your “client”) will provide project requirements. When you submit your projects, you'll receive direct feedback from our experts, and iterate on your solution — just like in a professional AI team.

By the end of the program, you won’t just walk away with a certificate. You will have public, portfolio-grade projects and the kind of hands-on experience that proves you can thrive in real-world AI development.

Our Task-Driven Learning Approach

Traditional learning programs follow a predictable pattern: you sit through lectures, absorb a mountain of theory, and only later attempt assignments to apply what you retained.

The problem? It’s boring. Passive learning often leads to disengagement and high dropout rates — and it’s disconnected from how real-world projects work.

In industry, you don’t learn first and act later — you’re given a business problem, and you must figure out how to solve it by acquiring the necessary knowledge and skills along the way.

That’s why we built the Agentic AI Developer Certification Program around a Task-Driven Learning model.

From Day 1 of each module, you'll receive real-world tasks and project requirements. Your goal is to complete them — drawing from our curated lectures, articles, templates, and tools, and supplementing with external research as needed.

Why This Matters:

• Makes learning engaging: Projects drive curiosity, pride, and ownership.

• Accelerates learning: Doing leads to faster, deeper understanding than passive study.

• Builds adaptive, real-world skills: Mirrors exactly how professional teams work.

We don't believe in “lecture first, application later.” We believe in challenge first, learning by doing — because that’s what prepares you for real success in industry.

Team-Based Projects: Build Like a Real AI Team

Real-world AI systems aren’t built in isolation — and neither are the projects in this program.

Team Size: 3–4 members recommended (maximum 5). Solo projects are allowed but strongly discouraged — real industry work is collaborative.

Skill Balance: Form teams based on complementary expertise for the best results. Ideally, your team should cover:

• AI/ML Theory Expert: Strong in embeddings, transformers, LLM prompting, and applied AI concepts.

• Programming Expert: Skilled in Python, Git, and clean, modular coding practices.

• Documentation Expert: Able to write clear, polished documentation and create compelling visuals.

• UI Expert: Proficient in Streamlit or Gradio to build a functional and professional demo app.

Note: One person can fill multiple roles if needed, but your team should cover all key skill areas to succeed.

If you don't have a team yet, you can look for teammates on our Discord channel. The Discord link will be shared in the email you receive with program details.