AI Integrated Agentic AI Development Course | BlackBox Learning
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Build Autonomous
Agentic AI Systems

Design and deploy autonomous AI agents in 3 months. Master tool-using workflows and multi-agent systems with LangChain and CrewAI — from prompt engineering to production deployment.

Start Learning Watch Demo
agent.py
1 from crewai import Agent, Task, Crew
2
3 researcher = Agent(
4     role="Research Analyst",
5     goal="Find accurate, up-to-date info",
6     tools=[web_search_tool],
7     memory=True
8 )
9
10 task = Task(description="Research AI agent trends", agent=researcher)
11 crew = Crew(agents=[researcher], tasks=[task])
12 result = crew.kickoff()
What You'll Master

Three Core Skill Tracks

Structured learning paths designed to take you from LLM fundamentals to production-ready autonomous agents.

LLM & Prompt Engineering Foundations

Understand how large language models work and how to prompt them for reliable, structured results.

  • How LLMs work under the hood
  • Prompt design & patterns
  • Structured outputs
  • Function & tool calling
Module 1 Beginner
Core Skill

Agent Frameworks — LangChain & CrewAI

Build single autonomous agents, equip them with tools and memory, and chain multi-step reasoning.

  • Building single agents
  • Giving agents tools & memory
  • Chaining reasoning steps
  • LangChain fundamentals
Module 2 Intermediate

Multi-Agent Systems & Deployment

Orchestrate teams of agents that collaborate, communicate, and ship to production.

  • Orchestrating multi-agent workflows
  • Agent-to-agent communication
  • Deploying agentic applications
  • Production monitoring
Modules 3 & 4 Advanced
See It In Action

Build Real Agents From Day One

No boring theory. You'll build practical, autonomous agents that reason, use tools, and collaborate. Each project is designed to teach you the agentic AI skills employers actually want.

Autonomous Research Agent

Build an agent that plans, searches the web, and synthesizes findings on its own.

Customer Support Agent with Tools

Give an agent real tools — order lookup, FAQs, ticket creation — and let it act.

Multi-Agent Content Pipeline

Orchestrate a crew of specialized agents that research, write, and edit together.

AI Task Automation Bot

Deploy an agent that automates repetitive workflows end-to-end.

View Full Curriculum
crewai_pipeline.py 
from crewai import Agent, Task, Crew, Process
from langchain.tools import DuckDuckGoSearchRun

search_tool = DuckDuckGoSearchRun()

researcher = Agent(
    role="Researcher",
    goal="Gather the latest information",
    tools=[search_tool],
    verbose=True
)

writer = Agent(
    role="Content Writer",
    goal="Write clear, engaging summaries",
    verbose=True
)

research_task = Task(
    description="Research trending agent frameworks",
    agent=researcher
)
write_task = Task(
    description="Summarize findings into a report",
    agent=writer
)

crew = Crew(
    agents=[researcher, writer],
    tasks=[research_task, write_task],
    process=Process.sequential
)

# Deploy the multi-agent workflow
result = crew.kickoff()
print("Workflow complete! 🚀")
Complete Syllabus

Agentic AI Development & Multi-Agent Systems

3 Month Program • Beginner to Advanced • 4 Comprehensive Modules

01

LLM Foundations & Prompt Engineering

Understand how LLMs reason and how to prompt them reliably

Prompt Engineering Structured Outputs Function Calling LLM Fundamentals
Understand how LLMs generate & reason over text Design effective, structured prompts Implement function/tool calling with LLMs
02

Building Agents with LangChain

Build your first autonomous agents with tools and memory

LangChain Agent Tools Memory Chains
Build a single autonomous agent with LangChain Equip agents with external tools & memory Chain multi-step reasoning workflows
03

Multi-Agent Systems with CrewAI

Orchestrate crews of agents that collaborate on complex tasks

CrewAI Multi-Agent Orchestration Agent Roles Task Delegation
Design multi-agent crews with defined roles Enable agent-to-agent communication Delegate and sequence complex tasks
04

Agent Deployment & Real Projects

Ship production-ready agentic applications

Deployment API Integration Monitoring Production Projects
Deploy agentic apps to production environments Integrate agents with real APIs and data sources Build and ship 6 real-world agent projects
Expert Guidance

Learn from Industry Experts

Get mentored by professionals who build real-world agentic AI applications every day.

Saravana Perumal - Python & GenAI Mentor
5+ Years
Experience

Saravana Perumal

Python & GenAI Mentor

A hands-on LLM application engineer specializing in building autonomous agents and multi-agent workflows for real production systems. Saravana has designed agent architectures using LangChain and CrewAI that reason, call tools, and collaborate to complete complex tasks. His mentorship focuses on taking you from prompt basics to shipping deployable, autonomous AI applications. He believes the fastest way to learn agentic AI is to build agents that actually do useful work.

LLM Engineering Agent Frameworks Workflow Automation

Ready to Build Autonomous AI Agents?

3 months. 4 modules. Real autonomous agent projects.

Enroll Now — Limited Seats Chat on WhatsApp Download Brochure
Beginner Friendly Industry Certificate 6 Real Projects Learning Support
FAQ

Got Questions?

Everything you need to know. Can't find your answer? WhatsApp us anytime.

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Do I need prior AI/ML experience?

No advanced AI/ML background is required. Basic familiarity with Python is helpful, since we build agents in Python throughout. We start from how LLMs and prompting work before moving into agent frameworks like LangChain and CrewAI.

What will I be able to build after this course?

You'll be able to build autonomous research agents, tool-using customer support agents, multi-agent content pipelines, and task automation bots — using LangChain and CrewAI, deployed as real applications.

Will I get a certificate?

Yes! You'll receive an industry-recognized Agentic AI Certificate from BlackBox Learning with a unique verification ID. It's LinkedIn-ready and employer-accepted.

What makes this course different?

Most courses stop at prompting ChatGPT. We go further — you'll build real autonomous agents that reason, call tools, and work in multi-agent teams, with live mentorship and 6 hands-on projects throughout the program.

What careers can I pursue after this?

AI Agent Developer, Automation Engineer, LLM Application Developer, GenAI Engineer, AI Workflow Consultant — demand for agentic AI skills is growing fast across every industry.

Online or offline?

Blended format — live in-person sessions at our Thiruvananthapuram center plus online access to recordings, resources, and mentor support. Best of both worlds.

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