Live Sessions

ML Ops and Cloud Engineering

Design scalable ML systems with AWS/GCP, Docker, Kubernetes, CI/CD pipelines, and MLflow.

Tools you’ll work with
Python
LangChain
OpenAI API
Hugging Face
AutoGPT
Vector Databases
+4 more tools
₹15000
6 weeksBeginner
Instructor
Ram Nandan
MSc AI • 9+ years • Ex - PWC
Enroll Now→

Course Overview

Description

25 lessons•57 exercises•4 exams•~12 hours

Are you looking for a well-structured data science fundamentals course?

Do you want to gain a clear understanding of the data science field?

This is the perfect course for you.

If terms like traditional data, big data, business intelligence, and machine learning sound confusing, this course will help you understand both meaning and practical application.

25 lessons•57 exercises•4 exams•12 hours

Course Curriculum

A structured, progressive curriculum designed to build depth, intuition, and real-world proficiency over time.

This section introduces key concepts and builds intuition through structured lessons and exercises.

Introduction to Agentic AI and Autonomous Systems
AI Agents vs Traditional AI Models
LLMs and Prompt Engineering Basics
Agent Architectures and Components
Planning, Reasoning and Decision Making
Case Study: Building a Simple AI Agent

This section introduces key concepts and builds intuition through structured lessons and exercises.

Working with Large Language Models (LLMs)
LangChain Basics and Chains
Memory Management in AI Agents
Tool Calling and Function Execution
Multi-step Reasoning and Task Decomposition
Introduction to AutoGPT and BabyAGI
End to End Agent Workflow Implementation

This section introduces key concepts and builds intuition through structured lessons and exercises.

Python for AI Agents Development
Working with APIs and External Tools
Handling JSON, Data and Responses
Building Custom Agent Logic
Debugging and Testing AI Agents

This section introduces key concepts and builds intuition through structured lessons and exercises.

Introduction to Multi-Agent Systems
Agent Communication and Coordination
Task Allocation and Collaboration
Human-in-the-Loop Systems
Use Cases of Multi-Agent AI Systems

This section introduces key concepts and builds intuition through structured lessons and exercises.

Deploying AI Agents on Cloud
Monitoring and Logging Agent Behavior
Performance Optimization Techniques
Safety, Ethics and Guardrails in AI
Case Study: Production-Ready Agentic AI System

How You’ll Learn

This course is designed to help you move beyond tutorials — toward deep understanding, confident implementation, and long-term career growth.

Live Classes
Quizzes
Assignments
Projects
Certification

Build Skills That Scale With You

This course is designed to help you move beyond tutorials — toward deep understanding, confident implementation, and long-term career growth.

Learn deeply. Apply repeatedly.