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Course Details

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Software Agentic AI Program
4.0

Description

Python for AI Engineering

  • Python Fundamentals

  • OOP with Python

  • APIs Development

  • FastAPI

  • Async Programming

  • Data Processing

AI Foundations

  • Artificial Intelligence Fundamentals

  • Machine Learning Concepts

  • Generative AI

  • LLM Fundamentals

  • AI System Design

LLM Engineering

  • OpenAI Models

  • Gemini Models

  • Claude Models

  • Local Models

  • Prompt Engineering

  • Structured Outputs

Vector Databases & Embeddings

  • Embeddings

  • Similarity Search

  • Vector Databases

  • Knowledge Retrieval

RAG Engineering

  • Retrieval Augmented Generation

  • Document Processing

  • Knowledge Bases

  • Enterprise Search Systems

Agent Engineering

  • AI Agents

  • Autonomous Agents

  • Multi-Agent Systems

  • Agent Memory

  • Agent Planning

  • Tool Calling

  • Function Calling

  • Human-in-the-Loop Systems

AI Agent Frameworks

  • LangChain
  • LangGraph
  • CrewAI
  • AutoGen
  • Semantic Kernel
  • Pydantic AI
  • OpenAI Agents SDK

 

MCP (Model Context Protocol)

  • MCP Fundamentals

  • MCP Servers

  • MCP Clients

  • Enterprise Integrations

Workflow Automation

  • n8n

  • AI Workflows

  • Webhooks

  • Event Driven Systems

  • Enterprise Automation

AI Backend Development

  • FastAPI

  • REST APIs

  • Authentication

  • Authorization

  • Background Processing

  • Message Queues

  • AI Service Architecture

Angular Development

  • Angular Fundamentals

  • Components

  • Services

  • Routing

  • State Management

  • API Integration

  • Enterprise Angular Architecture

What You Will Learn

  • Build AI Agents using Python and modern Agent Frameworks.
  • Develop autonomous AI systems capable of reasoning and decision-making.
  • Integrate Large Language Models (LLMs) into real-world applications.
  • Design and implement Multi-Agent Systems that collaborate to solve complex tasks.
  • Build Retrieval-Augmented Generation (RAG) applications using private knowledge bases.
  • Connect AI Agents with external APIs, databases, and third-party services.
  • Develop intelligent workflow automation solutions for business processes.
  • Use Vector Databases for semantic search and knowledge retrieval.
  • Apply Prompt Engineering techniques to improve AI performance and reliability.
  • Deploy AI Agent applications to cloud and production environments.
  • Build AI-powered web applications with modern frontend and backend technologies.
  • Create AI copilots, chatbots, virtual assistants, and business automation agents.
  • Implement monitoring, evaluation, and optimization strategies for AI systems.
  • Develop complete portfolio projects demonstrating Agentic AI skills.
  • Understand AI security, governance, and responsible AI practices.
  • Be prepared for roles such as:
  • Agentic AI Developer
  • AI Engineer
  • Generative AI Engineer
  • AI Solutions Developer
  • AI Automation Engineer
  • LLM Application Developer
  • AI Integration Specialist
  • Portfolio Projects
  • AI Customer Support Agent
  • AI Sales & Marketing Agent
  • Multi-Agent Business Assistant
  • Enterprise Knowledge Base Chatbot (RAG)
  • AI Document Processing System
  • AI Task Automation Platform
  • AI-Powered Web Application
  • End-to-End Agentic AI Capstone Project for a real business scenario.

Requirements

  • Basic programming knowledge in any language (.NET, PHP, Java, Node.js, Python, etc.)
  • Understanding of Object-Oriented Programming (OOP)
  • Familiarity with APIs and web services (REST APIs)
  • Basic knowledge of databases (SQL or NoSQL)
  • Understanding of software development fundamentals
  • Experience with Git and GitHub (recommended)
  • Basic command-line usage
  • A laptop with at least 8 GB RAM (16 GB recommended)
  • Stable internet connection
  • Willingness to learn Python for AI development
  • Passion for Artificial Intelligence and automation technologies
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