AI Engineer

4.5
Advanced
20 Weeks

AI Engineer

Artificial Intelligence Engineers are responsible for designing, developing, deploying, and maintaining AI-powered applications and intelligent systems. With the rapid growth of Generative AI, Large Language Models (LLMs), AI Agents, and Machine Learning, AI Engineers are among the most sought-after professionals in the technology industry.

This comprehensive AI Engineer Master Program is designed to take learners from Python and Machine Learning fundamentals to advanced AI application development, Generative AI, Agentic AI, LLMs, RAG systems, AI deployment, and MLOps.

The program focuses on:

  • Python Programming
  • Data Science Fundamentals
  • Machine Learning
  • Deep Learning
  • Natural Language Processing (NLP)
  • Generative AI & LLMs
  • Agentic AI Systems
  • AI Application Development
  • MLOps & Deployment
  • Real-World Industry Projects

Who Can Join This Course?

  • Students
  • Freshers
  • Software Developers
  • Data Analysts
  • Data Scientists
  • Working Professionals
  • Career Transition Candidates
  • No prior AI experience is required. Basic computer knowledge is sufficient

Training Methodology

Career Opportunities After Course

Course Curriculum

AI Fundamentals

  • What is Artificial Intelligence?
  • Evolution of AI
  • Types of AI
  • AI Applications Across Industries

AI Ecosystem

  • Machine Learning
  • Deep Learning
  • NLP
  • Computer Vision
  • Generative AI
  • Agentic AI

AI Project Lifecycle

  • Problem Definition
  • Data Collection
  • Model Development
  • Deployment
  • Monitoring

Outcome

Understand the complete AI landscape and career opportunities.

  • Python Fundamentals

    • Variables & Data Types
    • Operators
    • Loops & Conditions
    • Functions

    Data Structures

    • Lists
    • Tuples
    • Dictionaries
    • Sets

    Object-Oriented Programming

    • Classes
    • Objects
    • Inheritance
    • Polymorphism

    File Handling & Exception Handling

    Practical Exercises

    • AI Utility Programs
    • Data Processing Scripts

    Outcome

    Develop programming skills required for AI engineering.

Mathematics

  • Linear Algebra
  • Matrices & Vectors
  • Probability
  • Calculus Basics

Statistics

  • Descriptive Statistics
  • Inferential Statistics
  • Hypothesis Testing

AI Applications of Mathematics

  • Optimization Concepts
  • Statistical Modeling

Outcome

Build strong mathematical foundations for AI and ML.

NumPy

  • Arrays
  • Matrix Operations

Pandas

  • DataFrames
  • Data Cleaning
  • Data Transformation

Data Visualization

  • Matplotlib
  • Interactive Charts

Exploratory Data Analysis (EDA)

  • Feature Analysis
  • Correlation Analysis

Outcome

Prepare and analyze datasets for AI applications.

Machine Learning Fundamentals

  • ML Workflow
  • Training & Testing Data

Supervised Learning

  • Linear Regression
  • Logistic Regression
  • Decision Trees
  • Random Forest
  • KNN
  • SVM

Unsupervised Learning

  • K-Means Clustering
  • PCA

Model Evaluation

  • Accuracy
  • Precision
  • Recall
  • F1 Score

Outcome

Build predictive and classification models.

Neural Networks

  • Artificial Neural Networks (ANN)
  • Activation Functions
  • Backpropagation

Deep Learning Frameworks

  • TensorFlow
  • Keras
  • PyTorch Overview

CNN (Computer Vision)

  • Image Classification
  • Object Detection Concepts

RNN & Sequence Models

  • Time Series Concepts
  • Sequence Processing

Outcome

Develop advanced AI models using deep learning.

NLP Fundamentals

  • Text Cleaning
  • Tokenization
  • Stemming
  • Lemmatization

NLP Techniques

  • Bag of Words
  • TF-IDF
  • Word Embeddings

NLP Applications

  • Sentiment Analysis
  • Text Classification
  • Named Entity Recognition (NER)

Outcome

Process and understand human language using AI.

Introduction to Generative AI

  • What is Generative AI?
  • Generative AI Applications

Large Language Models

  • GPT Models
  • Gemini
  • Claude
  • Open-Source LLMs

Prompt Engineering

  • Zero-Shot Prompting
  • Few-Shot Prompting
  • Chain-of-Thought Prompting

AI Productivity Applications

  • Content Generation
  • Coding Assistance
  • Business Automation

Outcome

Understand and leverage Generative AI effectively.

LLM Architecture

  • Transformers
  • Tokens
  • Context Windows

Embeddings

  • Semantic Search
  • Vector Representations

Vector Databases

  • FAISS
  • ChromaDB

Retrieval-Augmented Generation (RAG)

  • Knowledge Base Integration
  • Document Search Systems

Practical Projects

  • Company Knowledge Assistant
  • Document Q&A Chatbot

Outcome

Build enterprise-grade AI assistants using RAG.

Agent Fundamentals

  • AI Agents
  • Agent Architecture

Agentic Workflows

  • Planning
  • Reasoning
  • Memory
  • Tool Usage

Multi-Agent Systems

  • Collaborative Agents
  • Agent Communication

Agent Frameworks

  • LangGraph
  • CrewAI
  • AutoGen

Practical Labs

  • Research Agent
  • Business Analyst Agent
  • Customer Support Agent

Outcome

Build autonomous AI systems capable of complex task execution.

AI APIs

  • LLM APIs
  • AI Service Integration

Application Development

  • AI Chatbots
  • AI Assistants
  • Knowledge Bots

Streamlit

  • Interactive AI Applications

API Development

  • FastAPI Basics
  • AI Backend Services

Outcome

Develop full-stack AI-powered applications.

Model Deployment

  • Model Serialization
  • API Deployment

MLOps Fundamentals

  • Model Monitoring
  • Version Control

Cloud Deployment Concepts

  • Azure AI Services
  • AWS AI Services
  • Google AI Services

CI/CD for AI

  • Deployment Pipelines

Outcome

Deploy and manage AI systems in production environments.

Responsible AI

  • Fairness
  • Transparency
  • Explainability

AI Security

  • Prompt Injection
  • Data Leakage Risks
  • Model Security

Governance

  • AI Compliance
  • Risk Management

Outcome

Develop secure and ethical AI solutions.

๐Ÿค– Enterprise AI Assistant

Build a business assistant using LLMs and RAG.

๐Ÿ“š AI Knowledge Management Platform

Create a document intelligence system.

๐Ÿ›’ AI Sales Automation Agent

Automate lead generation and customer engagement.

๐Ÿ“Š AI Business Analyst

Generate reports and insights from business data.

๐ŸŽง Customer Support Chatbot

Build an AI-powered support assistant.

๐Ÿฅ Healthcare AI Assistant

Create an AI solution for healthcare information retrieval.

๐Ÿข Multi-Agent Enterprise Workflow System

Develop a team of AI agents collaborating on business tasks.

๐Ÿ“ˆ Predictive Analytics Platform

Build an AI-powered forecasting application.

Outcome

Gain real-world experience with enterprise AI solutions.