Back to Learn More

AI Engineering

Build, deploy, and scale real Artificial Intelligence systems used in modern companies. (Advanced / Job Ready)

Module 1: AI Engineering Foundations

  • Role of an AI Engineer
  • AI vs Machine Learning vs Deep Learning
  • Modern AI architecture
  • Overview of AI pipelines
  • Working with Python AI ecosystem
  • Working with Jupyter, Git and project workflow
  • AI ethics and responsible AI
Project: Build a **mini AI pipeline that collects data, trains a model and produces predictions.**

Module 2: Advanced Data Engineering for AI

  • Data pipelines
  • Data collection and automation
  • Large dataset management
  • Feature engineering techniques
  • Handling real-world messy datasets
  • Data storage for AI systems
Project: Build a **data pipeline that collects and processes real-time data from an API.**

Module 3: Deep Learning Systems

  • Neural network architecture
  • Training deep learning models
  • Computer vision models
  • Convolutional Neural Networks (CNN)
  • Transfer learning
  • Model optimization
Project: Build an **AI image classifier that can detect objects or animals in images.**

Module 4: Natural Language Processing & LLMs

  • Text processing pipelines
  • Word embeddings
  • Transformers architecture
  • Introduction to Large Language Models (LLMs)
  • Prompt engineering
  • Fine-tuning language models
Project: Build an **AI chatbot that answers questions about a company website.**

Module 5: AI APIs & Integration

  • Creating AI powered APIs
  • Integrating AI with web applications
  • Using Python APIs with Node or frontend apps
  • Building intelligent applications
  • Handling user input and responses
Project: Build a **Resume Analyzer AI that evaluates candidate CVs automatically.**

Module 6: MLOps & AI Deployment

  • Model versioning
  • Continuous training pipelines
  • Monitoring AI systems
  • Docker for AI deployment
  • Deploying AI APIs
  • Scaling AI applications
Project: Deploy an **AI prediction system accessible via a web API.**

Module 7: Scaling AI Systems

  • Handling large user traffic
  • AI model optimization
  • Distributed AI systems
  • Model caching strategies
  • Cost optimization
  • Building scalable AI architecture
Project: Design a **scalable recommendation engine used by an e-commerce platform.**

Module 8: Industry AI Capstone Projects

  • AI powered recommendation systems
  • AI resume screening systems
  • Fraud detection models
  • AI document summarization tools
  • AI customer support chatbot
Capstone Project Options:
  • AI Job Recommendation Platform
  • AI Powered Personal Tutor
  • AI Medical Symptom Checker
  • Smart Document Summarizer
  • AI Business Analytics Dashboard

By the end of this program, learners will confidently design, build and deploy **production-grade AI systems used in modern technology companies.**