To develop competent AI professionals capable of designing, developing, and deploying machine learning models, working with data-driven systems, and applying AI solutions across industries including engineering, business, and automation.

1. Analyse complex datasets for AI applications
2. Design machine learning models and pipelines
3. Evaluate AI model performance
4. Apply advanced AI tools and programming techniques
5. Develop AI-based solutions for real-world problems

Module 1: Advanced AI Concepts

• AI paradigms and intelligent systems
• Problem-solving in AI
• Knowledge representation
• AI system architecture
• Real-world AI applications

Module 2: Data Science for AI

• Data acquisition techniques
• Data wrangling and preprocessing
• Exploratory data analysis (EDA)
• Data visualization techniques
• Feature engineering basics

Module 3: Machine Learning Algorithms

• Regression models (linear & logistic)
• Classification algorithms:
  • Decision trees
  • K-Nearest Neighbors (KNN)
• Clustering algorithms:
  • K-means clustering
• Model evaluation techniques:
  • Accuracy
  • Precision
  • Recall

Module 4: Deep Learning Fundamentals

• Introduction to neural networks
• Perceptron model
• Activation functions
• Deep learning frameworks:
o TensorFlow / Keras (intro level)
• Basic image classification model

Module 5: Natural Language Processing (NLP)

• Text processing basics
• Tokenization and stemming
• Sentiment analysis
• Chatbot development basics
• NLP applications

Module 6: Computer Vision Basics

• Image processing fundamentals
• Object detection basics
• Image classification models
• OpenCV introduction
• Real-world applications

Module 7: AI Deployment & Tools

• Model deployment basics
• Cloud platforms overview:
o AWS / Azure / Google Cloud
• API integration basics
• AI pipelines
• Version control (Git basics)

Module 8: AI Ethics, Governance & Industry Applications

• Responsible AI principles
• Bias and fairness in AI systems
• Data privacy laws
• AI governance frameworks
• Industry applications in:
o Engineering
o Healthcare
o Finance
o Smart cities

Final Project

Learners must:
• Develop a complete AI solution project, such as:
o Predictive model (engineering/business data)
o Chatbot system
o Image classification tool

• Include:
o Data collection
o Model development
o Evaluation
o Deployment demonstration

• Submit a technical report + presentation