AI/ML Engineer Course & Curriculum

NCPL's hands-on AI/ML Engineer training — full curriculum, real projects, certification prep, and job placement support. We train, mentor and place you.

Module 1: Programming & Math Foundations

12 hours: Python mastery and mathematical foundations

  • Advanced Python programming
  • Data structures and algorithms
  • Software design patterns
  • Linear algebra
  • Calculus fundamentals
  • Probability theory
  • Statistical methods

Module 2: Machine Learning Fundamentals

15 hours: Supervised and unsupervised learning techniques

  • Regression algorithms
  • Classification models
  • Clustering techniques
  • Decision trees and ensembles
  • Feature engineering
  • Model evaluation
  • Cross-validation

Module 3: Deep Learning & Neural Networks

13 hours: Advanced neural network architectures

  • Neural network fundamentals
  • CNNs for image processing
  • RNNs for sequences
  • TensorFlow framework
  • PyTorch development
  • Transfer learning
  • Model optimization

Module 4: MLOps & Cloud Deployment

10 hours: Production deployment and MLOps practices

  • Cloud platforms (AWS, Azure, GCP)
  • Docker containerization
  • Kubernetes orchestration
  • CI/CD pipelines
  • Model monitoring
  • Version control
  • Scalability patterns