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Pan-India Training
Industry Standard

Machine Learning Course

From ML Fundamentals to Production-Grade Model Deployment

A rigorous, end-to-end Machine Learning program covering supervised learning, unsupervised methods, neural networks, MLOps and real-world deployment. Ideal for data scientists, engineers and analysts who want to build ML systems that work in production.

10 Weeks
Online + Offline
Beginner to Advanced
Max 30 students
Enrol NowCall +91 97918 17766

What You Get

Complete supervised & unsupervised ML coverage
Deep learning with PyTorch and TensorFlow
Feature engineering, model evaluation & tuning
MLOps: MLflow, DVC, model versioning & pipelines
Deploy models on AWS/GCP with CI/CD
CraftVoy ML Professional Certification

Who Is This For

  • Software engineers transitioning to data science
  • Analysts who want to build predictive models
  • Data scientists formalising their ML knowledge
  • Engineers interested in production ML systems

Learning Outcomes

  • Build end-to-end ML pipelines from data to deployment
  • Apply state-of-the-art algorithms to real business problems
  • Manage the full ML lifecycle with MLOps best practices
  • Land data science or ML engineering roles

Curriculum

1

Module 1: ML Fundamentals

  • Supervised vs unsupervised learning
  • Linear & logistic regression
  • Bias-variance tradeoff & cross-validation
2

Module 2: Advanced ML Algorithms

  • Decision trees, random forests & gradient boosting
  • SVMs, k-means & DBSCAN
  • Dimensionality reduction: PCA, t-SNE
3

Module 3: Deep Learning

  • Neural networks & backpropagation
  • CNNs, RNNs & transformers
  • Transfer learning & fine-tuning
4

Module 4: MLOps & Deployment

  • Experiment tracking with MLflow
  • Model serving: FastAPI & Triton
  • Monitoring model drift in production

Frequently Asked Questions

What mathematics do I need?

Basic linear algebra and statistics are helpful. We cover all necessary math concepts in the first week.

Which programming language is used?

Python throughout — scikit-learn, PyTorch, TensorFlow, pandas and relevant ML ecosystem libraries.

Is there a project component?

Yes — you build 3 end-to-end ML projects and present a capstone to an industry panel.

Ready to get started?

Talk to a CraftVoy advisor today and find the right batch for your schedule.

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