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AI/ML

Artificial Intelligence & Machine Learning

Models, data and deployed intelligent systems.

Field of study

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Core subjects

Subjects you actually study in AI/ML — with notes, PDFs and video links.

Browse all subject notes & PDFs →

Learning roadmap

Phase by phase, with a resource link on every step.

1
Phase 1 — Foundations
2
Phase 2 — Core subjects
3
Phase 3 — Specialise
4
Phase 4 — Job ready

Technical skills

Model training & evaluation
Feature engineering
Deep learning architectures
Prompt engineering & RAG
Experiment tracking
Model deployment

Programming skills

PythonSQLPyTorchNumPy / PandasBashTypeScript (for app layers)

Tools & technologies

PyTorchscikit-learnHugging FaceWeights & BiasesDockerVector databases

Mini projects

Short, buildable projects to start with.

  • Spam classifier with proper validation
  • Sentiment analysis on real reviews
  • Image classifier with transfer learning
  • RAG chatbot over your own notes

Major projects

Final-year scale projects that stand out in interviews.

  • End-to-end ML service with monitoring
  • Fine-tuned domain LLM with evaluation suite
  • Computer-vision quality inspection prototype
  • Recommendation engine with A/B testing plan

Career paths

  • • Machine learning engineering
  • • Data science
  • • Applied research
  • • MLOps
  • • AI product engineering

Job roles

  • • ML Engineer
  • • Data Scientist
  • • AI Engineer
  • • Research Assistant
  • • MLOps Engineer
  • • Applied Scientist

Government & PSU opportunities

Exams and organisations that recruit from this branch.

  • ISRO / DRDO AI research posts
  • NIC and IndiaAI mission projects
  • CSIR labs
  • UGC NET for teaching
  • Defence analytics roles

Higher studies

  • • MTech / MS in AI or Data Science
  • • PhD in machine learning
  • • Specialised LLM and MLOps programmes

Certifications

  • • DeepLearning.AI specialisations
  • • Google Professional ML Engineer
  • • AWS Machine Learning Specialty
  • • Hugging Face NLP course

Industry-relevant technologies

What companies in this field are actively working on.

Large language models and agentsRetrieval-augmented generationModel evaluation and safetyEdge and on-device inferenceSynthetic data

AI/ML career updates

Domains hiring from this branch and the skills each one expects.

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