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September 2026 qualifier: applications close Sun 27 Sep · Week 1 starts Fri 2 Oct
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IIT Madras DS AI Lab Lectures: Data Science and AI Lab

BSDA400177 lectures12 weeks

Weeks

  1. Week 115 lecturesNumPy and matplotlib - notebooks · Numpy and matplotlib - vectors · Numpy and matplotlib - plotting simple curves · Numpy and matplotlib - matrices · Numpy and matplotlib - more on plots · Numpy and matplotlib - numpy arrays, part-1 · Numpy and matplotlib - numpy arrays, part-2 · Numpy and matplotlib - numpy arrays, part-3 · Pandas introduction · Pandas series and dataframe 1 · Pandas series and dataframe 2 · Data selection using pandas 1 · Data selection using pandas 2 · Drop in dataframe · Apply statistics using pandas
  2. Week 29 lecturesWeek 2 - introduction · Introduction - looking at the big picture · Data visualization · Data Preparation · Selection and training of ml models · Finetuning ml models · Structured approach to ml projects (part 1) · Structured approach to ml projects (part 2) · Refining ml projects
  3. Week 35 lecturesPytorch introduction · Autograd · Building ANN · Optimizer, batching and training on GPU · Image classification using pytorch CNN
  4. Week 44 lecturesImage Manipulation with Pillow and OpenCV · Image preprocessing · Transfer Learning · Object Detection
  5. Week 53 lecturesIntroduction to HuggingFace · Fine Tuning GPT2 · Bert Fine tuning
  6. Week 611 lecturesIntroduction to LangChain · Model serving using fastapi · Languange Models in LangChain · Handson: fastapi · PromptTemplates · Model serving using containers · OutputParsers · Handson: docker · LangChain Expression Language · Introduction to kubernetes · Handson: kubernetes
  7. Week 72 lecturesIntroduction to RAG · Demonstration of RAG using LangChain
  8. Week 86 lecturesWeek 8: Introduction · Understanding AI Agent · Exploring various frameworks · Langgraph Fundamentals · Intelligent email assitand Part-I · Intelligent email assitand Part-II
  9. Week 96 lecturesWeek 9: Introduction · Foundations of Data Visualization · Plotly for Visualisation · Detecting bias in machine learning · Explaining machine learning models · Handson: governance tools
  10. Week 107 lecturesTime_series_using_pandas · Time Resampling · Classical Decomposition · STL Decomposition · Stationarity · Make_data_stationary · Hands On Forecasting
  11. Week 118 lecturesIntroduction · GCP Console walkthrough · Introduction to Google Cloud Functions · PySpark: part 1 · PySpark: part 2 · PySpark: part 3 · DataProc tutorial · PySpark Execution Tutorial
  12. Week 121 lectureIntroduction

DS AI Lab previous year papers