> ## Documentation Index
> Fetch the complete documentation index at: https://launchpad-about-us.nxtwave.tech/llms.txt
> Use this file to discover all available pages before exploring further.

# 📊 Data Science & ML

> Learn Data Science and Machine Learning on Launchpad with statistics, classical ML, ensemble methods, NLP, and deep neural networks.

The DS-ML track on Launchpad takes you from statistical foundations to production-style machine learning and deep learning. You will move through the same layers a working ML engineer touches, so the projects you build map cleanly to the questions asked in DS and ML placement interviews.

## What you will learn

<AccordionGroup>
  <Accordion title="Statistics" icon="chart-column">
    Build the statistical intuition that every data science and machine learning workflow depends on, from descriptive summaries to the probability concepts behind modeling decisions.
  </Accordion>

  <Accordion title="Classical Machine Learning" icon="brain">
    Work through the core supervised and unsupervised algorithms that anchor most ML interview rounds and real-world tabular problems.
  </Accordion>

  <Accordion title="Ensemble Learning" icon="layer-group">
    Combine models to squeeze out extra accuracy, and understand why ensemble methods are the go-to choice for competitions and production tabular models.
  </Accordion>

  <Accordion title="Natural Language Processing" icon="message">
    Learn how text becomes features and predictions, so you can build NLP systems and answer language-focused ML interview questions with confidence.
  </Accordion>

  <Accordion title="Neural Networks and Deep Learning" icon="network-wired">
    Move from a single neuron to full deep learning architectures, and connect the theory to hands-on model building.
  </Accordion>
</AccordionGroup>

<Tip>
  If you are targeting Gen AI or LLM-focused roles, follow this track with the [Gen AI](/courses/gen-ai) course to layer LLM application building on top of your ML foundation.
</Tip>