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   "source": "(contents)=\n\n# Contents\n\n*Think Data Science and Management* has 15 chapters in five parts, followed by the appendices and bibliography. Chapter 1 introduces data science and programming; set up your tools with the appendices before the first lab. {doc}`Chapter Topics <chapter_topics>` summarizes what each chapter teaches."
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   "metadata": {},
   "source": "<h2><a class=\"part-overview-link\" href=\"../parts/part_01_fundamentals.html\">Part I. Fundamentals</a></h2>"
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   "source": "Data science as a field and Python as its working language.\n\n- {doc}`Introduction <../01-intro/0100-data-science>`\n- {doc}`Python Basics <../02-python/0200-python>`"
  },
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   "source": "<h2><a class=\"part-overview-link\" href=\"../parts/part_02_working_with_data.html\">Part II. Working with Data</a></h2>"
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   "source": "Arrays and tables: the two data structures the rest of the book builds on.\n\n- {doc}`NumPy Arrays <../03-numpy/0300-numpy>`\n- {doc}`Pandas <../04-pandas/0400-pandas>`"
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": "<h2><a class=\"part-overview-link\" href=\"../parts/part_03_data_visualization.html\">Part III. Data Visualization</a></h2>"
  },
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   "source": "Telling stories with data in pandas, Matplotlib, and Seaborn.\n\n- {doc}`Visualization <../05-visualization/0500-visualization>`\n- {doc}`Matplotlib <../06-matplotlib/0600-matplotlib>`\n- {doc}`Seaborn <../07-seaborn/0700-seaborn>`"
  },
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   "metadata": {},
   "source": "<h2><a class=\"part-overview-link\" href=\"../parts/part_04_inferential_statistics.html\">Part IV. Inferential Statistics</a></h2>"
  },
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   "cell_type": "markdown",
   "metadata": {},
   "source": "Probability, simulation, hypothesis tests, estimation, and regression.\n\n- {doc}`Probability and Statistics <../08-prob-stats/0800-probability-statistics>`\n- {doc}`Hypothesis Testing <../09-test-hypothesis/0900-hypothesis-testing>`\n- {doc}`Two Samples <../10-two-samples/1000-two-samples>`\n- {doc}`Estimation <../11-estimation/1100-estimation>`\n- {doc}`Regression <../12-regression/1200-regression>`"
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": "<h2><a class=\"part-overview-link\" href=\"../parts/part_05_machine_learning.html\">Part V. Machine Learning</a></h2>"
  },
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   "cell_type": "markdown",
   "metadata": {},
   "source": "Predicting and grouping with models: regression, classification, and clustering.\n\n- {doc}`Multiple Regression <../13-multiple-regression/1300-multiple-regression>`\n- {doc}`Classification <../14-classification/1400-classification>`\n- {doc}`Clustering <../15-clustering/1500-clustering>`"
  },
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   "cell_type": "markdown",
   "metadata": {},
   "source": "<h2>Appendices</h2>"
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": "Tool setup for the course, then the bibliography.\n\n- {doc}`Course Tooling <../appendices/0101-tooling>`\n- {doc}`Jupyter Setup <../appendices/jupyter/0200-intro-jupyter>`\n- {doc}`Bibliography <../bibliography>`"
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