Unit III - Data Analytics Life Cycle

<h3>Analytics of Vidhya</h3>
<p><a href="https://www.analyticsvidhya.com/blog/2023/05/what-is-data-science-a-complete-guide/">What is Data Science? | Lifecycle, Application, Tools &#x26; More</a></p>
<h3>Campus X</h3>
<p>Links: <a href="https://github.com/campusx-official">GitHub</a> | <a href="https://www.notion.so/91443d1b14cd486abc87a54cdbf00030?pvs=21">Data Science Course</a></p>
<h3><span class="internal-link-container"><a href="../../../../2.%20AI%20Interns-2024/Python%20Resources" class="internal-link">Python Resources</a><html><head></head><body><span class="note-preview block col-span-2 max-w-[400px] rounded shadow-sm p-5 bg-white cursor-pointer text-lg hover:bg-gray-200 hover:border-transparent"><span class="block font-bold leading-snug tracking-tight truncate mb-1">Python Resources</span><span class="block font-normal text-gray-600 whitespace-pre-line max-h-[150px] truncate">To have a solid foundation in certain key areas. Here's a list of essential concepts and skills you should familiarise yourself with:

1. Basic Python Programming:
   * Understand variables, data types, and basic operators.
   * Learn control flow statements (if, else, elif, loops).
   * Familiarize yourself with functions and how to define and call them.
1. Data Structures in Python:
   * Know how to work with lists, tuples, sets, and dictionaries.
   * Understand indexing and slicing for acces</span></span></body></html></span></h3>
<p><a href="https://pandas.pydata.org/">Pandas</a>
<a href="https://numpy.org/">NumPy</a>
<a href="https://matplotlib.org/">Matplotlib</a></p>

My Blog.

DS III - Lecture Notes 2

Analytics of Vidhya

Campus X