Learn Data Science with focus on adding value with the most efficient tech stack.

Overview

DataScienceWithPython

Get started with Data Science with Python

An engaging journey to become a Data Scientist with Python

TL;DR

  • Download all Jupyter Notebooks from repo (zip-file-download).
  • Unzip download (main.zip) an appropriate place.
  • Launch Ananconda and start JuPyter Notebook (Install it from here if needed)
  • Open the first Notebook from download.
  • Start watching the first video lesson (YouTube).

Why do most fail with Data Science?

  • Most focus on getting good at all technical aspects:
    • Math
    • Stat
    • Python
    • R
    • Machine Learning
    • pandas
    • NumPy
    • PyTorch

...and the list could go on and we didn't dive into sub-categories (but you get the point)

DISCLAIMER!!! This is the wrong (long) way to learn!

Master the Data Science Workflow

Data Science Workflow

  • Understanding what matters
    • The full workflow
    • How to add value to customers
  • Focus on how to add value
    • This can be done with limited technical knowledge
    • ...and we will cover all you need
  • Later you can become an expert in whatever your interest are
  • But you should first understand the WHY!

This course will cover all aspects of it with the focus to get you there as fast as possible!

What will we cover?

  • Data Science Workflow
    • Acquire - Prepare - Analyze - Report - Actions
  • Data Visualization
  • pandas for Data Science
  • Data Sources
    • Web Scraping
    • Databases
    • CSV, Excel & parquet files
  • Where to find data
  • Join (combine) data
  • Statistics you need to know
  • Machine Learning Models
  • Cleaning Data
  • Feature Scaling
  • Feature Selection
  • Model Selection

At the end of the course you are provided with a template covering all aspects of the Data Science Workflow

  • Acquire - Prepare - Analyze - Report - Actions
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