Data Science Bookcamp

When to Tweet for Best Effect you own this product

This project is part of the liveProject series Data Science Bookcamp Projects
prerequisites
basic Python • basic Pandas • basic Jupyter Notebook • basic statistics
skills learned
using Python fundamentals to set up environments to test hypotheses • using Pandas and NumPy for for data operations • doing permutation test for calculating p-values
Emre Rencberoglu
1 week · 3-5 hours per week · INTERMEDIATE

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team

5, 10 or 20 seats+ for your team - learn more


Look inside

In this liveProject, you’ll build a fun (and useful!) data analysis tool that can determine which day of the week is the best to Tweet. You’ll test the hypothesis that Friday is the best day for engagement by calculating the p-variables and interpreting the results. You’ll utilize common techniques such as the permutation test and bonferroni correction to see if your hypothesis is accurate—essential skills for any data scientist.

This project is designed for learning purposes and is not a complete, production-ready application or solution.

book resources

When you start your liveProject, you get full access to the following books for 90 days.

project author

Emre Rencberoglu
Emre Rencberoglu is a senior data scientist with over seven years of experience in machine learning, statistics, analytics, and data engineering. He developed numerous machine learning projects and built data pipelines from scratch using R, Python and Spark. Currently, he is leading a data science team of ten in one of the biggest e-commerce companies in the Europe, Middle East, and Africa region.

prerequisites

The liveProject is for data practitioners who want to improve their hypothesis testing skills. To begin this liveProject, you will need to be familiar with the following:


TOOLS
  • Basic Python
  • Basic pandas: Dataframes, basic feature transformations
  • Basic Jupyter Notebook
TECHNIQUES
  • Basic statistics: basic functions and distributions

you will learn

In this liveProject, you’ll stretch your skills for hypothesis testing: one of the most important abilities of any practicing data scientist.


  • Python fundamentals to set up environments to test hypotheses
  • pandas and NumPy for for data operations
  • Permutation test for calculating p-values
  • Calculating the statistical confidence intervals

features

Self-paced
You choose the schedule and decide how much time to invest as you build your project.
Project roadmap
Each project is divided into several achievable steps.
Get Help
While within the liveProject platform, get help from other participants and our expert mentors.
Compare with others
For each step, compare your deliverable to the solutions by the author and other participants.
book resources
Get full access to select books for 90 days. Permanent access to excerpts from Manning products are also included, as well as references to other resources.

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team

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