Are you ready to work out with the Data Science Bookcamp? This series of liveProjects takes you hands-on with fun and engaging data science challenges from the bestselling book by Leonard Apeltsin. It features Discovering Disease Outbreaks from News Headlines, which he co-created with Will Koehrsen, Nate George’s Decoding Data Science Job Postings to Improve Your Resume, and three original projects by Emre Rencberoglu. Each challenge stretches your data science muscles and teaches you useful new skills through practice, such as using NumPy and SciPy for mathematical operations, clustering with scikit-learn, and analyzing and visualizing network datasets with NetworkX. Tackle them individually or all of them for an intensive workout of your data capabilities!
In this liveProject, you’ll stretch your Python data science skills by building a simulator for popular Blackjack variant game 21. You’ll design your simulation step-by-step, then use visualization techniques to interpret your findings. By the end of your project, you’ll have a winning strategy for playing card games and new skills with fundamental Python libraries like NumPy and SciPy.
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.
In this liveProject, you’ll turn your data science skills to analyzing an OTC network dataset scraped from bitcoin users in order to establish the most (and least!) trustworthy users. You’ll analyze a provided graph dataset, visualize it, generate features, and then create user clusters. You’ll start out by reading and examining the trust network dataset in Python, then create and interpret user clusters, and finally visualize the nodes and edges of the network dataset. This fast and engaging data science project will stretch your skills and build your knowledge of clustering.
These liveProjects are for intermediate Python programmers who want to improve their data science skills. To begin these liveProjects you will need to be familiar with the following:
In this liveProject, you’ll work out your Python data science skills and develop an important understanding of common data science and statistics techniques, such as:
geekle is based on a wordle clone.