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Would you like to learn to use Python extracting meaningful insight from data to grow your business but you reckon it will be too complex? As a beginner, you will be probably afraid that programming is difficult. Learning data analysis and data mining can take months, and the possibility to give up before mastering them could be high. The best solution is a complete programming manual with hands-on projects and practical exercises. This guide is structured as a course with seven chapters for seven days and studied special exercises to apply what you learned step-by-step.

Today, 91 percent of Python programmers are not quite prepared. This is what the IT companies say, according to a recent survey. Do you know why? The reason is that they have no notions of artificial intelligence. So, future programmers will no longer find work without having knowledge of this particular field that is constantly evolving.

Python Data Science is a complete guide on Python for every person who is looking to expand their current or future business, learn the basics of data science, and how Python programming can be used for it. There are so many businesses that are going to benefit when it comes to working with data analysis and seeing this work for some of their needs. It is always a good idea to learn a bit more about this process and how you are able to really use it to learn more about your customers, learn how to beat out your competition, and so much more.

Classic Computer Science Problems in Python sharpens your CS problem-solving skills with time-tested scenarios, exercises, and algorithms, using Python. You'll tackle dozens of coding challenges, ranging from simple tasks like binary search algorithms to clustering data using k-means. You'll especially enjoy the feeling of satisfaction as you crack problems that connect computer science to the real-world concerns of apps, data, performance, and even nailing your next job interview!

This is a two book bundle related to data analytics and learning Python programming from scratch!