Additional information
by Computer Programming Academy (Author)
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? Or perhaps you want to know how to analyze data to solve simple domestic issues but you don't know how to do it?
Here's the deal... 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. So, if you have a project to develop you could think on hiring a professional analyst to shorten the time. This may seem like a good solution but it is certainly very expensive and if the analyst you chose doesn't perform a proper job you still have to pay for it.
The best solution is a complete programming manual with hands-on projects and practical exercises. Computer Programming Academy structured this guide as a course with seven chapters for seven days and studied special exercises for each section to apply what you learned step-by-step. This protocol, tested on both total beginners and people who were already familiar with coding, takes advantage of the principle of diving, concentrating learning in one week. The result of this method has been one for both categories of students: the content of the course was learned faster and remembered longer respect the average.
Inside this book, you will go through a first section in which fundamental and basic notions of data science are discussed, to get to the next chapters crafted specifically to help you learn all the advance data analysis concepts required to produce valuable outcomes from a large volume of data.
In the detail, you will learn:
- The importance of data science technologies in our daily lives
- What are the most common mistakes to avoid when you start dealing with Python for data science
- The 5 stages of the data science lifecycle at the basis of most used applications
- 3 important actions required to gain insights from big data
- What are the advantages of the data mining process in resolving real world problems
- The data analysis tools that will make your life easier
- 3 key frameworks that you have to know to transform unstructured and unorganized data in significant insight
- How to download and use the main Python based data analysis libraries
- A simple method to implement predictive analytics to resolve a business issue in less than 7 days
- A proven strategy to develop predictive models to analyze customers' behavior
- Exercises and quizzes at the end of every chapter to review immediately what you've learned
- Extra content that you will appreciate as curious technology enthusiast
Why is this book different for? Most of the books on the market only take a brief look into data science, showing some of the topics but never going deep concretely. The best way to learn data analysis and data mining is by doing and with this manual you will work through applicable projects in order to solidify your knowledge and obtain a huge sense of achievement.
This is what this guide offers to you, even if you're completely new to programming in 2020 or you are looking to widen your skills as programmer.
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