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Welcome to Python for statistical analysis! This course is designed to position you for success by immersing yourself in the real world of statistics and data science. Learn through real-world examples: Rather than spend hours on theoretical content and struggle to connect it to real-world problems, we'll focus entirely on applied statistics. Taking theory and immediately applying it through Python on common problems to give you the knowledge and skills you need to excel. Presentation-focused results: Adding numbers is easy and quickly becomes the domain of computers and not people. The skills that people have are interpreting and visualizing results, so we focus a lot on this, integrating visual production and graphical exploration into our workflows. Plus, bonus bonus content on great ways to bring images to life for reports, articles, and presentations, so you can stand out from the crowd. Modern tools and workflows: This is not school, where we want to spend hours solving problems by hand for reinforcement learning. No, we will solve our problems using state-of-the-art techniques and code libraries, using the features of the latest software versions to make us as productive and efficient as possible. Don't reinvent the wheel when the industry has moved on to rockets. Who is this course for? Data scientists who want to add statistical analysis to their skill set Data scientists who want to do machine learning but want some more statistical fundamentals before entering Students who want to learn applied statistics for research, coursework, or business This is not the school, where we want to spend hours solving problems by hand for reinforcement learning. No, we will solve our problems using state-of-the-art techniques and code libraries, using the features of the latest software versions to make us as productive and efficient as possible. Don't reinvent the wheel when the industry has moved on to rockets. Who is this course for? Data scientists who want to add statistical analysis to their skill set Data scientists who want to do machine learning but want some more statistical fundamentals before entering Students who want to learn applied statistics for research, coursework, or business This is not the school, where we want to spend hours solving problems by hand for reinforcement learning. No, we will solve our problems using state-of-the-art techniques and code libraries, using the features of the latest software versions to make us as productive and efficient as possible. Don't reinvent the wheel when the industry has moved on to rockets. Who is this course for? Data scientists who want to add statistical analysis to their skill set Data scientists who want to do machine learning but want some more statistical fundamentals before entering Students who want to learn applied statistics for research, coursework, or business We will solve our problems using techniques from state-of-the-art software and code libraries, using the features of the latest software releases to make us as productive and efficient as possible. Don't reinvent the wheel when the industry has moved on to rockets. Who is this course for? Data scientists who want to add statistical analysis to their skill set Data scientists who want to do machine learning but want some more statistical fundamentals before entering Students who want to learn applied statistics for research, coursework, or business We will solve our problems using techniques from state-of-the-art software and code libraries, using the features of the latest software releases to make us as productive and efficient as possible. Don't reinvent the wheel when the industry has moved on to rockets. Who is this course for? Data scientists who want to add statistical analysis to their skill set Data scientists who want to do machine learning but want some more statistical fundamentals before entering Students who want to learn applied statistics for research, coursework, or business Who is this course for? ? Data scientists who want to add statistical analysis to their skill set Data scientists who want to do machine learning but want some more statistical fundamentals before entering Students who want to learn applied statistics for research, coursework, or business Who is this course for? ?
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