Data Processing Using Python

Go to Course: https://www.coursera.org/learn/python-data-processing

Introduction

**Course Review: Data Processing Using Python** **Introduction** In the era of big data, the ability to effectively process and analyze data is crucial across numerous fields, including finance, marketing, and healthcare. For those without a computer science background, diving into programming can seem daunting. However, Coursera's course, **Data Processing Using Python**, is specifically designed to bridge this gap. Aimed at non-computer majors, the course offers a comprehensive introduction to Python, focusing on data acquisition, analysis, visualization, and even basic GUI design. **Course Overview** The course unfolds in a structured manner, starting from the basics and gradually escalating to more advanced topics. Here’s a brief breakdown of what you can expect from each module: 1. **Basics of Python**: This foundational module introduces you to Python's syntax and structure. You will learn about data types, operations, conditions, loops, functions, and modules. The emphasis is on simplicity and clarity, ensuring that you can comfortably write useful programs by the end of it. 2. **Data Acquisition and Presentation**: The second module covers methods for acquiring data both locally and from the web. You will learn how to utilize Python's powerful data structures such as sequences, strings, lists, and tuples to effectively present and process your data. 3. **Powerful Data Structures and Python Extension Libraries**: Here, you will dive into intermediate and advanced data structures, including dictionaries and sets, as well as notable libraries like SciPy. The course highlights how these structures can enhance your data processing capabilities. 4. **Python Data Statistics and Mining**: This module demonstrates Python’s capabilities in data analysis and statistics. Through practical examples, you’ll learn how to preprocess data, extract useful insights, and visualize results using various libraries. 5. **Object Orientation and Graphical User Interface**: The final module introduces concepts of object-oriented programming and GUI. Although extensive programming is not required here, understanding these concepts will empower you to explore new functionalities in your future coding endeavors. **Learning Experience** The course is designed with an engaging approach that makes learning enjoyable. The use of real-world examples, particularly from finance data, allows students to relate theoretical concepts with practical applications. The instructor adopts a communicative style that simplifies complex ideas, making them accessible for those without a technical background. Interactive quizzes and assignments reinforce learning and provide immediate feedback. The combination of video lectures, written materials, and hands-on projects caters to various learning styles, ensuring that you can grasp the material effectively. **Why You Should Enroll** 1. **Targeted for Non-Computer Majors**: This course is tailored for individuals with little to no programming experience, making it the perfect starting point for anyone interested in data science or analysis. 2. **Comprehensive Content**: The syllabus covers everything from the basics of Python to advanced data processing techniques, ensuring a well-rounded education. 3. **Practical Applications**: The emphasis on real-world examples, particularly within the finance domain, makes the content relevant and immediately applicable. 4. **Community & Support**: Being part of a global learning platform like Coursera means you can interact with fellow learners and access helpful resources if you encounter challenges. 5. **Flexibility**: As an online course, you can learn at your own pace, fitting study sessions into your schedule. **Conclusion** **Data Processing Using Python** is a highly recommended course for anyone looking to enhance their data processing skills without a deep computer science background. The structured approach, practical examples, and supportive learning environment make it an excellent choice for both professionals and students. By the end of the course, you will not only have a solid foundation in Python programming but also the ability to process, analyze, and present data effectively. Ready to embark on your Python journey? [Enroll today](https://www.coursera.org/learn/hipython/home/welcome) and take your first step toward mastering data processing!

Syllabus

Welcome to learn Data Processing Using Python!

Hi, guys, welcome to learn “Data Processing Using Python”(The English version of "用Python玩转数据", url is https://www.coursera.org/learn/hipython/home/welcome)!In this course, I tell in a manner that enables non-computer majors to understand how to utilize this simple and easy programming language – Python to rapidly acquire, express, analyze and present data based on SciPy, Requests, Beautiful Soup libraries etc. Many cases are provided to enable you to easily and happily learn how to use Python to process data in many fields.

Hi, guys, welcome to learn Module 01 “Basics of Python”! I’ll first guide you to have a glimpse of its simplicity for learning as well as elegance and robustness. Less is more: the author of Python must know this idea well. After learning this module, you can master the basic language structures, data types, basic operations, conditions, loops, functions and modules in Python. With them, we can write some useful programs!

Welcome to learn Module 02 “Data Acquisition and Presentation”! After learning this module, you can master the modes of acquiring local data and network data in Python and use the basic and yet very powerful data structure sequence, string, list and tuple in Python to fast and effectively present data and simply process data.

Welcome to learn Module 03 “Powerful Data Structures and Python Extension Libraries”! Have you felt you are closer to using Python to process data? After learning this module, you can master the intermediate-level and advanced uses of Python: data structure dictionaries and sets. In some applications, they can be very convenient. What’s special here is that, you can also feel the charm of such concise and efficient data structures: ndarray, Series and DataFrame in the most famous and widely applied scientific computing package SciPy in Python.

Welcome to learn Module 04 “Python data statistics and mining”! In this module, I will show you, over the entire process of data processing, the unique advantages of Python in data processing and analysis, and use many cases familiar to and loved by us to learn about and master methods and characteristics. After learning this module, you can preprocess the data and fast and effectively mine your desired or expected or unknown results from a large amount of data, and can also present those data in various images. In addition, the data statistics modes of all third party packages in Python are extraordinarily and surprisingly strong, but we, as average persons, can still understand and possess them.

Welcome to Module 05 “Object Orientation and Graphical User Interface”! In this module, I will guide you to understand what object orientation is and the relationship between graphical user interface and object orientation. Learners are only required to understand the concepts so that you can more freely and easily pick up various new functions in future. No program writing is required here. Besides, you also need to master the basic framework of GUI, common components and layout management. After learning them, you will find development with GUI is actually not remote.