Python Basics
This course introduces the basics of Python 3, including conditional execution and iteration as control structures, and strings and lists as data structures. You'll program an on-screen Turtle to draw pretty pictures. You'll also learn to draw reference diagrams as a way to reason about program executions, which will help to build up your debugging skills. The course has no prerequisites. It will cover Chapters 1-9 of the textbook "Fundamentals of Python Programming," which is the accompanying text (optional and free) for this course.

The course is for you if you're a newcomer to Python programming, if you need a refresher on Python basics, or if you may have had some exposure to Python programming but want a more in-depth exposition and vocabulary for describing and reasoning about programs. This is the first of five courses in the Python 3 Programming Specialization.

Python Functions, Files, and Dictionaries
This course introduces the dictionary data structure and user-defined functions. You'll learn about local and global variables, optional and keyword parameter-passing, named functions and lambda expressions. You'll also learn about Python's sorted function and how to control the order in which it sorts by passing in another function as an input. For your final project, you'll read in simulated social media data from a file, compute sentiment scores, and write out .csv files. It covers chapters 10-16 of the textbook "Fundamentals of Python Programming," which is the accompanying text (optional and free) for this course.

The course is well-suited for you if you have already taken the "Python Basics" course and want to gain further fundamental knowledge of the Python language. Together, both courses are geared towards newcomers to Python programming, those who need a refresher on Python basics, or those who may have had some exposure to Python programming but want a more in-depth exposition and vocabulary for describing and reasoning about programs. This is a follow-up to the "Python Basics" course (course 1 of the Python 3 Programming Specialization), and it is the second of five courses in the specialization.

Data Collection and Processing with Python
This course teaches you to fetch and process data from services on the Internet. It covers Python list comprehensions and provides opportunities to practice extracting from and processing deeply nested data. You'll also learn how to use the Python requests module to interact with REST APIs and what to look for in documentation of those APIs. For the final project, you will construct a "tag recommender" for the flickr photo sharing site.

The course is well-suited for you if you have already taken the "Python Basics" and "Python Functions, Files, and Dictionaries" courses (courses 1 and 2 of the Python 3 Programming Specialization). If you are already familiar with Python fundamentals but want practice at retrieving and processing complex nested data from Internet services, you can also benefit from this course without taking the previous two. This is the third of five courses in the Python 3 Programming Specialization.

Python Classes and Inheritance
This course introduces classes, instances, and inheritance. You will learn how to use classes to represent data in concise and natural ways. You'll also learn how to override built-in methods and how to create "inherited" classes that reuse functionality. You'll also learn about how to design classes. Finally, you will be introduced to the good programming habit of writing automated tests for their own code.

The course is best-suited for you if you are already familiar with Python fundamentals, which are covered in the "Python Basics" and "Python Functions, Files, and Dictionaries" courses (courses 1 and 2 of the Python 3 Programming Specialization). It is optional to have taken the "Data Collection and Processing with Python" course (course 3 of the specialization), but knowledge of retrieving and processing complex nested data is helpful. This is the fourth of five courses in the Python 3 Programming Specialization.

Python Project: pillow, tesseract, and opencv
This course will walk you through a hands-on project suitable for a portfolio. You will be introduced to third-party APIs and will be shown how to manipulate images using the Python imaging library (pillow), how to apply optical character recognition to images to recognize text (tesseract and py-tesseract), and how to identify faces in images using the popular opencv library. By the end of the course you will have worked with three different libraries available for Python 3 to create a real-world data-analysis project.

The course is best-suited for learners who have taken the first four courses of the Python 3 Programming Specialization. Learners who already have Python programming skills but want to practice with a hands-on, real-world data-analysis project can also benefit from this course. This is the fifth and final course in the Python 3 Programming Specialization.

Citación :

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