Discover how to use Python for data science in this four-hour course. Learn how you can use Python to store and manipulate data before you move on to analysis.
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Running Sum (Exercise) Raising Your Own Exceptions Python Dates and Times Understanding Time The time Module Time Structures Times as Strings Time and Formatted Strings Pausing Execution withtime.sleep() ThedatetimeModule datetime.datetimeObjects
Python Console Exercise: Librarian Project: Guess the Word Project: The Game of PigCourse Resources Here are a few examples of teacher resources and materials to use in the Introduction to Python Programming course Sample Handout (student): Lesson 1.4 Sample Handout (teacher): Lesson 1.4 Lesson...
Discover how you can use deep learning to run natural language processing, image recognition, and artificial intelligence with Python package, Keras 2.0.
Module 1: Course Introduction This course covers the basics of Python and provides you with knowledge to solve real-world problems using Python. Module 2: Input-Output Process in Python In this module, you will learn what input and output data are, how to handle input and output data, how...
Power up your career with the best and most popular data science language, Python. Leverage your Python skills to start your Data Science journey. This free data science course is intended for beginners with no coding or Data Science background.
Whether you're interested in writing simple scripts, full programs, or graphical user interfaces, this course will give you the tools you need to use Python with skill and confidence. Syllabus Lesson 1 - Welcome to Python Two things that make Python attractive are that it's a free download ...
Learn how to write a few lines of Python code, declare variables, and work with console input and outputLearning objectives In this module, you will: Explore the choices available to run Python apps Use the Python interpreter to execute statements and scripts Learn how to declare variables ...
Python Scientific Lecture Notes byEuroScipy tutorial team Teaching material on the scientific Python ecosystem, a quick introduction to central tools and techniques. The different chapters each correspond to a 1 to 2 hours course with increasing level of expertise, from beginner to expert. ...