Python Basics for Data Science

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Free Online Course: Python Basics for Data Science provided by edX is a comprehensive online course, which lasts for 3 weeks long, 4-10 hours a week. The course is taught in English and is free of charge. Upon completion of the course, you can receive an e-certificate from edX. Python Basics for Data Science is taught by Joseph Santarcangelo.

Overview
  • Please Note: Learners who successfully complete this IBM course can earn a skill badge —a detailed, verifiable and digital credential that profiles the knowledge and skills you’ve acquired in this course. Enroll to learn more, complete the course and claim your badge!

    Kickstart your learning of Python for data science, as well as programming in general with this introduction to Python course. This beginner-friendly Python course will quickly take you from zero to programming in Python in a matter of hours and give you a taste of how to start working with data in Python. ~~~~

    Upon its completion, you'll be able to write your own Python scripts and perform basic hands-on data analysis using our Jupyter-based lab environment. If you want to learn Python from scratch, this course is for you.

    You can start creating your own data science projects and collaborating with other data scientists using IBM Watson Studio. When you sign up, you will receive free access to Watson Studio. Start now and take advantage of this platform and learn the basics of programming, machine learning, and data visualization with this introductory course.

Syllabus
  • Module 1 - Python Basics
    Your first program
    Types
    Expressions and Variables
    String Operations

    Module 2 - Python Data Structures
    Lists and Tuples
    Sets
    Dictionaries

    Module 3 - Python Programming Fundamentals
    Conditions and Branching
    Loops
    Functions
    Objects and Classes

    Module 4 - Working with Data in Python
    Reading files with open
    Writing files with open
    Loading data with Pandas
    Working with and Saving data with Pandas

    Module 5 - Working with Numpy Arrays
    Numpy 1d Arrays
    Numpy 2d Arrays