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IBM

Python for Data Science, AI & Development

IBM via Coursera

Overview

Kickstart your learning of Python with this beginner-friendly self-paced course taught by an expert. Python is one of the most popular languages in the programming and data science world and demand for individuals who have the ability to apply Python has never been higher. This introduction to Python course will take you from zero to programming in Python in a matter of hours—no prior programming experience necessary! You will learn about Python basics and the different data types. You will familiarize yourself with Python Data structures like List and Tuples, as well as logic concepts like conditions and branching. You will use Python libraries such as Pandas, Numpy & Beautiful Soup. You’ll also use Python to perform tasks such as data collection and web scraping with APIs. You will practice and apply what you learn through hands-on labs using Jupyter Notebooks. By the end of this course, you’ll feel comfortable creating basic programs, working with data, and automating real-world tasks using Python. This course is suitable for anyone who wants to learn Data Science, Data Analytics, Software Development, Data Engineering, AI, and DevOps as well as a number of other job roles.

Syllabus

  • Python Basics
    • This module teaches the basics of Python and begins by exploring some of the different data types such as integers, real numbers, and strings. Continue with the module and learn how to use expressions in mathematical operations, store values in variables, and the many different ways to manipulate strings.
  • Python Data Structures
    • This module begins a journey into Python data structures by explaining the use of lists and tuples and how they are able to store collections of data in a single variable. Next learn about dictionaries and how they function by storing data in pairs of keys and values, and end with Python sets to learn how this type of collection can appear in any order and will only contain unique elements.
  • Python Programming Fundamentals
    • This module discusses Python fundamentals and begins with the concepts of conditions and branching. Continue through the module and learn how to implement loops to iterate over sequences, create functions to perform a specific task, perform exception handling to catch errors, and how classes are needed to create objects.
  • Working with Data in Python
    • This module explains the basics of working with data in Python and begins the path with learning how to read and write files. Continue the module and uncover the best Python libraries that will aid in data manipulation and mathematical operations.
  • APIs and Data Collection
    • This module delves into the unique ways to collect data by the use of APIs and web scraping. It further explores data collection by explaining how to read and collect data when dealing with different file formats.

Taught by

Joseph Santarcangelo

Reviews

2.3 rating, based on 3 Class Central reviews

4.6 rating at Coursera based on 35435 ratings

Start your review of Python for Data Science, AI & Development

  • This is a basic introduction to Python for whoever wants to start with data science and AI. If you are completely new to Python you will probably need more exercise than just this course. For people with Python experience, this can be a good rehearsal if your skills are a bit rusty.

    The Coursera certificate is not worth the money in my opinion. If you are happy with an IBM certificate instead you can follow the same course for free at https://cognitiveclass.ai/courses/python-for-data-science including the certificate
  • Profile image for Trang Le
    Trang Le
    Sometimes I got freaked out when I completed a course with flying colors and felt like I didn't get anything out of it. Unfortunately, that's exactly my experience with this course, Python for Data Science and AI offered by IBM. If you are consider…

  • "Python for Data Science, AI & Development is an excellent course. It provides a comprehensive and practical introduction to Python's applications in data science and AI. The content is well-structured, and the hands-on exercises are valuable for real-world proficiency. Whether you're a beginner or have some programming experience, this course offers valuable insights and skills. Highly recommended!"

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