[Coursera] Python for Data Science, AI & Development
About this Course
Kickstart your learning of Python for data science, as well as programming in general, with this beginner-friendly introduction to Python. Python is one of the world’s most popular programming languages, and there has never been greater demand for professionals with the ability to apply Python fundamentals to drive business solutions across industries.
This course will take you from zero to programming in Python in a matter of hours—no prior programming experience necessary! You will learn Python fundamentals, including data structures and data analysis, complete hands-on exercises throughout the course modules, and create a final project to demonstrate your new skills. By the end of this course, you’ll feel comfortable creating basic programs, working with data, and solving real-world problems in Python. You’ll gain a strong foundation for more advanced learning in the field, and develop skills to help advance your career. This course can be applied to multiple Specialization or Professional Certificate programs. Completing this course will count towards your learning in any of the following programs: IBM Applied AI Professional Certificate Applied Data Science Specialization IBM Data Science Professional Certificate Upon completion of any of the above programs, in addition to earning a Specialization completion certificate from Coursera, you’ll also receive a digital badge from IBM recognizing your expertise in the field.
Explain Python Basics including Types, Expressions, and Variables.
Describe Data Structures in Python including Lists, Tuples, Dictionaries, Sets.
Apply Python programming using Branching, Loops, Functions, Objects & Classes.
Work with data in Python using Pandas and Numpy libraries.
Skills you will gain
- Data Science
- Python Programming
- Data Analysis
Python for Data Science, AI & Development is a Python programming language course and its application in data science, artificial intelligence and software development, published by Coursera Academy. This course is one of the most popular Python introductory courses at Coursera Academy, prepared in partnership with IBM, and is a prerequisite for a range of Corsara training programs and collections. Python is one of the most popular and widely used programming languages in the world and is used in almost all companies and various industrial fields, from artificial intelligence to software development. There is a huge demand for professional Python developers, and this demand is expected to continue to rise in the coming years.
This course is completely beginner and can introduce you to the basics of the Python programming language in just one hour. This training course is completely project-oriented and during its training process, you will get acquainted with the data structure and data analysis process in Python. As mentioned a while ago, this training course is considered as a prerequisite in a series of official programs and Corsara training sets, the most important of which are the following:
- IBM Data Analyst Professional Certificate
- IBM DevOps and Software Engineering Professional Certificate
- Data Science Fundamentals with Python and SQL Specialization
- IBM Data Engineering Professional Certificate
- IBM Applied AI Professional Certificate
- Data Engineering Foundations Specialization
- IBM Full Stack Software Developer Professional Certificate
- Applied Data Science Specialization
- IBM Data Science Professional Certificate
What you will learn in The Python for Data Science, AI & Development
- Basic principles of Python programming language such as data types (data types), variables and expressions (Expressions)
- Types of data structures in the Python programming language such as lists, collections or sets, dictionaries, etc.
- Categories, objects, functions, loops, and classes in the Python programming language and the uses and benefits of each
- Pandas and Numpy data analysis libraries
- Data science
- And …
Instructors: Joseph Santarcangelo
Number of Weeks: 5
Duration: Approximately 21 hours
Size: 201.14 MB