Python for Data Science, AI & Development

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What Will You Learn?

Describe Python Basics including Data Types, Expressions, Variables, and Data Structures.
Apply Python programming logic using Branching, Loops, Functions, Objects & Classes.
Demonstrate proficiency in using Python libraries such as Pandas, Numpy, and Beautiful Soup.
Access web data using APIs and web scraping from Python in Jupyter Notebooks.  

About This Course

Provider: Coursera
Format: Online
Duration: 25 hours to complete [Approx]
Target Audience: Beginners
Learning Objectives: By the end of this free course, you’ll feel comfortable creating basic programs, working with data, and automating real-world tasks using Python.
Course Prerequisites: NA
Assessment and Certification: NA
Instructor: IBM
Key Topics: Data Science, Data Analysis, Python Programming, Numpy, Pandas
Topic Covered: 
  1. - Types
  2. - Expressions and Variables
  3. - String Operations
  4. - List and Tuples
  5. - Dictionaries
  6. - Sets
  7. - Conditions and Branching
  8. - Loops
  9. - Functions
  10. - Exception Handling
  11. - Objects and Classes
  12. - Reading Files with Open
  13. - Writing Files with Open
  14. - Loading Data with Pandas
  15. - Pandas: Working with and Saving Data
  16. - One Dimensional Numpy
  17. - Two Dimensional Numpy
  18. - Simple APIs 
  19. - REST APIs & HTTP Requests
  20. - Optional: HTML for Webscraping
  21. - Webscraping
  22. - Working with different file formats (csv, xml, json, xlsx)

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