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Python for Data Science, AI & Development Course By IBM

Python for Data Science, AI & Development Course By IBM Course

The "Python for Data Science, AI & Development" course offers a comprehensive introduction to Python programming. It's particularly beneficial for individuals seeking to understand and apply Pytho...

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9.8/10 Highly Recommended

Python for Data Science, AI & Development Course By IBM on Coursera — The "Python for Data Science, AI & Development" course offers a comprehensive introduction to Python programming. It's particularly beneficial for individuals seeking to understand and apply Python in data science and AI contexts.

Pros

  • Beginner-friendly with no prior experience required.
  • Taught by experienced instructors from IBM.
  • Flexible schedule accommodating self-paced learning.
  • Applicable to both technical and non-technical audiences.​

Cons

  • Limited focus on advanced Python topics; further courses are needed for deeper exploration.
  • Some learners may seek more extensive hands-on projects or real-world datasets.

Python for Data Science, AI & Development Course By IBM Course

Platform: Coursera

What you will learn in Python for Data Science, AI Development By IBM Course

  • Understand Python basics, including data types, variables, expressions, and string operations.
  • Utilize Python data structures such as lists and tuples, and apply logic concepts like conditions and branching.
  • Work with Python libraries like Pandas, NumPy, and Beautiful Soup for data manipulation and web scraping.

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  • Perform tasks such as data collection and automation using Python.
  • Develop and test Python code using Jupyter Notebooks.​

Program Overview

Python Basics

⏱️2 hours

  • Introduction to Python and Jupyter Notebooks.

  • Understanding data types, expressions, variables, and string operations.​​

Python Data Structures

⏱️4 hours

  • Exploring lists, tuples, dictionaries, and sets.

  • Manipulating data structures and understanding their applications.​

Python Programming Fundamentals

⏱️ 5 hours

  • Implementing conditions, branching, loops, and functions.

  • Understanding objects and classes in Python.​

Working with Data in Python

⏱️ 7 hours

  • Using Pandas and NumPy for data analysis.

  • Reading and writing files, and working with APIs.​​​

Python Project

⏱️ 7 hours

  •  Applying learned skills in a hands-on project.
  • Demonstrating proficiency in Python for data science tasks.​

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Job Outlook

  • Proficiency in Python is essential for roles such as Data Analyst, Data Scientist, and AI Developer.
  • Skills acquired in this course are applicable across various industries, including technology, healthcare, finance, and more.
  • Completing this course can enhance your qualifications for entry-level positions in data science and AI development.

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FAQs

Who is this course best suited for, and what career value does it offer?
Ideal for aspiring data scientists, AI developers, analysts, or software professionals, especially those entering data-focused fields. Teaches real-world Python skills applicable across careers in tech, AI, data engineering, and automation. You'll earn a shareable certificate from IBM, which can enhance your portfolio or resume.
What are the strengths and limitations of this course?
Strengths: Developed by IBM, with practical, hands-on labs in Jupyter Notebooks. Strong learner reviews (e.g., 4.7/5 rating). Limitations: Focuses on Python fundamentals—does not teach advanced AI, ML, or data visualization applications. Better suited as an introductory course rather than a deep dive.
What skills and topics will I learn?
You’ll develop practical Python capabilities, including: Core programming fundamentals like variables, strings, loops, functions, OOP, and exception handling. Essential data structures including lists, tuples, dictionaries, and sets. Data manipulation with NumPy and Pandas, and file handling (CSV, JSON, etc.). API interaction and web scraping techniques using libraries like requests and BeautifulSoup.
Do I need any prior programming experience?
No prior experience needed—it’s tailored for complete beginners. Covers fundamental syntax through to data handling and automation.
How long does the course take, and is it self-paced?
Composed of 5 modules, covering everything from basics to APIs and web scraping. Estimated completion time is around 25 hours, though some sources list 19 hours, depending on pace. Designed to be self-paced, allowing for flexible scheduling.

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