Python has become one of the most in-demand programming languages in the world. From data science and artificial intelligence to software and web development, Python powers some of the most impactful technologies today. The Python for Data Science, AI & Development course is designed to take you from a complete beginner to a confident Python programmer with real-world, job-ready skills.
This beginner-friendly, self-paced course is ideal for anyone looking to build a strong foundation in Python and apply it to modern technology roles.
What You’ll Learn in This Course
This course focuses on both core programming concepts and practical data handling skills, ensuring you gain hands-on experience along with theoretical understanding.
Python Programming Fundamentals
You’ll start by learning the basics of Python, including:
- Python syntax and expressions
- Variables and data types (integers, floats, strings)
- String operations, indexing, formatting, and escape sequences
You’ll write your first Python programs and practice concepts using interactive labs in Jupyter Notebooks.
Data Structures in Python
A strong understanding of data structures is essential for efficient programming. In this course, you’ll learn:
- Lists and tuples (indexing, slicing, sorting, cloning)
- Dictionaries (key-value data handling)
- Sets and set operations
By the end of this module, you’ll be able to store, access, and manipulate data effectively.
Python Programming Fundamentals (Logic & OOP)
This module strengthens your programming logic and problem-solving skills:
- Conditions and branching
- For loops and while loops
- Functions (built-in and user-defined)
- Exception handling for robust programs
- Object-Oriented Programming (OOP) using classes and objects
You’ll learn how to model real-world problems using Python and write reusable, clean code.
Working with Data in Python
This module focuses on real-world data handling, a must-have skill for data-related roles:
- Reading and writing files (TXT, CSV, JSON)
- File I/O operations
- Data manipulation using Pandas
- Numerical computing with NumPy
You’ll gain hands-on experience working with structured datasets and performing data analysis.
APIs and Data Collection
In the final module, you’ll learn how to collect data from external sources:
- Working with REST APIs using the
requestslibrary - Handling JSON responses
- Web scraping with BeautifulSoup
- Collecting structured and unstructured data
This module prepares you to gather real-world data for analysis, automation, and AI projects.
Skills You’ll Gain
By completing this course, you’ll develop in-demand skills such as:
- Python Programming
- Data Analysis & Data Manipulation
- Pandas and NumPy
- Data Structures
- Object-Oriented Programming (OOP)
- File I/O and Data Import/Export
- REST APIs and Web Scraping
- JSON handling
- Automation
- Jupyter Notebooks
These skills are highly valuable across multiple technology domains.
Course Structure at a Glance
- Total Modules: 5
- Learning Style: Beginner-friendly, self-paced
- Practice: Hands-on labs using Jupyter Notebooks
- Assessment: Labs, exercises, and a final exam
- Certificate: Shareable career certificate on completion
Who Should Take This Course?
This course is suitable for:
- Aspiring Data Scientists and Data Analysts
- Students and freshers entering tech
- Software and Python developers
- AI and Machine Learning enthusiasts
- Data Engineers and DevOps learners
- Anyone interested in automation and data-driven roles
No prior programming experience is required.
Build Job-Ready Expertise
When you enroll, you’ll:
- Learn from industry experts
- Build a strong Python foundation
- Develop job-relevant, practical skills
- Work on real-world scenarios
- Earn a shareable certificate for your resume and LinkedIn
Final Thoughts
The Python for Data Science, AI & Development course is a powerful starting point for anyone looking to enter or grow in the tech industry. With its structured modules, hands-on labs, and focus on real-world applications, this course equips you with the skills needed to work confidently with Python, data, APIs, and automation.
course link: https://www.coursera.org/learn/python-for-applied-data-science-ai#modules
