Introduction to Data Science and AI with Python (Part 2) - Oladeinde Muis | Learnkasts
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Introduction to Data Science and AI with Python (Part 2)

Take your Python skills to the next level by building real-world projects, mastering OOP, working with databases, handling errors, using GitHub, and exploring the foundations of Data Science and AI development.

1 learner 9 lessons · 4h 30m Beginner
OM Created by Oladeinde Muis
What you'll learn
Welcome to Part 2 of Introduction to Data Science and AI with Python , where you transition from learning fundamentals to building real-world, practical applications.
This course is designed to strengthen your programming foundation and prepare you for data-driven and AI-focused development.

What You’ll Learn

You will move beyond basic syntax and start applying Python in real development scenarios:
  •  Complete a Milestone Project with 6 practical coding challenges
  •  Master Object-Oriented Programming (OOP)
  •  Implement professional Error Handling techniques
  •  Work with Files, Modules, Libraries, and Packages
  •  Use Regular Expressions (Regex) for text processing
  •  Learn version control with Git & GitHub
  •  Connect Python with SQL databases
  •  Build a complete Capstone Project from scratch




  • Why This Course Matters

  • Data Science and AI require more than just knowing Python syntax. You need to:
    • Structure scalable programs
    • Handle real-world data
    • Organize code professionally
    • Work with databases
    • Manage projects using version control
    • Apply logical and analytical thinking
  • This course bridges the gap between beginner programming and real-world development.
  •  
    Who This Course Is For

    • Students who completed Python basics (Part 1)
    • Beginners ready to move toward Data Science and AI
    • Aspiring developers who want practical experience
    • Anyone who wants to build structured, real-world Python projects

  •  By the End of This Course

  • You will be able to:
    • Build structured applications using OOP
    • Handle errors like a professional developer
    • Work with files and databases
    • Use GitHub confidently
    • Write cleaner, more maintainable code
    • Develop a complete end-to-end Python project
  • This course marks your transition from Python learner to Python practitioner, ready to explore Data Science, Machine Learning, and AI with confidence.
Curriculum
1 module · 9 lessons
Introduction to Data Science and AI with Python (Part 2) 9 lessons · 4h 30m
FIRST MILESTONE PROJECT (6 Practical Challenges) 50 min
OBJECT-ORIENTED PROGRAMMING (OOP) IN PYTHON 30 min
ERROR HANDLING IN PYTHON 20 min
ERROR HANDLING IN PYTHON 20 min
FILES, LIBRARIES, PACKAGES, AND MODULES 20 min
REGULAR EXPRESSIONS IN PYTHON 30 min
COMPLETE GUIDE TO GITHUB FOR BEGINNERS 20 min
GETTING STARTED WITH SQL IN PYTHON 30 min
FINAL CAPSTONE PROJECT 50 min
OM
Oladeinde Muis
₦30,000

What's included

9 lessons
1 module
4h 30m
Access on any device
Lifetime access
Secure checkout via Paystack