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

Created by Oladeinde Muis

₦30,000

What's included

  • 9 lessons
  • 1 module
  • 4h 30m
  • Access on any device
  • Lifetime access

Secure checkout via Paystack

Curriculum

1 module · 9 lessons

  • 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

Description

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.

Your instructor

Oladeinde Muis

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