Free Udemy Course __ Full-Stack AI Engineer 2026–Machine Learning Foundations - I

Build strong Machine Learning foundations with Python, real projects, and a Full-Stack AI Engineer mindset

4.5 (3,386 students students enrolled) English
data-science Machine Learning
Full-Stack AI Engineer 2026–Machine Learning Foundations - I

What You'll Learn

  • Build end-to-end machine learning pipelines from data preprocessing to model evaluation using industry best practices
  • Apply supervised, unsupervised, and ensemble ML algorithms to solve real-world regression, classification, and clustering problems
  • Prevent common ML failures by handling data leakage, feature scaling, encoding, and cross-validation correctly.
  • Optimize model performance using feature selection, hyperparameter tuning, and proper evaluation metrics.
  • Write clean, reusable, and production-ready ML code with reproducible workflows and pipelines.
  • Think like an ML engineer and design models that scale beyond notebooks into real-world systems.

Requirements

  • Basic Python knowledge (variables, loops, functions) is helpful but not required
  • No prior machine learning or statistics experience needed
  • A computer with internet access (Windows, macOS, or Linux)
  • Willingness to learn and practice with real-world datasets

Who This Course is For

  • Beginners and students who want a structured, end-to-end introduction to machine learning without prior experience
  • Software developers and data analysts looking to transition into machine learning and AI engineering roles
  • Aspiring ML engineers who want to move beyond notebooks and learn industry-grade ML workflows
  • Professionals and career switchers seeking practical, hands-on experience with real datasets and projects
  • Anyone interested in AI who wants to understand how machine learning models are built, optimized, and scaled in real systems

Your Instructor

Data Science Academy

Bridging knowledge to industry with Data & AI education

4.3 Instructor Rating

1,070 Reviews

50,911 Students

24 Courses

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