Applied Data Science and Machine Learning
Analyze data and build ML models using Pandas, NumPy, Scikit-learn, and Jupyter.
Course overview
Analyze data and build ML models using Pandas, NumPy, Scikit-learn, and Jupyter.
What you’ll learn
- Understand the range of ML algorithm.
- Master feature engineering and selection Techniques.
- Learn about model evaluation and hyperparameter tuning
- Deploy machine learning models as APIs.
- Understanding the ethics and biases in machine learning.
- Build a portfolio of ML projects.
Course Curriculum
A structured, progressive curriculum designed to build depth, intuition, and real-world proficiency over time.
This section introduces key concepts and builds intuition through structured lessons and exercises.
Who this course is for
- Solid understanding of Python and Pandas
- Basic knowledge of linear algebra and probability
- Familiarity with machine learning fundamentals
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Want to know whether this course is right for you?
Send an enquiry with your learning goals and the Variable team can help you with the next step.