Course
Data Science
Machine Learning
Algorithms
Continuing Education

Machine Learning with Python

0 credit hours

Credits awarded upon completion

Self-Paced

Progress at your own speed

20.04 hours

Estimated learning time

About the Course

Description

Python is one of the most widely used programming languages in machine learning (ML), and many ML job listings require it as a core skill. This course equips aspiring machine learning practitioners with essential Python skills that help them stand out to employers.

Throughout the course, you’ll dive into core ML concepts and learn about the iterative nature of model development. With Python libraries like Scikit-learn, you’ll gain hands-on experience with tools used for real-world applications. Plus, you’ll build a foundation in statistical methods like linear and logistic regression.

You’ll explore supervised learning techniques with libraries such as Matplotlib and Pandas, as well as classification methods like decision trees, KNN, and SVM, covering key concepts like the bias-variance tradeoff. The course also covers unsupervised learning, including clustering and dimensionality reduction.

With guidance on model evaluation, tuning techniques, and practical projects in Jupyter Notebooks, you’ll gain the Python skills that power your ML journey. ENROLL TODAY to enhance your resume with in-demand expertise!

This Course is part of a program

You can only buy it along with program.

Sections

Schedule

Asynchronous

Delivery method

Online

Deliverables

  • 0 Credits

    Academic Excellence

    Earn necessary number of credit hours for completing this content

  • Hone Important Skills

    Total Upgrade

    Such as Supervised Learning, Regression Analysis, Unsupervised Learning, Machine Learning, Dimensionality Reduction, Scikit Learn (Machine Learning Library), Feature Engineering, Statistical Modeling, Matplotlib, Python Programming, Predictive Modeling, Classification And Regression Tree (CART), Jupyter, NumPy