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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鈥檒l dive into core ML concepts and learn about the iterative nature of model development. With Python libraries like Scikit-learn, you鈥檒l gain hands-on experience with tools used for real-world applications. Plus, you鈥檒l build a foundation in statistical methods like linear and logistic regression. You鈥檒l 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鈥檒l gain the Python skills that power your ML journey. ENROLL TODAY to enhance your resume with in-demand expertise!