Python for Machine Learning

Master the skills to utilize machine learning in your daily tasks with our Python course. Acquire the expertise to develop algorithms for predicting classes, continuous values, and more.

This course is tailored for individuals with prior Python knowledge who are eager to deepen their understanding of applying Python for machine learning. With a focus on SciKit Learn, you will explore various aspects of machine learning, including different regression types such as Linear, Lasso, Ridge, and Elastic Net. Additionally, you will delve into K Nearest Neighbors, Mean Clustering, Hierarchical Clustering, DBSCAN, PCA, and Model Deployment.

Upon completion, you will receive 6-month access to the full course content in an on-demand format, providing ongoing support for post-class reference and review.

Course Objectives:

– Acquire proficiency in using Python for data science applications

– Develop data pipeline workflows to analyze, visualize, and extract insights from data

– Establish a portfolio of data science projects using real-world data

– Analyze datasets and derive insights through data science techniques

– Master essential data science skills

– Replicate real-world scenarios and generate data reports

– Learn NumPy for numerical processing in Python

– Perform feature engineering on real-world case studies

– Master Pandas for data manipulation in Python

– Utilize Matplotlib to create customized data visualizations in Python

– Utilize Seaborn to generate visually appealing statistical plots in Python

– Build a modern portfolio of data science projects for your resume

– Quickly set up the Anaconda data science stack environment