Python Data Science and Machine Learning: Zero to Production

About this course

Data Science and Machine Learning are transforming every industry, and there has never been a better time to build these skills. Whether you are a student, software developer, data analyst, or working professional, this course will take you from the fundamentals to building and deploying real machine learning applications.

This is not a course that only explains algorithms with slides. Instead, you'll learn by building practical projects and understanding why each concept matters in the real world. Every topic is explained in a simple, beginner friendly way with hands on coding examples.

By the end of this course, you'll have the confidence to analyze data, build machine learning models, evaluate their performance, and deploy them as production ready REST APIs using FastAPI and Docker.

What you'll learn

You will build a strong foundation in Data Science and Machine Learning, including:

• Python programming for Data ScienceEssential Mathematics and Statistics for Machine Learning
• Data Visualization using popular Python libraries
• Exploratory Data Analysis (EDA) with a real-world movie streaming customer churn dataset
• Data Cleaning and Feature Engineering techniques
• Supervised Machine Learning using Scikit-LearnUnsupervised Machine Learning and clustering techniques
• Model evaluation and performance metrics
• Building REST APIs with FastAPIContainerizing machine learning applications using DockerDeploying trained machine learning models for real-world use

Machine Learning Algorithms CoveredRegressionLinear Regression

Polynomial RegressionClassificationLogistic Regression

Support Vector Machine (SVM)K-Nearest Neighbors (KNN)Naive BayesDecision TreeRandom Forest

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