AI and Machine Learning Foundations - Python, Data Science, and MLOps

This introductory course presents core machine learning concepts, including supervised and unsupervised learning, regression, classification, bias-variance trade-offs, overfitting, regularization, and common algorithms. It also includes a data analytics project, a linear regression case study, and an MLOps movie recommendation system.

Syllabus

⌨️ Introduction
⌨️ Machine Learning Roadmap for 2024
⌨️ ML Basics Supervised vs. Unsupervised, Regression vs. Classification
⌨️ Machine Learning Bias-Variance Trade-off
⌨️ Machine Learning Overfitting Regularization
⌨️ Machine Learning Linear Regression Model
⌨️ Machine Learning Linear Regression Model As a Prediction Model
⌨️ Top 10 Machine Learning Algorithms
⌨️ Data Analysis : Superstore Data Analytics Project
⌨️ Machine Learning Linear Regression Case Study
⌨️ MLOps: Movie recommendation system.
⌨️ Workshop: How to Become a Data Scientist With No Experience
⌨️ Workshop: How to Build A Startup
⌨️ Machine Learning Interview Prep Thanks to our Champion and Sponsor supporters: