Course Overview
Are you ready to dive into the world of Machine Learning and transform raw data into powerful predictive models?
This comprehensive course will guide you through the entire journey—from building your first machine learning model to deploying it in a production environment. Whether you’re a beginner or have some experience, this course will equip you with the skills needed to excel in this cutting-edge field.
Throughout the course, we will cover:
Data Preprocessing (Cleaning and preparing your data for ML)
Supervised Learning (Building models for regression and classification)
Unsupervised Learning (Exploring clustering and dimensionality reduction techniques)
Model Evaluation and Tuning (Improving performance with validation and optimization)
Deep Learning (Introducing neural networks and advanced architectures)
Deployment (Making your model accessible through APIs and cloud services)
What you will learn
Data Preprocessing and Cleaning for Machine Learning Models
Understanding Supervised and Unsupervised Learning Techniques
Feature Engineering and Selection for Model Optimization
Building and Training Machine Learning Models with Python (e.g., Scikit-learn)
Model Evaluation and Tuning for Improved Accuracy
FINAL PROJECT: Deploying a Machine Learning Model to a Web Application
Course Curriculum
46
Lessons
(
5 hours
)
Course Review
Rock
Machine Learning: Train to Deploy gave me a solid foundation in both model training and deployment. The hands-on projects made the learning experience practical and engaging. I now feel confident deploying models into production environments.
Hanza
This course bridged the gap between theory and real-world application beautifully. From data preprocessing to deploying models on the cloud, everything was well-explained. A must for anyone serious about machine learning.
