Become a Machine Learning Engineer

Learn Python

This module demystifies the foundations of Python, providing a comprehensive Python tutorial for beginners and guiding absolute novices to learn Python programming from scratch.

Python Libraries

Learn to effectively process and visualize data using Python data structures, loops, and libraries to master data science techniques in Python.

Rock Paper Scissors Game

Create a Rock Paper Scissors game in Python to enhance your programming skills and showcase a practical Python project in your portfolio.

Object Oriented Programming in Python

In this module, you’ll explore object-oriented programming in Python by building a social media app using classes, inheritance, and encapsulation.

Machine Learning for Beginners

Learn machine Learning for beginners with key topics like the machine learning process, scikit-learn, artificial neural networks, and gradient descent to become a skilled machine learning engineer.

Preprocessing Data

Master data preprocessing and modeling techniques with scikit-learn. Build machine learning models like linear regression and decision trees, focusing on data training, testing, and evaluation.

Machine Learning Project Using scikit-learn

Learn to build and optimize neural networks and support vector machines (SVMs) with scikit-learn. Tackle machine learning challenges through practical exercises and solution reviews.

Machine Learning Challenges

Fine-tune neural networks and classify non-linear data using support vector machines (SVMs) with scikit-learn. Tackle machine learning challenges by optimizing various machine learning models.

Unsupervised Learning

Explore clustering with scikit-learn, focusing on unsupervised learning techniques like K-Means, DBSCAN, cosine similarity, nearest neighbors, and cluster evaluation.

Customer Segmentation with K-Means Clustering

Implement customer segmentation with K-Means clustering to refine marketing efforts and enhance experiences through targeted strategies using the K-Means algorithm in unsupervised learning.

Deep Learning Models

Explore deep learning models with convolutional neural networks (CNNs) and apply your skills in an AI-powered image colorization project, featuring face extraction and colorization exercises.