Machine Learning – Course Content

Machine Learning is a revolutionary field of artificial intelligence that enables computers to learn from data and make predictions or decisions without being explicitly programmed. It is widely used in various industries such as healthcare, finance, marketing, and automation. The core of machine learning lies in algorithms that identify patterns in data, allowing businesses and researchers to develop intelligent systems that improve over time.

This course provides an in-depth understanding of machine learning concepts, covering essential topics such as supervised and unsupervised learning, deep learning, natural language processing, and model deployment. It is designed for students, professionals, and data enthusiasts who want to build expertise in this fast-growing domain. With hands-on projects, real-world applications, and expert-led training, learners will gain the necessary skills to apply machine learning in practical scenarios.

If you’re ready to enhance your career in AI and Machine Learning, explore the course details at CNT Tech and take the first step towards mastering ML.

Module 1: Core Python Practice

Module 2: Python Libraries for Data Science

Module 3: Analysis and Visualization of Data

Module 4: Linear & Logistic Regression

Module 5: Introduction to Machine Learning

Module 6: Unsupervised Learning: Segmentation

Module 7: Clustering of K-Means

Module 8: Decision Tree

Module 9: Types of Decision Tree Algorithms

Module 10: Modeling Process

Module 11: Ensemble Learning (Supervised)

Module 12: Methods of Ensembling

Module 13: Neural Networks

Module 14: Single Layered Neural Network

Module 15: Multi Layered Neural Network

Module 16: Support Vector

Module 17: Validating SVM models

Module 18: K-Nearest Neighbors (KNN) Algorithm

Module 19: Naïve Bayes Theorem

Module 20: Applications of Naive Bayes

Module 21: Data Mining Concept

Module 22: Implementation of Algorithms