Courses Information

Learn foundational machine learning algorithms, starting with data cleaning and supervised models. Then, move on to exploring deep and unsupervised learning. At each step, get practical experience by applying your skills to code exercises and projects.

You will learn about training data, and how to use a set of data to discover potentially predictive relationships.

Curriculum

Module 1 - Introduction To Machine Learning And AI Concepts

Module 2 - Foundation of ML / AI (Python)

Module 3 - Foundation of ML / AI (R Programming)

Module 4 - Descriptive Statistics

Module 5 - Data Acquisition

Module 6 - Data Pre-processing and Preparation

Module 7 - Supervised Learning

Module 8 - Unsupervised Learning

Module 9 - Support Vector Machines

Module 10 - Ensemble Techniques

Module 11 - Reinforcement Learning

Module 12 - ARTIFICIAL INTELLIGENCE

Module 13 - Convolution Neural Networks

Module 14 - Recurrent Neural Network

Module 15 - Natural Language Processing

Module 16 - Predictive Analysis

Module 17 - Deep Learning

Module 18 - TensorFlow

Module 19 – Computer Vision