Ementorhub

Skills you'll gain

Artificial Intelligence and Machine Learning (AI/ML)

Business Logic

Predictive Modeling

Feature Engineering

Machine Learning Algorithms

Large Language Modeling

Artificial Neural Networks

Statistical Machine Learning

Deep Learning

Reinforcement Learning

Decision Tree Learning

Data Modeling

Generative AI

Unsupervised Learning

Performance Metric

Applied Machine Learning

Dimensionality Reduction

Supervised Learning

There are 5 modules in this course

By the end of this course, you will be able to: 1. Implement, evaluate, and explain supervised, unsupervised, and reinforcement learning algorithms. 2. Apply feature selection and engineering techniques to improve model performance. 3. Describe deep learning models for complex AI tasks. 4. Assess the suitability of various AI & ML techniques for specific business problems. To be successful in this course, you should have intermediate programming knowledge of Python, plus basic knowledge of AI and ML capabilities, and newer capabilities through generative AI (GenAI) and pretrained large language models (LLM). Familiarity with statistics is also recommended.

Unsupervised learning

Reinforcement learning and other approaches

Deep learning and neural networks

The concepts in practice