Ementorhub

Skills you'll gain

Scalability

Anomaly Detection

Probability & Statistics

Data Manipulation

Statistical Analysis

Data Transformation

Data Analysis

Data Access

Exploratory Data Analysis

Statistical Inference

Workflow Management

Data Processing

Machine Learning

Data Cleansing

Feature Engineering

There are 5 modules in this course

By the end of this course you should be able to: Retrieve data from multiple data sources: SQL, NoSQL databases, APIs, Cloud Describe and use common feature selection and feature engineering techniques Handle categorical and ordinal features, as well as missing values Use a variety of techniques for detecting and dealing with outliers Articulate why feature scaling is important and use a variety of scaling techniques Who should take this course? This course targets aspiring data scientists interested in acquiring hands-on experience with Machine Learning and Artificial Intelligence in a business setting. What skills should you have? To make the most out of this course, you should have familiarity with programming on a Python development environment, as well as fundamental understanding of Calculus, Linear Algebra, Probability, and Statistics.

Retrieving and Cleaning Data

Exploratory Data Analysis and Feature Engineering

Inferential Statistics and Hypothesis Testing

Final Project