Data Analysis and Statistics

Statistics for Business – I

Essential Math for Machine Learning: Python Edition

Introduction to Big Data

Supply Chains for Manufacturing II

Marketing Analytics: Data Tools and Techniques

Market Segmentation Analysis

Evidence-Based Management Foundations

Data Science Ethics

Data Science: R Basics

Using GPUs to Scale and Speed-up Deep Learning

Foundations of Data Science: Inferential Thinking by Resampling

IoT Programming and Big Data

Machine Learning with Python: A Practical Introduction

Introduction to R for Data Science

Machine Learning Fundamentals

Introduction to Artificial Intelligence (AI)

Data Mining: Theories and Algorithms for Tackling Big Data

Data Science: Probability

Demystifying Biomedical Big Data: A User’s Guide

An Introduction to Credit Risk Management

CERTaIN: Observational Studies and Registries

Data Analysis: A Practical Introduction for Absolute Beginners

Marketing Analytics: Competitive Analysis and Market Segmentation

Theory of Change for Development

Data Analysis for Decision Making

Principles of Machine Learning: R Edition

Six Sigma: Define and Measure

Data Science Research Methods: Python Edition

Business and Data Analysis Skills

Querying Data with Transact-SQL

CERTaIN: Patient-Centered Outcomes Research

Programming Reactive Systems

Probability and Statistics in Data Science using Python

Introduction to Analytics Modeling

Processing Real-Time Data Streams in Azure

Evidence-Based Technology Management

Statistical Thinking for Data Science and Analytics

Supply Chains for Manufacturing I

Data Science and Machine Learning Capstone Project

Big Data and Education

Big Data Capstone Project

Lean Production

Python for Data Science

Data Analytics for Business

Orchestrating Big Data with Azure Data Factory

Data Visualization: A Practical Approach for Absolute Beginners

Processing Big Data with Azure Data Lake Analytics

CERTaIN: CER/PCOR Methods: Introduction