Artificial Intelligence and Machine Learning for Business

Discover how predictive analytics could transform your business

As businesses accrue more and more data about their customers – from their behavioural history to their transactions – being able to use ‘Big Data’ is becoming increasingly key to low-term business success.

On this course, you’ll understand how predictive analytics can be used to get useful information out of your data. You’ll identify how techniques like machine learning and data mining can help you become a data-centred project manager who can solve business problems, and drive revenue.

Learn how predictive analytics helps business

Predictive analytics encompasses a variety of statistical techniques in big data analysis and machine learning.

Alongside data science experts at Sungkyunkwan University (SKKU), you’ll get foundational training in the concepts and principles that underlie data science and statistical modelling techniques.

See how data science can boost business performance

The course will take you through a series of real-world business problems, solving each by using key predictive analytics methods.

These include statistical methodologies and algorithms such as artificial neural networks, clustering, text mining, decision trees, and natural language processing.

Explore the relationship between predictive analysis and machine learning

You’ll discover the essentials of machine learning, which can be a vital tool in analysing and making use of data.

Discover the difference between supervised machine learning – where you can collect data based on previous experience – and unsupervised machine learning – where you can find new data patterns.

Gain practical big data skills

Along the way, you’ll learn how to use predictive tools to extract knowledge from data, connect actual business problems with data science solutions, and lead a data science-orientated team.

This course would benefit an aspiring manager who wants to align their understanding of business and technical solutions and to lead comprehensive business solutions including data science teams.

Learners will require access to Microsoft Excel (or Excel Online) to open and edit data sheet files.

• Data Analytic Thinking
• Introduction
• Independent variable vs. dependent variable
• Quiz
• What is predictive analytics?
• Data analytic problems and solutions
• Models and prediction
• Innovation and quality.
• Quiz
• Supervised learning
• Classification tree & Employee retention
• Determinants of housing price
• What is deep learning
• Quiz
• Unsupervised learning
• Nearest neighbour & Breast cancer study
• Distance measures
• Clustering & Titanic survivors
• Quiz