Overview
Develop your decision making and management skills informed by data analytics
Data analytics expertise empowers managers to transform their business frameworks and enables them to work effectively with data science teams.
In this six-week course from the University of Adelaide, you’ll develop your knowledge of how data analysts operate in business environments. You’ll learn how to explain data analysis processes, identify trends, and develop data-informed business solutions.
Explore the fundamentals of data science analysis
Many managers lack the confidence to interpret data, depriving them of useful insights and preventing them from developing a competitive edge.
In this course, you’ll be introduced to the basics of data analysis, equipping you with the skills to work alongside your data science team to derive meaning from data and capitalise on the data analytical skills of your workforce.
Deliver business transformation by understanding relationships in data
Using engaging case studies, you’ll learn to apply cutting-edge data processing techniques to solve common business problems and discover new patterns in data.
You’ll explore key terminology, from the k-means clustering algorithm to linear regressions, allowing you to interpret data and predict upcoming business trends.
Discover the power of market basket analysis and network analysis
You’ll learn to analyse transaction data, using the concept of association rules analysis, before moving on to learning the basics of network metrics and analysis.
By the end of this course, you’ll have enhanced your understanding of data analysis and the insights it can deliver within your business environment. Equipped with an understanding of processes used within business data analytics, you’ll be able to work alongside your data analytics team to deliver better strategies and make data-driven decisions.
This course is designed for managers who want to improve their knowledge of data analytics. It will help both managers and those in leadership work effectively with data science teams and data analysts to improve business processes, identify trends and interpret data.
This course is suitable for managers who already work with data analysts, as well as those looking to expand their business team to include data analysts.
Whilst the primary audience is those in management roles, this course may also benefit those who collaborate with data analysts who wish to further their understanding of data analytic processes, key terminology and practices.
No prior knowledge or experience of data analytics is required, though you do need an understanding of basic maths terminology such as mean, logarithm, and Pythagoras.
Syllabus
- Introduction to data analytics
- Getting Started
- Introduction to Week 1
- What is data analytics?
- What are the roles and responsibilities in a data analytics team?
- What are the different types of data analytics techniques?
- What is the data analytics process?
- Assessment
- Bringing it all together
- Discovering new patterns in data to transform your business
- Introduction to Week 2
- Strategies in using new data patterns to transform your business
- What is a cluster? Similarity and distance measures
- The k-means clustering algorithm
- Optimising your clustering analysis with the elbow method
- Limitations of k-means clustering analyses
- Assessment
- Bringing it all together
- Making predictions using your data to solve business problems
- Introduction to Week 3
- Simple linear and non-linear regressions
- Complex linear and non-linear regressions
- Non-linear regression with neural networks
- Overfitting
- Assessment
- Bringing it all together
- Predicting the category of data points to solve business problems
- Introduction to Week 4
- K-nearest neighbours
- Decision trees and random forests
- Assessment
- Bringing it all together
- The power of shopping basket analysis
- Introduction to Week 5
- Association Rules
- The Apriori algorithm
- Assessment
- Bringing it all together
- What are your influencers?
- Introduction to Week 6
- Basics of networks
- Network metrics
- Assessment
- Bringing it all together
- What’s next?