Why is data science so important for organizations? It can allow us to draw meaningful conclusions from all the data around us. We’re excited to announce the launch of a new type of course for managers and executives to make sense of how data science can best position their organizations for success. (And don’t worry, no coding required!)
Who This Course is For
Have you ever wondered what skills you need on your data team or how to best structure your data team for success? Do you want to understand the different internal and external data sources your company can use and how best to store your data? Perhaps you’d like to discover ways to analyze and visualize your data through dashboards and A/B tests. This course covers all of that and more. We’ll also discuss exciting topics in machine learning, including clustering, time series prediction, natural language processing (NLP), deep learning, and explainable AI.
What You’ll Learn
This course provides a concise overview of why data science matters, and can help you to better organize and build your data science team and understand the data science workflow.
We’ll dive into data collection and storage, including different data sources and risks, applicable storage types like servers and the cloud, and how to query data to get what you need.
Exploration and Visualization
We’ll discuss ways to explore and visualize data through dashboards, including how to choose the right elements to include and which type to use. We’ll also cover ad hoc data requests and A/B tests, a powerful analytics tool that de-risks decision-making.
Experimentation and Prediction
We’ll discuss how to make better predictions with machine learning, including an exploration of supervised and unsupervised machine learning and clustering. We'll also discuss special topics in machine learning, including time series prediction, natural language processing, deep learning, and explainable AI.
The course includes real-world applications of data science to deepen your understanding through practical exercises. Along the way, we’ll answer some of your burning questions about data science:
- Should I hire a data engineer, data analyst, or machine learning scientist?
- When do I need to use external data sources like APIs?
- When do I need a dashboard versus an ad hoc report, and what are the use cases?
- What can machine learning actually do for my company?
- What’s the difference between deep learning and explainable AI?
How You’ll Learn
You may be wondering how we will help you master the basics of data science without using code. We’ll introduce you to the various topics and follow up with some interactive conceptual exercises in a fun learn-by-doing approach.
Here’s an example of a conceptual exercise:
Ready to take the course? Start Data Science for Business for free here.
Need a handy overview of data science? Click the image below for an easy reference on building your data science team and the common steps in the data science workflow with our brand-new cheat sheet for business leaders.
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