Level: Beginner to Intermediate
Prerequisite: None
Data science has been called “the sexiest job of the 21st century” and with good reason—the size and breadth of our data is growing exponentially, and businesses are leveraging advances in machine learning and AI capabilities to make sense of it all for competitive advantage. This course defines data science, describes how it is similar to and different from related analytics disciplines, and covers key concepts every business stakeholder and data scientist needs to know. You will learn how a data science program is organized, the roles of key participants, and the major stages of data science projects.
In this overview, a project-oriented framework is used to provide insights into each phase of the data science process. Every data science project must begin with establishing business and analytics objectives, then collect and integrate data, prepare it for analysis, develop analytic models, and deploy the results. For each stage, key principles will be described, and real-world examples will illustrate the concepts. These key principles apply whether the end goal of the project is to make a single decision, develop dashboards and visualizations, deploy new reports, or automate key business activities.
You Will Learn
- How data science is applied to business challenges to produce useful results
- How data science programs are organized
- Key roles, including business stakeholders, subject matter experts, data engineers, and analytic modelers
- The major stages of a data science project, including establishment of goals, data preparation, analytic modeling, and deployment
- The relationship of data science to statistical analysis, machine learning, and AI
- Tools and technologies used in data science
Geared To
This course is geared to technical and non-technical professionals getting started with data science, including:
- Business analysts
- Business stakeholders
- Data scientists
- Analytics practitioners
- Data engineers
- Analytics project leads
- BI and data management professionals
Experienced data scientists will find this course to be a review, but they will benefit from the class if they have not been formally exposed to key principles and practices.