What is Data Science? Course Syllabus

Overview: This beginner-friendly course provides a clear and concise introduction to data science, designed to equip learners with foundational knowledge of the field. Over approximately 7.5 hours, you'll explore core concepts, tools, workflows, and ethical considerations that define modern data science. The course features interactive, no-installation-needed exercises to help you grasp real-world applications and prepare for further specialization. Lifetime access ensures you can learn at your own pace.

Module 1: Introduction to Data Science

Estimated time: 1.5 hours

• What is data science?
• Examples of data-driven projects
• Impact of data science across industries
• Reflect on use cases in your organization

Module 2: Data Science Tools & Ecosystem

Estimated time: 2 hours

• Overview of Python for data science
• Introduction to Jupyter notebooks
• Using Git and GitHub for collaboration
• Basics of SQL databases and command-line workflows

Module 3: The Data Science Lifecycle

Estimated time: 2.5 hours

• Defining the problem and formulating questions
• Data acquisition and cleaning processes
• Exploratory data analysis techniques
• Modeling basics and deployment concepts

Module 4: Roles, Teams & Ethical Considerations

Estimated time: 1.5 hours

• Data scientist vs. data engineer vs. ML engineer
• Teamwork and communication in data projects
• Ethics, bias, and privacy in data science
• Conduct an ethical risk assessment

Prerequisites

• Familiarity with basic computer operations
• No prior programming experience required
• Interest in data and problem-solving

What You'll Be Able to Do After

• Define data science and its role in solving real-world problems
• Describe the end-to-end data science lifecycle
• Identify key tools like Python, Jupyter, Git, and SQL
• Recognize roles and collaboration dynamics on data teams
• Assess ethical implications in data-driven decision-making