Introduction to Data Science

The Introduction to Data Science course is designed for learners who are curious about how data shapes decisions in business, healthcare, government, and everyday life. Whether you're completely new to the field or looking to sharpen your analytical edge, this course provides a strong foundation in the essential tools and methods used by today’s data professionals.

Students will gain hands-on experience in core areas such as:

• Data exploration and cleaning

• Descriptive and inferential statistics

• Data visualization using Python, Matplotlib, Seaborn, and Tableau

• Structured Query Language (SQL) for data querying

• Introductory machine learning models including logistic regression, decision trees, and clustering algorithms

You’ll work with real-world datasets and apply your skills to solve practical problems. Along the way, you’ll build confidence in using programming languages like Python and tools like Pandas, Jupyter Notebooks, and Tableau to uncover insights and communicate findings clearly.

By the end of the course, you’ll be able to:

• Understand and apply basic statistical and machine learning concepts

• Clean, organize, and analyze data with Python and SQL

• Create compelling visualizations and dashboards

• Approach real-world problems using a data-driven mindset

• Build and present a final project that demonstrates your skills

This course is ideal for:

• Beginners looking to break into data science

• Professionals from any field interested in making more data-informed decisions

• Students exploring career paths in analytics, public health, informatics, or business intelligence

No prior coding experience is required. We start with the basics and guide you through each concept with practical, project-based learning.

If you’ve ever wondered how data informs the world around us—or how you can be part of that conversation—this is where your journey begins.