This Introduction to Data Analytics course is designed to provide participants with a strong foundational understanding of data analytics and its practical, real-world applications. Through engaging lessons and hands-on projects, students will develop essential skills in collecting, analyzing, and visualizing data to make informed decisions. By the end of the course, participants will be prepared with the knowledge needed to pursue an industry-recognized certification in data analytics.

No prior experience is required—just curiosity and a Gmail account to save your work!

Start Date: Tuesday, November 4th

Session Times: 6:00 PM – 8:00 PM

Location: St. Johns River State College, Orange Park Campus

Format: 6 in-person classes

Instructor: Dr. Daniel Ray

Dr. Ray, a St. Johns River State College faculty member, brings 25 years of IT experience and a Master’s Degree in Data Analytics to the classroom. He is an accomplished educator with a passion for helping students succeed, ensuring high-quality, tailored instruction.

This course is ideal for:

Career changers exploring opportunities in data analytics or tech.

Small business owners looking to leverage data for smarter decisions.

Students and recent graduates seeking to boost their resumes.

Nonprofit professionals analyzing program impact and fundraising strategies.

Curious learners interested in how data drives decision-making across industries.

Participants will:

Gain in-demand skills in data analysis, visualization, and decision-making.

Learn to use tools like spreadsheets, SQL, and data visualization software.

Be prepared to pursue an industry-recognized certification in data analytics.

Explore a potential career path in a supportive, risk-free learning environment.

Build connections with peers interested in data analytics.

Solve real-world problems using data insights for personal and professional growth.

Graduates will be well-positioned to:

Pursue certifications such as the Google Data Analytics Certificate or Microsoft Power BI Certification.

Enroll in intermediate courses to deepen skills in Python, SQL, or advanced visualization tools.

Apply new skills in their workplace, community, or personal projects.

Join professional networks and connect with the broader data analytics community.

Consider further education through degree programs or specialized training.