Turn raw data into actionable insights with this hands-on, career-focused course in modern data management, analysis, and visualization. Designed for students seeking to excel in today's data-driven economy, this course covers the complete data lifecycle—from collection and wrangling to analysis, visualization, and ethical application.

You'll learn how to:

• Query and manage databases – write SQL queries (SELECT, JOIN, GROUP BY, subqueries) and work with relational and NoSQL systems.
• Wrangle and clean data – transform messy datasets using Python (Pandas, NumPy) and tools like OpenRefine.
• Apply statistical methods – analyze trends with regression, clustering, and hypothesis testing to uncover patterns and insights.
• Visualize data effectively – create compelling dashboards and reports in Tableau, Power BI, and Python (Matplotlib/Seaborn).
• Automate workflows – build ETL pipelines using Apache Airflow, Talend, or similar tools.
• Optimize databases – apply indexing, normalization, and performance tuning strategies.
• Explore machine learning basics – apply supervised and unsupervised methods for predictive analytics.
• Protect data integrity – implement security practices, encryption, and compliance standards such as GDPR.

Course format & features

• Interactive labs with real datasets and industry-standard tools.
• Case studies applying analytics to business, science, and social impact problems.
• Certification-aligned assessments mapped to leading data analytics and BI exams.
• Capstone project: design and present a full data analysis pipeline with professional reporting.

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

• Collect, clean, and transform raw data into structured, usable formats.
• Derive meaningful insights through statistical and computational methods.
• Communicate results effectively through visualizations and dashboards.
• Automate data workflows for scalability and efficiency.
• Demonstrate readiness for roles such as Data Analyst, Business Intelligence Specialist, or Data Engineer.

Expectations: Complete weekly projects, contribute to peer review sessions, and follow data ethics guidelines to ensure responsible use of data.

This course equips you with the technical expertise and analytical mindset to drive decision-making in business, research, and technology careers.