This intensive course prepares students for careers in data science by covering SQL database management, Python data analysis using Pandas, and data visualization with Power BI. Students master techniques for manipulating databases, conducting advanced data analysis, and creating insightful visualizations. Emphasis is placed on evaluating machine learning proficiency, including regression, classification, model interpretation, and algorithm application such as linear regression, logistic regression, decision trees, random forests, and support vector machines.

Through real-world data science challenges, students hone their problem-solving skills, culminating in the creation of a polished resume showcasing their readiness for the field. By the course’s end, students emerge as skilled data practitioners with the expertise and portfolio necessary for success in the data science industry.

• Present, reflect, and iterate on a portfolio of data
  science challenges and solutions which demonstrate
  career readiness.
• Create a resume that demonstrates career readiness.
• Exhibit entry-level readiness by completing tasks
  related to SQL database management, Python data analysis using Pandas, data visualization with Power BI, database manipulation, data analysis, and the creation of insightful visualizations.
• Exhibit entry-level career readiness by demonstrating machine learning proficiency, emphasizing regression, classification, interpretation of model parameters, evaluation metrics, and the application of algorithms including linear regression, logistic regression, decision trees, random forests, and support vector machines.