Address Business Issues with Data Science Course Syllabus

This course provides a practical framework for applying data science to real-world business challenges. Over approximately 6.5 hours, learners will progress through five core modules and a final project, each designed to build skills in identifying business problems, analyzing data, applying data science techniques, and communicating insights. The self-paced structure includes hands-on activities and real-world case studies, culminating in a final business case project. Flexible deadlines allow learners to complete the course at their own pace while gaining actionable skills in data-driven decision-making.

Module 1: Understanding Business Problems

Estimated time: 1.5 hours

• Identify and define business challenges
• Translate business questions into analytical problems
• Explore real-world examples of data-driven solutions
• Recognize the importance of problem framing

Module 2: Data Analysis & Insight Generation

Estimated time: 1.5 hours

• Explore techniques for analyzing business data
• Identify patterns, trends, and relationships in data
• Use analytical tools to support decision-making
• Interpret results in business context

Module 3: Applying Data Science Techniques

Estimated time: 1.5 hours

• Select appropriate analytical models for business scenarios
• Use predictive analytics to forecast outcomes
• Evaluate model performance and results
• Solve real-world business problems using data science methods

Module 4: Communicating Data Insights

Estimated time: 1 hour

• Communicate insights effectively to stakeholders
• Use data visualization techniques to present findings
• Translate technical results into business language

Module 5: Final Business Case Project

Estimated time: 1 hour

• Define a real or simulated business problem
• Analyze data and generate actionable insights
• Present data-driven recommendations

Module 6: Final Project Submission and Review

Estimated time: 0.5 hours

• Submit completed business case analysis
• Review key learning outcomes
• Reflect on application of data-driven decision-making

Prerequisites

• Familiarity with basic business concepts
• Basic understanding of data analysis
• No coding experience required

What You'll Be Able to Do After

• Assess whether a business issue is suitable for a data science solution
• Frame business problems as data-driven questions
• Apply core data science techniques to generate business insights
• Effectively communicate analytical findings to non-technical stakeholders
• Demonstrate the value of data-driven decision-making in real-world contexts