1. Enable participants to efficiently gather data that addresses specific business challenges.
2. Teach how to recognize and reduce biases in data samples to enhance analysis accuracy.
3. Provide learners with the skills to create statistical summaries and visualizations to better understand the impact of variables on outcomes.
4. Empower participants to assess decisions through key performance indicators and understand their implications for stakeholders.
5. Enable participants to formulate and test hypotheses effectively.
6. Instruct participants on developing and refining regression models for more accurate data analysis.
7. Guide participants on making accurate predictions or estimates using their models, applying these techniques to practical business scenarios.
8. Teach participants to identify and utilize data relationships to reduce uncertainty in business decisions.

Module 1: Understanding and visualizing data

Section 1: Gather and Qualify data

Section 2: Visualization and Analysis

Section 3: Bring the data into the decision

Module project

Module 2: Implementing scientific decision making

Section 1: Define a Hypothesis

Section 2: Test the Hypothesis

Section 3: Testing and conclusion

Module project  

Module 3: Using predictive data analysis

Section 1: Discovering Relationships

Section 2: Quantifying Impact

Section 3: Assessing and Validating Your Model

Section 4: Applying the Predictive Analytics Framework

1. Module project  

1. Analysts: Professionals who interpret and transform data into actionable insights.
2. Functional Managers: Leaders who oversee specific business areas and rely on data to optimize performance.
3. Executives: Senior decision-makers who use data to guide strategic directions and operations.
4. Consultants: Advisors who analyze data to provide informed recommendations to their clients.
5. Any Professional That Uses Data to Make Business Decisions: This includes a wide range of roles across various industries who need to leverage data for informed decision-making.