1: Introduction to Qlik for Data Scientists

1.1 Overview of Qlik’s Capabilities in Business Intelligence
1.2 Role of Qlik in Data Science Projects
1.3 Course Objectives and Expected Outcomes

2: Integrating Data Science Models with Qlik

2.1 Connecting Qlik to Data Science Environments (e.g., Python, R)
2.2 Importing and Exporting Data Science Model Results
2.3 Automating Data Updates and Model Refreshes

3: Data Preparation and Preprocessing in Qlik

3.1 Data Import and Transformation Techniques
3.2 Handling Large Data Sets for Data Science Applications
3.3 Creating and Managing Data Models in Qlik(Ref: Qlik Sense SaaS Data Architect Endorsement)

4: Building Predictive and Analytical Models in Qlik

4.1 Overview of Predictive Analytics in Qlik
4.2 Creating and Visualizing Regression and Classification Models
4.3 Case Study: Developing a Predictive Model Dashboard

5: Advanced Visualization Techniques for Data Science

5.1 Designing Effective Visualizations for Complex Data Science Models
5.2 Using Qlik Extensions and Custom Visuals for Advanced Analysis
5.3 Case Study: Visualizing Clustering and Segmentation Results

6: Interactive Dashboards for Data-Driven Decision Making

6.1 Designing Interactive Dashboards for Data Science Insights
6.2 Incorporating Filters, Variables, and Actions
6.3 Best Practices for Dashboard Usability and Interactivity

7: Communicating Insights and Results

7.1 Techniques for Presenting Data Science Findings to Stakeholders
7.2 Creating Compelling Data Stories with Qlik
7.3 Case Study: Effective Communication of Data Science Insights

8: Real-World Applications and Case Studies

8.1 Case Study 1: Sales Forecasting and Trend Analysis
8.2 Case Study 2: Risk Management and Fraud Detection
8.3 Case Study 3: Customer Behavior Analysis

9: Troubleshooting and Optimization

9.1 Common Challenges and Solutions in Data Science Projects with Qlik
9.2 Optimizing Dashboard Performance and Load Times
9.3 Best Practices for Debugging and Troubleshooting

10: Final Project and Course Summary

10.1 Final Project: Creating a Comprehensive Data Science Dashboard in Qlik
10.2 Recap of Key Concepts and Techniques
10.3 Q&A Session and Next Steps for Continued Learning

To conclude; This course equips data scientists with essential skills to leverage Qlik for effective data analysis and visualization. Participants will gain hands-on experience, enabling them to communicate insights and drive data-driven decision-making in their organizations.

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