Data Science for Business - Repeatable and Objective Data Science Process

Overview

Unlock the potential of data science in your business by understanding the Team Data Science Process (TDSP). This comprehensive guide focuses on incorporating predictive analytics and AI into business processes through agile methodologies and practical strategies.

Whether you're in the field of artificial intelligence courses or attending conference talks, this content provides valuable insights to streamline your data strategies.

Syllabus

• Introduction to Data Science for Business
Overview of Data Science and AI in Business
Importance of a Repeatable and Objective Process
• Understanding the Team Data Science Process (TDSP)
Key Principles of TDSP
The TDSP Life Cycle
• Business Understanding and Planning
Defining Business Problems
Developing a Project Plan and Metrics
• Data Acquisition and Understanding
Techniques for Data Collection
Data Cleaning and Preprocessing
• Modeling and Implementation
Selecting Appropriate Modeling Techniques
Building and Testing Predictive Models
Implementing Models in Business Scenarios
• Evaluation and Deployment
Model Evaluation Metrics
Strategies for Model Deployment and Monitoring
• Agile Methodology in Data Science
Applying Agile Principles to TDSP
Iterative Development and Continuous Improvement
• Practical Implementation Strategies
Case Studies of Successful Implementations
Overcoming Common Business Challenges
• Ethics and Governance in Data Science
Ensuring Data Privacy and Compliance
Establishing Fairness and Bias Mitigation
• Review and Future Trends
Recap of the TDSP
Emerging Trends in Data Science for Business

---

Subjects

Conference Talks