AI for Analysts

Overview

Discover how AI enhances the analyst role, learn techniques to leverage AI in your work, and optimize collaboration with data science teams for better decision-making and career growth.

Syllabus

• Introduction to AI in Analytics
Overview of AI technologies
The role of AI in data analysis
Key benefits and challenges of integrating AI into analytics
• Understanding AI Tools for Analysts
Common AI frameworks and libraries
Overview of AI software and platforms
Hands-on session: Exploring AI tools for data analysis
• Data Preparation and Management
Data collection and cleaning methods
Handling large datasets
Ensuring data quality and integrity
• Fundamental AI Techniques for Analysts
Introduction to machine learning models: supervised and unsupervised learning
Basics of natural language processing
Overview of computer vision in analytics
• AI-Driven Data Analysis
Using AI for predictive analytics
Anomaly detection techniques
Automating data exploration with AI
• Enhancing Decision-Making with AI
AI-driven insights for strategic decision-making
Risk assessment using AI
Scenario analysis and forecasting
• Collaborating with Data Science Teams
Understanding the data scientist role
Effective communication strategies between analysts and data scientists
Case studies: successful collaboration examples
• AI Ethics and Responsible Use
Understanding AI biases and fairness
Privacy considerations in AI applications
Ensuring ethical use of AI in analytics
• Career Growth and Future Trends
Building AI skills for career advancement
Emerging trends in AI that impact analytics
Continuous learning resources and communities
• Capstone Project
Real-world problem-solving using AI tools
Collaboration with peers to deliver actionable insights
Presentation and feedback session on findings

---

Subjects

Conference Talks