AI
Leveraging AI for Data Analysis and Visualization
Overview
This course examines how data analysts can utilize AI tools such as LLMs (Large Language Models) and other specialized tools to accelerate, automate and enhance their analyses, spreadsheets, programs, visualizations and presentations.
Duration
2 days
Who Should Take This Course
Prerequisites
- Familiarity with data analysis fundamentals (e.g., SQL, Python, spreadsheets).
- Basic understanding of visualization tools like Power BI, Tableau, or matplotlib.
Why You Should Take This Course
In the duration of this course, students will gain:
- Mastery of AI tools for accelerating data analysis and visualization workflows.
- Proficiency in Python, SQL, and AI-assisted spreadsheet tools for data tasks.
- Confidence in creating advanced visualizations and data narratives with AI.
- Awareness of ethical considerations and biases in AI-driven analyses.
Course Outline
- Day 1: Foundations of AI-Driven Data Analysis
- Morning Session (4 hours)
- Introduction to AI in Data Analysis (0.5 hour)
- Role of AI in modern data workflows.
- Overview of key tools: LLMs, automated analysis platforms, and visualization assistants.
- Benefits: Speed, accuracy, and insights generation.
- Using LLMs for Data Queries and Insights (1.5 hours)
- Exploring how LLMs (e.g., ChatGPT) can assist with SQL queries, exploratory data analysis (EDA), and scripting.
- Hands-on:
- Generating SQL queries for data filtering and aggregation.
- Using Python (pandas) for EDA with LLM guidance.
- Best practices for prompt engineering to get accurate results.
- Data Cleaning and Transformation with AI (1 hour)
- AI-powered tools for data cleaning (e.g., OpenRefine, Python libraries).
- Automating data transformation tasks with LLMs.
- Hands-on: Cleaning a messy dataset using Python and AI suggestions.
- Accelerating Spreadsheet Tasks with AI (1 hour)
- Advanced spreadsheet capabilities powered by AI (e.g., Excel Copilot, Google Sheets AI features).
- Automating formulas, conditional logic, and predictive modeling in spreadsheets.
- Hands-on: Solving complex spreadsheet problems using AI tools.
- Afternoon Session (4 hours)
- AI-Assisted Statistical Analysis (2 hours)
- Performing statistical tests and generating summaries with AI.
- Hands-on:
- Using Python libraries (e.g., statsmodels, scipy) with AI support.
- Automating hypothesis testing and regression analysis.
- Exploring Data Patterns and Trends with AI (2 hours)
- Using AI to identify correlations, anomalies, and clusters in data.
- Tools and techniques: Python (scikit-learn, matplotlib), LLM-guided analysis.
- Hands-on: Applying clustering algorithms with AI-generated Python scripts.
- AI-Assisted Statistical Analysis (2 hours)
- Introduction to AI in Data Analysis (0.5 hour)
- Morning Session (4 hours)
- Day 2: AI-Powered Data Visualization and Storytelling
- Morning Session (4 hours)
- Automating Data Visualization with AI (2 hours)
- Creating visualizations using AI tools like Tableau GPT, Power BI Copilot, or matplotlib with LLMs.
- Hands-on:
- Automating chart generation for datasets in Python.
- AI-driven customization of dashboards in Power BI.
- Advanced Visualization Techniques (2 hours)
- AI-assisted recommendations for effective data visualization (chart types, color schemes, annotations).
- Generating multi-dimensional and interactive visualizations.
- Hands-on: Building advanced dashboards with AI support in Power BI or Tableau.
- Afternoon Session (4 hours)
- Storytelling with Data Using AI (2.5 hours)
- Transforming insights into narratives with AI assistance (e.g., natural language summaries of data).
- AI tools for creating compelling presentations (e.g., PowerPoint Copilot, Canva AI).
- Hands-on:
- Generating a report summary using LLMs.
- Integrating data visualizations into presentations.
- Responsible AI Use in Data Analysis (1 hour)
- Understanding biases in data and AI-generated insights.
- Ensuring transparency and accountability in analysis workflows.
- Case study: Identifying and correcting biases in AI-driven analyses.
- Storytelling with Data Using AI (2.5 hours)
- Automating Data Visualization with AI (2 hours)
- Morning Session (4 hours)
FAQs
Is there a discount available for current students?
UMBC students and alumni, as well as students who have previously taken a public training course with UMBC Training Centers are eligible for a 10% discount, capped at $250. Please provide a copy of your UMBC student ID or an unofficial transcript or the name of the UMBC Training Centers course you have completed. Asynchronous courses are excluded from this offer.
What is the cancellation and refund policy?
Student will receive a refund of paid registration fees only if UMBC Training Centers receives a notice of cancellation at least 10 business days prior to the class start date for classes or the exam date for exams.