Data Analytics Course with Generative AI

Overview

This comprehensive Generative AI in Data Analytics course equips you with the skills to optimize data workflows, automate analysis, and generate actionable insights using AI. Begin by mastering the four types of analytics, descriptive, diagnostic, predictive, and prescriptive, and explore how GenAI enhances each stage. Learn to automate ETL processes, generate synthetic data with tools like ChatGPT-4 and MOSTLY AI, and perform EDA using Julius AI and Tableau Pulse. Progress to building predictive models, forecasting trends, and conducting risk analysis through real-world simulations. Understand performance metrics, address integration challenges, and apply GenAI in practical business scenarios. You should have a basic understanding of data analysis, statistics, and familiarity with tools like Excel, SQL, or BI platforms. By the end of this course, you will be able to: - Automate Data: Streamline ETL and generate synthetic data using GenAI - Analyze Insights: Perform EDA and visualize data with AI-powered tools - Predict Outcomes: Build models and simulate risk for better decisions - Apply GenAI: Use GenAI across real-world analytics with measurable impact Ideal for analysts, data professionals, and business leaders advancing data strategy with AI.

Syllabus

Exploration to Visualization

Explore how Generative AI is transforming the data analytics process from integration to visualization. Learn the types of analytics such as descriptive, diagnostic, predictive, and prescriptive, and GenAI's role in each stage. Automate ETL processes, enhance data quality, and generate synthetic datasets using tools like ChatGPT-4 and MOSTLY AI. Perform EDA and create insights with tools like Julius AI and Tableau Pulse.

ETL Optimization, Generative Modeling, and Future Trends

Advance your data analytics skills with GenAI-powered visualization, modeling, and forecasting techniques. Learn to optimize ETL, build predictive models, and assess risk using tools like Julius AI. Explore GenAI’s role in data modeling and scenario simulation. Understand integration challenges, performance metrics, and real-world applications through case studies and practical demos.