AI for Data Analytics & Reporting

Unlock insights with AI for data analytics and reporting—automate analysis, visualize trends, and make data-driven decisions with greater speed and accuracy.
Duration: 1 Day
Hours: 3 Hours
Training Level: All Levels
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Contact Support for Group Offers
Batch One
Monday, March 09, 2026
11:00 AM - 03:00 PM (Eastern Time)
Batch Two
Tuesday, April 21, 2026
11:00 AM - 03:00 PM (Eastern Time)
Batch Three
Wednesday, May 20, 2026
11:00 AM - 03:00 PM (Eastern Time)
Live Session
Single Attendee
$149.00 $249.00
Live Session
Recorded
Single Attendee
$199.00 $332.00
6 month Access for Recorded
Live+Recorded
Single Attendee
$249.00 $416.00
6 month Access for Recorded

About the Course:

Step into the world of Artificial Intelligence for Data Analytics and Reporting with this beginner-friendly course, crafted for professionals eager to unlock insights, analyze data, and create impactful reports quickly with AI tools, all without coding.

Discover how AI can streamline data analysis, simplify data cleaning, enhance visualizations, spark new insights, and automate reporting. Dive into hands-on use cases like data exploration, uncovering business insights, supporting dashboards, and making smarter decisions with AI-powered tools.

Blending clear concepts, real-world scenarios, and interactive demonstrations, this course welcomes business users, analysts, and non-technical professionals to harness the power of AI confidently. 

Course Objectives:

In just three hours, you will unlock the ability to:

  • Discover how AI can supercharge your data analytics workflows.
  • Harness AI tools to explore data and uncover valuable insights.
  • Transform raw datasets into clear summaries and actionable business insights.
  • Streamline data cleaning and preprocessing with the power of AI.
  • Bring your data to life with AI-assisted charts and visualizations.
  • Effortlessly build automated reports with AI tools.
  • Ask better analytical questions using AI.
  • Improve productivity in data-driven decision making.
  • Understand limitations and responsible use of AI in analytics.

Who is the Target Audience?

This course is ideal for:

  • Driven professionals from all backgrounds are ready to elevate their expertise.
  • Trailblazing leaders and managers who thrive on momentum.
  • Ambitious students and fearless professionals seeking new directions.
  • Creative educators and trainers who spark inspiration.
  • Entrepreneurs and founders.
  • Content creators and marketers are eager to amplify their reach.
  • Anyone ready to harness AI for everyday success

Basic Knowledge:

Participants should have:

  • A comfortable grasp of digital basics.
  • Experience navigating web apps and everyday software.
  • A spark of curiosity for exploring AI tools.
  • No need for coding, math, or prior AI know-how.

Curriculum
Total Duration: 3 Hours
Introduction to AI in Data Analytics

  • What is AI-driven analytics
  • Traditional analytics vs AI-assisted analytics
  • Why AI is transforming data-driven work

Role of AI in Modern Data Workflows

  • Data collection to decision making
  • AI-assisted analysis lifecycle
  • Human + AI collaboration in analytics

Understanding Data for Analysis

  • Structured vs unstructured data
  • Common data formats (Excel, CSV, databases)
  • Data quality and reliability

AI for Data Exploration

  • Understanding datasets quickly
  • Identifying trends and patterns
  • Generating summary statistics using AI

AI for Data Cleaning and Preparation

  • Handling missing values
  • Detecting anomalies and inconsistencies
  • Data transformation assistance

Asking Analytical Questions Using AI

  • Converting business problems into data questions
  • Natural language queries for analysis
  • Improving analytical thinking

AI for Data Visualization

  • Generating charts using AI tools
  • Choosing the right visual representation
  • Explaining insights using visual data

Insight Generation and Interpretation

  • Extracting meaningful business insights
  • Pattern recognition and interpretation
  • Data storytelling fundamentals

Automated Reporting Using AI

  • Report generation from data
  • Executive summaries
  • Automated dashboards and insights

AI for Business Decision Support

  • Predictive insights (conceptual understanding)
  • Scenario analysis
  • Risk and opportunity identification

AI in Spreadsheet Tools

  • Using AI in Excel and Google Sheets
  • Formula assistance
  • Data analysis features powered by AI

AI in BI Tools and Dashboards

  • AI features in Power BI, Tableau (conceptual)
  • Natural language analytics
  • Automated visual insights

Prompting AI for Data Analysis

  • Writing effective instructions for data tasks
  • Structured analytical prompts
  • Improving data outputs using better prompts

Evaluating AI-Generated Insights

  • Validating data results
  • Checking accuracy and bias
  • Avoiding misleading interpretations

Common Mistakes in AI-Assisted Analytics

  • Over-reliance on AI
  • Misinterpretation of outputs
  • Poor data quality issues

Responsible AI in Data Analytics

  • Privacy and sensitive data handling
  • Ethical data usage
  • Transparency in reporting

AI Limitations in Analytics

  • Where human judgment is required
  • Understanding model limitations
  • Risk awareness

Improving Productivity with AI Analytics

  • Reducing manual work
  • Faster reporting cycles
  • Automation opportunities

Future of AI in Data Analytics

  • Augmented analytics trends
  • AI-driven decision intelligence
  • Changing roles of analysts

Building a Data + AI Mindset

  • Human + AI collaboration in analytics
  • Continuous learning approach
  • Future outlook and closing thoughts