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AI-INTEGRATED DATA ANALYTICS WITH GENAI CRASH COURSE Specialization.

2 Month
1500+ Enrolled
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Accelerate your career with the most comprehensive AI-INTEGRATED DATA ANALYTICS WITH GENAI CRASH COURSE course designed by industry veterans. Learn by doing with real-world projects.

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DATA ANALYTICS, COVERING ADVANCED EXCEL, SQL, MICROSOFT POWER BI, DATA VISUALIZATION, AND GENERATIVE AI. THE PROGRAM EMPHASIZES HANDS-ON LEARNING THROUGH REAL-WORLD DATASETS, INTERACTIVE DASHBOARDS, AND AI-ASSISTED ANALYTICS, ENABLING LEARNERS TO MAKE DAT
₹25,000.00 / Lifetime Access
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What is AI-INTEGRATED DATA ANALYTICS WITH GENAI CRASH COURSE?

Master Data Analytics with Advanced Excel, SQL, Power BI, Data Visualization, and Generative AI. Gain practical experience through real-world datasets, interactive dashboards, and AI-powered analytics to become job-ready.

This program is designed to take you from a complete beginner to a job-ready professional. We focus on practical skills, industry best practices, and the latest tools used by top tech companies globally.

Course Syllabus

Module 1: Data Analytics Foundations

  • Core Concepts: Learn the core definitions, different types of analytics, and the standard analytics lifecycle.

  • Business Applications: Understand data-driven decision-making and fundamental Business Intelligence (BI) concepts.

  • Design Practices: Master fundamental data visualization principles to properly structure upcoming dashboards.

Module 2: Advanced Microsoft Excel for Data Analytics

  • Data Manipulation: Work with advanced Excel functions, data cleaning techniques, and data validation rules.

  • Summarization & ETL: Master Pivot Tables, Pivot Charts, and extract-transform-load (ETL) workflows using Power Query.

  • Reporting Architecture: Build interactive dashboards, automate business reporting, and design specialized MIS & KPI dashboards.

Module 3: Statistics for Data Analytics

  • Descriptive & Probability: Build a mathematical baseline with descriptive statistics and fundamental probability concepts.

  • Relationship Modeling: Analyze data patterns utilizing correlation analysis, regression analysis, and forecasting techniques.

  • Strategic Logic: Apply advanced business decision models to back business operations with mathematical proof.

Module 4: SQL for Data Analytics

  • Database Programming: Learn database fundamentals and write proper SQL programming syntax.

  • Query Engineering: Handle complex relational operations via Joins, Subqueries, and Common Table Expressions (CTEs).

  • Advanced Engine Logic: Leverage window functions, create views, and build reusable stored procedures for business analytics.

Module 5: Python for Data Analytics

  • Programming Foundations: Learn Python fundamentals and master computational structures using NumPy and Pandas.

  • Data Processing: Execute rigorous data cleaning, automated data transformations, and exploratory data analysis (EDA).

  • Visuals & Automation: Generate dynamic charts utilizing Matplotlib and Plotly, and set up data analytics automation scripts.

Module 6: Microsoft Power BI

  • Data Infrastructure: Import, transform, and clean disparate sources using Power Query alongside advanced data modeling techniques.

  • Metrics & Layouts: Master DAX (Data Analysis Expressions) fundamentals to construct rich interactive dashboards and structured KPI reports.

  • Cloud Operations: Deploy, manage, and share your data products on the Power BI Service.

Module 7: Tableau for Data Visualization

  • Platform Core: Master Tableau fundamentals and construct secure, live database connections.

  • Narrative Design: Build highly interactive dashboards, present actionable storytelling with data, and manage automated business reporting.

  • Advanced Calculations: Build automated data forecasting pipelines directly inside your visualizations.

Module 8: Generative AI for Data Analytics

  • LLM Architectures: Explore Generative AI basics and Prompt Engineering workflows using ChatGPT, Google Gemini, Microsoft Copilot, and Claude AI.

  • AI Engine Optimization: Accelerate delivery with AI-assisted data cleaning, AI-powered SQL script generation, and AI-driven report and dashboard generation.

  • Workflow Acceleration: Maximize production output leveraging AI productivity and analytics automation tools.

Module 9: Professional Development

  • Career Readiness: Intensive resume building, professional GitHub portfolio setup, and LinkedIn profile optimization.

  • Soft Skills & Strategy: Refine presentation skills, review strategic case study discussions, and prepare for technical and behavioral interviews.

Frequently Asked Questions

What is an AI-Integrated Data Analytics with GenAI Crash Course?

It is a short-term practical course that combines data analytics, artificial intelligence, and Generative AI to help learners analyze data and generate useful insights efficiently.

Will I learn Prompt Engineering?

Yes. Prompt engineering techniques can help learners create effective prompts for AI tools used in data analysis, reporting, research, and business tasks.

How is GenAI used in Data Analytics?

GenAI can assist with data exploration, generating analytical summaries, identifying patterns, creating reports, explaining results, and supporting data-driven decision-making.

Will I learn Power BI or data visualization?

Depending on the course curriculum, learners can explore Power BI and other visualization techniques for creating interactive dashboards and presenting insights.

Is the training practical?

Yes. Practical exercises and mini-projects can help learners apply analytics and GenAI tools to real-world datasets and business scenarios.