Data Analytics with Agentic AI

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Data Analytics with Agentic AI

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About Course

Learn how to transform raw data into meaningful insights using Python, from data cleaning and analysis to interactive visualizations. Master pandas, NumPy, Matplotlib & Seaborn, and build end-to-end dashboards to drive smarter business decisions.

What Will You Learn?

  • Understand the complete data analytics lifecycle — from collecting raw data to presenting insights
  • Work confidently with Python for data analysis, including variables, data types, and structures
  • Manipulate and clean data using pandas and NumPy
  • Perform Exploratory Data Analysis (EDA) to uncover trends and correlations
  • Visualize insights with Matplotlib and Seaborn using effective design principles
  • Build interactive, business-ready dashboards and reports in Python
  • Identify and treat missing data and outliers
  • Combine multiple datasets through merging, joining, and grouping operations
  • Translate analytical findings into strategic business decisions
  • Document and present results with professional data storytelling
  • Apply your learning through a capstone mini-project using a real-world dataset
  • Explore next-step tools like SQL, Tableau, and Power BI to expand your analytics journey

Course Content

Module 1 : Excel Fundamentals – 1 Week (4 Hours)
Build confidence in handling raw datasets in Excel and apply basic statistical analysis.

  • Types of Data (Qualitative / Quantitative)
  • Excel Introduction & Cell Formatting
  • Copy-Paste Operations
  • Filtering & Sorting Data
  • Basic Aggregations (SUM, AVERAGE)
  • Text Data Cleaning
  • Logical Functions: IF, AND
  • Lookup Basics & INDEX Function
  • Data Exploration Intro
  • Frequency Distributions, Mean, Median, Mode
  • Variance & Standard Deviation, Z-Score
  • Correlation & Hypothesis Testing

Module 2: Excel Analysis Tools – 1 Week (4 Hours)
Perform business reporting and forecasting using advanced Excel tools.

Module 3: SQL Basics – 1 Week (4 Hours)
Write SQL queries to extract, filter, and organize structured data.

Module 4: SQL Advanced Concepts – 1 Week (4 Hours)
Solve business queries with advanced joins and time-based analytics.

Module 5: SQL Subqueries & CTEs – 2 Week (8 Hours)
Create optimized SQL pipelines for complex queries.

Module 6: SQL Window Functions – 1 Week (4 Hours)
Perform advanced reporting and time-series analysis using window functions.

Module 7: Power BI Basics, Power Query & Visualizations – 1 Week (4 Hours)
Build interactive dashboards and reports in Power BI.

Module 8: Core DAX (Fundamentals) – 2 Weeks (8 Hours)
Apply DAX formulas for calculated columns, measures, and KPIs.

Module 9: Intermediate DAX (Filter & Time Intelligence) – 1 Week (4 Hours)
Analyze trends and patterns with advanced DAX functions.

Module 10: Advanced DAX & Enterprise Features – 1 Week (4 Hours)
Deliver enterprise-level BI dashboards with advanced metrics and row-level security.

Module 11: Python Basics – 1 Week (4 Hours)
Write basic Python scripts for data handling.

Module 12: Python Loops & Functions – 1 Week (4 Hours)
Automate repetitive tasks and create reusable Python functions.

Module 13: NumPy Foundations – 1 Week (4 Hours)
Perform mathematical operations on large datasets efficiently.

Module 14: Pandas Foundations – 1 Week (4 Hours)
Manage, clean, and manipulate datasets using Pandas.

Module 15: Exploratory Analysis – 1 Week (4 Hours)
Perform exploratory data analysis (EDA) and visualize insights.

Module 16: AI in Power BI – 1 Week (2 Hours)
Integrate AI-driven insights directly into dashboards.

Module 17: Agentic AI Basics & No-Code Agent Building with Flow wise – 2 Weeks (8 Hours)
Build no-code AI agents for automation and document intelligence.

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S
skillancy
4 months ago
Nice content and well planned course
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