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Data Analytics with Agentic AI
Total Duration: 20 Weeks (~80 hrs) / 5 Months
Module 1 : Excel Fundamentals
Build confidence in handling raw datasets in Excel and apply basic statistical analysis.
Time : 1 week (4 Hours)
Tools : Excel
What you'll learn:
- 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
Perform business reporting and forecasting using advanced Excel tools.
Time : 1 week (4 Hours)
Tools : Excel
What you'll learn:
- Pivot Tables
- What-If & Scenario Analysis
- Sensitivity Analysis
- Forecasting & Seasonality Handling
- Confidence Intervals
- Moving & Weighted Averages
- Using Slicers
- Charts & Graphs
- Chart Formatting
Module 3: SQL Basics
Write SQL queries to extract, filter, and organize structured data.
Time : 1 week (4 Hours)
Tools : SQL
What you'll learn:
- Database & Table Basics
- Primary vs Foreign Keys
- SQL Constraints & DDL Statements
- Dimension Modeling
- Query Structure (SELECT → HAVING)
- Aliases & SQL Operators
- Sorting & Limiting Data
- Views
Module 4: SQL Advanced Concepts
Solve business queries with advanced joins and time-based analytics.
Time : 1 week (4 Hours)
Tools : SQL
What you'll learn:
- Date & Time Formats
- Comparing Dates & Date Aggregations
- Time Difference Calculations
- CASE Statements
- Joins: Inner, Left, Right, Outer, Self
- Equi & Non-Equi Joins
Module 5: SQL Subqueries & CTEs
Create optimized SQL pipelines for complex queries.
Time : 2 weeks (8 Hours)
Tools : SQL
What you'll learn:
- Basic Subqueries
- Correlated & Nested Subqueries
- Common Table Expressions (CTEs)
- Recursive CTEs
Module 6: SQL Window Functions
Perform advanced reporting and time-series analysis using window functions.
Time : 1 week (4 Hours)
Tools : SQL
What you'll learn:
- RANK(), DENSE_RANK(), ROW_NUMBER()
- COUNT(), AVG(), SUM()
- LEAD & LAG Functions
- Temporary Tables
Module 7: Power BI Basics, Power Query & Visualizations
Build interactive dashboards and reports in Power BI.
Time : 1 week (4 Hours)
Tools : Power BI
What you'll learn:
- Intro to BI & Power BI Ecosystem
- Getting Data from Excel/CSV
- Power Query Basics (Remove Errors, Duplicates, Split, Merge, Unpivot)
- Data Modeling (Fact → Dimension)
- Visualization Basics: Tables, Cards, Charts, Maps
- Filters & Slicers
- Hierarchies & Drilldowns
Module 8: Core DAX (Fundamentals)
Apply DAX formulas for calculated columns, measures, and KPIs.
Time : 2 weeks (8 Hours)
Tools : Power BI
What you'll learn:
- Relationship Functions: RELATED, LOOKUPVALUE
- Logical Functions: IF, SWITCH
- CALCULATE (Filter Context)
- ALL, ALLEXCEPT, ALLSELECTED
Module 9: Intermediate DAX (Filter & Time Intelligence)
Analyze trends and patterns with advanced DAX functions.
Time : 1 week (4 Hours)
Tools : Power BI
What you'll learn:
- FILTER, VALUES, DISTINCT
- CALCULATE + FILTER (Context Transition)
- Time Intelligence Functions: DATEADD, SAMEPERIODLASTYEAR, PARALLELPERIOD
- TOTALYTD, TOTALQTD, TOTALMTD
- Running Totals & Rolling Averages
Module 10: Advanced DAX & Enterprise Features
Deliver enterprise-level BI dashboards with advanced metrics and row-level security.
Time : 1 week (4 Hours)
Tools : Power BI
What you'll learn:
- Dynamic Segmentation with SWITCH(TRUE())
- CALCULATE + FILTER (Context Transition)
- Customer Lifetime Value (CLV)
- What-if Parameters
- Incremental Refresh (RangeStart/RangeEnd)
- Capstone Project (Retail Dataset):
- Data Cleaning (Power Query)
- Model Building
- Advanced DAX (YoY Growth, RANKX, CLV)
- Dashboard (KPIs, Visuals)
- Publish to Service
- Apply RLS (Region-level security)
- Incremental Refresh
Module 11: Python Basics
Write basic Python scripts for data handling.
Time : 1 week (4 Hours)
Tools : Python
What you'll learn:
- Python Variables & Data Types
- Lists, Tuples, Ranges, Dictionaries, Booleans
- Operators & Conditional Statements
- Nested Conditions
Module 12: Python Loops & Functions
Automate repetitive tasks and create reusable Python functions.
Time : 1 week (4 Hours)
Tools : Python
What you'll learn:
- For & While Loops
- Nested Loops
- Defining Functions & Arguments
- Built-in Functions
Module 13: NumPy Foundations
Perform mathematical operations on large datasets efficiently.
Time : 1 week (4 Hours)
Tools : Python, NumPy
What you'll learn:
- NumPy Introduction
- Creating Arrays & Operations
- Indexing & Slicing
- Reshaping Arrays
- Statistical Functions
Module 14: Pandas Foundations
Manage, clean, and manipulate datasets using Pandas.
Time : 1 week (4 Hours)
Tools : Python, Pandas
What you'll learn:
- Intro to Pandas & DataFrames
- Filtering Data
- Cleaning & Transforming
- Indexing & Merging
- Time Series in Pandas
- File I/O with Pandas
Module 15: Exploratory Analysis
Perform exploratory data analysis (EDA) and visualize insights.
Time : 1 week (4 Hours)
Tools : Python, Seaborn, Matplotlib
What you'll learn:
- Data Cleaning & Validation
- Univariate → Multivariate Analysis
- Handling Outliers
- Categorical Feature Handling
- Time-based Analysis
- Data Visualization (Seaborn, Matplotlib)
Module 16: AI in Power BI
Integrate AI-driven insights directly into dashboards.
Time : 1 week (2 Hours)
Tools : Power BI
What you'll learn:
- Smart Narratives
- Q&A Visual (Natural Language Query)
- Key Influencers Visual
- Anomaly Detection in Line Charts
Module 17: Agentic AI Basics & No-Code Agent Building with Flowise
Build no-code AI agents for automation and document intelligence.
Time : 2 week (8 Hours)
Tools : Flowise AI, LangChain, Hugging Face
What you'll learn:
- AI Agents: Difference between Chatbots, Assistants & Autonomous Agents
- Intro to LangChain (Chains, Tools, Memory)
- Installing & Setting up Flowise AI
- Drag-and-Drop Agent Builder
- Creating a Chat with CSV Agent
- Building an FAQ Bot (Train on Text/PDF)