Certify
Master in

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)
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