Advanced Excel Mastery with AI Integration
- Description
- Curriculum
- FAQ
- Notice
- Reviews
Course Structure Summary
- Total Sessions: 40 (2 per week x 20 weeks)
- Total Hours: 60 (1.5 hours per session)
- Breakdown:
- Modules 1-2: Foundation and formulas (10 hours)
- Modules 3-4: Analysis and visualization (18 hours)
- Modules 5-6: Power tools (18 hours)
- Module 7: AI integration (6 hours)
- Module 8: Job preparation (8 hours)
- Teaching Approach:
- 40% theory (explaining concepts, demos)
- 50% hands-on (exercises, mini-projects)
- 10% assessments (quizzes, capstone project)
- Tools Covered: Excel (core), Power Query, Power Pivot, DAX, Microsoft Copilot (if available), Power Automate, basic Python for AI (optional), Power BI/Tableau (introductory).
Job-Ready Outcomes
By the end, students will:
- Master advanced Excel functions, PivotTables, and dashboards.
- Automate data tasks with Power Query and Power Pivot.
- Use AI tools to enhance analysis, forecasting, and reporting.
- Build professional dashboards and reports for business scenarios.
- Be confident in interviews with a portfolio of projects (e.g., sales dashboard, financial model).
- Qualify for roles like Data Analyst, Business Analyst, MIS Executive, or Reporting Specialist.
Additional Notes
- Prerequisites: Basic Excel knowledge (e.g., simple formulas, formatting).
- Resources: Provide students with sample datasets, cheat sheets, and access to Microsoft 365 (for Power Query/Pivot). Free AI tools like Power BI Desktop can be included.
- Assessments: Weekly quizzes, mid-course test, and a final capstone project.
- AI Tools: If Microsoft Copilot isn’t available, use free alternatives like Python (via Jupyter Notebook) or Power Automate for automation demos.
- Certification: Issue a course completion certificate highlighting “Advanced Excel with AI Implementation” to boost employability.
Basic Excel Foundations (Week 1-3, 6 Sessions)
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1
Introduction to Excel: Interface, ribbons, workbooks, and worksheets. -
2
Data entry formatting (fonts, colors, borders).
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3
Relative vs. absolute references.
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4
Simple formulas: IF, basic arithmetic (+, -, *, /),
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5
Data organization Sorting, filterin
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6
Basic charts: Bar, line, pie, and chart formatting. freeze panes.
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7
Printing and saving: Page layout, PDF export, and file management.
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8
Filter & Condition
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9
Hands-On: Create a personal budget tracker with basic formulas and a chart.
Advanced Formulas and Functions (Week 4-6, 6 Sessions)
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10
Test Function Class 1
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11
Test Function Class 2
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12
Lookup functions: VLOOKUP, HLOOKUP, INDEX, MATCH, XLOOKUP.
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13
Text functions: LEFT, RIGHT, MID, CONCAT, TEXTJOIN.
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14
Financial functions: PV, NPV, IRR.EDATE, DATEDIF, NETWORKDAYS.
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15
Build a dynamic inventory tracker using advanced formulas.
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16
Advance Chart and Waffle chart
Module 1: Excel Fundamentals Refresher (Week 1-2, 4 Sessions)
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17
Spreadsheet navigation, shortcuts, and customization.
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18
Data types, formatting, and conditional formatting basics.
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19
Essential functions: SUM, AVERAGE, IF, COUNTIF, VLOOKUP, HLOOKUP.
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20
Data validation and error-checking techniques.
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21
Introduction to tables and structured references.
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22
Hands-On: Create a formatted sales tracker with basic calculations.
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23
AI Teaser: Overview of AI-driven data cleaning tools (e.g., Power Query with AI suggestions).
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24
Data cleaning
Advanced Formulas and Functions (Week 3-5, 6 Sessions)
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25
Master complex formulas for data manipulation and analysis. -
26
Logical functions: IFERROR, IFS, AND, OR, nested IFs.
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27
Lookup functions: INDEX, MATCH, XLOOKUP, XMATCH.
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28
Text functions: LEFT, RIGHT, MID, CONCAT, TEXTJOIN, FIND, SEARCH.
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29
Date and time functions: EDATE, EOMONTH, DATEDIF, NETWORKDAYS.
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30
Array formulas and dynamic arrays (FILTER, SORT, UNIQUE, SEQUENCE).
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31
Financial functions: PV, FV, NPV, IRR for business calculations.
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32
Hands-On: Build a dynamic employee payroll system using advanced formulas.
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33
AI Integration: Use Excel’s built-in AI (e.g., Ideas/Insights) to suggest formula optimizations.
Module 3: Data Analysis with PivotTables and PivotCharts (Week 6-8, 6 Sessions)
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34
ObjectiveObjective: Enable students to summarize and visualize data effectively.
Duration: 9 hours -
35
Creating and customizing PivotTables.
Enable students to summarize and visualize data effectively.
Duration: 9 hours -
36
Grouping, filtering, and sorting data in PivotTables.
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37
Calculated fields and items in PivotTables.
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38
Slicers and timelines for interactive dashboards.
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39
PivotCharts: Types (bar, line, pie) and formatting.
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40
Connecting multiple PivotTables for complex analysis.
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41
Hands-On: Analyze a retail dataset to identify sales trends using PivotTables/Charts.
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42
AI Integration: Use Microsoft Copilot (if available in Excel) to generate PivotTable suggestions or Power BI for enhanced visuals.
Module 4: Data Visualization and Dashboards (Week 9-11, 6 Sessions)
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43
Advanced charting: Combo charts, sparklines, waterfall, funnel charts.
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44
Conditional formatting for visual insights (data bars, color scales, icon sets).
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45
Designing interactive dashboards using slicers and form controls.
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46
Best practices for dashboard layout and storytelling with data.
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47
Linking charts with PivotTables for dynamic updates.
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48
Hands-On: Build a sales performance dashboard with multiple KPIs.
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49
AI Integration: Use AI tools like Tableau Public or Power BI (connected to Excel) to suggest visualizations or predict trends.
Module 5: Power Query for Data Transformation (Week 12-14, 6 Sessions)
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50
Importing data from various sources (CSV, Excel, databases, web).
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51
Handling missing data, duplicates, and inconsistencies.
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52
Advanced transformations: Pivoting, unpivoting, custom columns.
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53
Automating repetitive tasks with Power Query scripts.
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54
Hands-On: Clean and transform a messy customer dataset for analysis.
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55
AI Integration: Explore AI-driven data profiling in Power Query or third-party tools like Alteryx for automation suggestions.
Module 6: Power Pivot and DAX (Week 15-17, 6 Sessions)
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56
Introduction to Power Pivot and data models.
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57
Creating relationships between tables.
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58
Introduction to DAX (Data Analysis Expressions): SUMX, CALCULATE, FILTER.
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59
Time intelligence functions: TOTALYTD, SAMEPERIODLASTYEAR.
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60
Building measures and KPIs for advanced analysis.
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61
Optimizing Power Pivot models for performance.
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62
Hands-On: Create a financial dashboard with Power Pivot and DAX calculations.
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63
AI Integration: Use AI to suggest DAX formulas or optimize data models (e.g., via Copilot or external tools).
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64
Why?Power Pivot and DAX are essential for handling complex datasets in corporate environments.
Module 7: AI Implementation in Excel (Week 18-19, 4 Sessions)
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65
Excel + Copilot Tutorial For Beginners! Master AI-Powered Spreadsheets in Minutes
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66
How to Use AI in Excel | Complete Beginner Tutorial (Step by Step)
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67
AI-driven forecasting and trend analysis in Excel.
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68
Automating repetitive tasks with AI-powered macros or Power Automate flows.
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69
Hands-On: Build an AI-assisted sales forecasting model using Excel and Python/Power Automate.
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70
AI Focus: Explore how AI can predict outcomes or automate report generation.
Module 8: Job-Ready Projects and Soft Skills (Week 20, 2 Sessions)
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71
Capstone project: End-to-end analysis (e.g., retail, finance, or HR dataset) using all learned tools.
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72
Resume building with Excel and AI skills highlighted.Resume building with Excel and AI skills highlighted.
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73
nterview preparation: Common Excel-related questions and case studies.
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74
Presentation skills for showcasing dashboards to stakeholders.
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75
Best practices for collaboration (e.g., OneDrive, SharePoint integration).
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76
Hands-On: Present capstone project to peers, simulating a corporate meeting.
Who is this course for?
This course is designed for intermediate Excel users who want to master advanced Excel techniques, learn AI-driven data analysis, and become job-ready for roles like Data Analyst, Business Analyst, or MIS Executive.
What are the prerequisites?
Basic knowledge of Excel (e.g., simple formulas like SUM, IF, and basic formatting) is required. No prior AI experience is needed.
What is the course duration and schedule?
The course runs for 5 months, with 2 classes per week, each lasting 1.5 hours (total 60 hours).
Will I learn AI in this course?
Yes! You’ll explore AI tools like Microsoft Copilot (if available), Power Automate, and basic Python integration to automate tasks, forecast trends, and enhance data analysis in Excel.
What tools will I use?
You’ll master Excel (advanced formulas, PivotTables, Power Query, Power Pivot), DAX, and introductory Power BI/Tableau. AI tools like Power Automate and Python (optional) will be covered for automation and insights.
Is this course job-oriented?
Absolutely! The course includes real-world projects (e.g., sales dashboards, financial models), resume-building tips, and interview preparation to make you job-ready.
Do I need special software?
You’ll need Microsoft Excel (preferably Microsoft 365 for Power Query/Pivot features). Free tools like Power BI Desktop and Python (optional) will be used for AI integration.
Will I get a certificate?
Yes, upon completion, you’ll receive a certificate in “Advanced Excel Mastery with AI Integration,” highlighting your skills for employers.
Are there any assessments?
Yes, the course includes weekly quizzes, a mid-course test, and a capstone project to showcase your skills.
Can I access course materials after completion?
Yes, you’ll get access to sample datasets, cheat sheets, and recorded sessions (if available) for future reference.
Subject: Billing & Fee Submission Guidelines
Billing Cycle: The billing cycle starts on the 1st day of every new month. Both one-time and monthly fee payment options are available for every student.
Fee Submission Date: Students must submit their course fees between the 1st and 10th of each month. A late fee of Rs. 25/- will be charged if the payment is not made within this period.
Non-Refundable Fee Policy: If a student leaves midway during the course or after admission, the course fee will not be refundable under any circumstances.
Student Conduct: Any mischief or misconduct by a student will not be tolerated. The institute reserves the right to take disciplinary action, which may include rejection from the institution.
Health Disclaimer: The institute will not be responsible for any health issues that a student may face while on the premises. If a student suffers from any sudden physical illness, the institution holds no liability.
LMS Access: If a student leaves before the end of the course period, access to the Learning Management System (LMS) will not remain active as per institutional policy. The Learning Management System (LMS) will remain active throughout the course period and for an additional six months after the final exam and certification.
For more details, please refer to our terms and conditions at: www.learngyan.co/student/termsandcondition
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