Data Analyst Training Program

1 Month Basic + 2 Months Expert

Frequency: 3 Classes/Week | Duration per Class: 2 Hours
Tools Covered: Power BI, SQL, Excel, Python

Course Fee Structure

Learning Path Fee (PKR)
Beginner to Expert Level
Pkr.20,000/-
Expert Level Only
Pkr.15,000/-
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Beginner Level (Foundation Track) – Month 1

  • Day 1: Intro to Data Analytics & Excel; working with datasets, cleaning basics
  • Day 2: Functions: SUM, AVERAGE, MIN, MAX, IF, nested IF
  • Day 3: COUNT, COUNTIF, logical functions, text manipulation
  • Day 4: Lookup functions: VLOOKUP, HLOOKUP
  • Day 5: INDEX-MATCH combo + practice
  • Day 6: Date functions (TODAY, YEAR, MONTH, NETWORKDAYS), conditional formatting
  • Day 7: Pivot Tables (summarizing data, grouping)
  • Day 8: Pivot Charts & slicers
  • Day 9: Case Study: Analyze sales dataset with Pivot Tables
  • Day 10: Interactive dashboards with charts & slicers
  • Day 11: Formatting, storytelling with data in Excel
  • Day 12: Review + Assignment 1 + Quiz 1 + Project 1 Launch

Expert Track – Month 2

  • Day 13: Intro to BI, Power BI interface, importing data
  • Day 14: Power Query Editor: cleaning, shaping data
  • Day 15: Combining multiple datasets (append, merge)
  • Day 16: Relationships between tables (1-to-many, many-to-many)
  • Day 17: Star schema basics; calculated columns vs measures
  • Day 18: Hands-on practice: build a simple model
  • Day 19: Intro to DAX: SUM, AVERAGE, COUNTROWS
  • Day 20: CALCULATE & FILTER
  • Day 21: Time intelligence: YTD, MTD, QTD
  • Day 22: Basic visuals (tables, bar, line, pie, KPI cards)
  • Day 23: Drill-downs, hierarchies, slicers, maps
  • Day 24: Dashboard creation + Assignment 2 + Quiz 2 + Project 2 Launch

Expert Track – Month 3

  • Day 25: Python intro; variables, operators, data types
  • Day 26: Conditionals (if-else), loops (for, while)
  • Day 27: Lists, dictionaries, functions
  • Day 28: Intro to Pandas; loading CSV, exploring data (head, describe, info)
  • Day 29: Filtering, sorting, grouping, aggregations
  • Day 30: Data cleaning (missing values, duplicates, string ops), intro to visualization
  • Day 31: Intro to databases & SQL; SELECT, WHERE, ORDER BY
  • Day 32: Aggregations: SUM, AVG, COUNT, GROUP BY, HAVING
  • Day 33: JOINS (INNER, LEFT, RIGHT, FULL)
  • Day 34: Subqueries & CTEs
  • Day 35: SQL + Power BI/Python integration (import SQL data)
  • Day 36: Assignment 3 + Quiz 3 + Final Project 3 Presentations
  • Beginner Modules (1–4) → Month 1
  • Advanced Modules (5–8) → Month 2 & 3
  • Capstone Project → Last 2 weeks of Month 3
  • Assignments (3 × 5) → 15
  • Quizzes (3 × 5) → 15
  • Projects (3 × 20) → 60
  • Final Presentation & Participation → 10
  • Total = 100
    For capstone project student will be choosing their own dataset and can use tool of their choice for this one/ we can provide them a real time dataset from any government organization and they can provide their own insights using their own potential tool.
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About the Instructor

Tayyaba Zahid

Tayyaba Zahid is a Data Analyst and Trainer with over two years of experience in data analytics, visualization, and automation. She has worked on diverse projects ranging from banking and healthcare analytics to predictive modeling and business intelligence solutions. Passionate about simplifying data for decision-making, Tayyaba now trains students and professionals in SQL, Power BI, Python, and Excel. She also shares insights through content creation and project-based learning.

  • Bachelor’s degree in Computer Science with major of Data Science
  • Certifications in Data Analytics, Business Intelligence, and Machine Learning from IBM, Johns Hopkins University and Google

Over 2 years of experience as a Data Analyst and Python Developer, with industry experience in business analytics, dashboard development, and automation. Currently working as, a Data Analyst Trainer, delivering structured programs in SQL, Power BI, Python, and Excel. Freelancing and professional projects include building interactive dashboards, predictive models, and end-to-end data workflows for banking, retail, and healthcare datasets.

  • Data Analysis & Visualization (Power BI, Tableau, Excel)
  • SQL (MySQL, SQL Server, Google Cloud BigQuery)
  • Python for Data Science
  • Business Intelligence & Reporting
  • Machine Learning Fundamentals
  • Data Cleaning, EDA, and Automation
  • Developed dashboards in Finance and Marketing sector and optimize them.
  • Completed Heart Disease Prediction Model using machine learning.
  • Conducted multiple freelancing projects in data analysis on Upwork.
  • Currently concluding Data Analytics course with AI integration