Course Overview

Data is the backbone of modern business, and Data Analytics is one of the most sought-after skills in the industry today. Techxeeria Technologies Pvt. Ltd. offers a comprehensive Data Analytics using Excel, SQL & Python Course that transforms beginners into job-ready professionals in 6 months. This course combines Excel, SQL, and Python training, along with real-world projects and hands-on assignments, preparing students for roles like Data Analyst, Business Analyst, and Analytics Consultant.

Why Choose This Data Analytics Training?

• Learn Excel for data management, visualization, and dashboard creation
• Master SQL for querying, data manipulation, and reporting
• Gain Python skills for data handling, cleaning, visualization, and automation
• Work on mini-projects and capstone projects for practical experience
• Resume building, portfolio creation, and mock interviews for career readiness

6-Month Data Analytics Syllabus (Day 1–180)

Month 1 – Excel for Data Analytics

Week 1: Excel Basics

• Day 1: Introduction to Excel & Data Analytics
• Day 2: Excel Interface & Shortcuts
• Day 3: Data Entry, Formatting & Cleaning
• Day 4: Sorting & Filtering Data
• Day 5: Conditional Formatting
• Day 6: Excel Tables & Structured References
• Day 7: Mini Project – Sales Data Cleaning

Week 2: Excel Functions (Beginner → Intermediate)

• Day 8: Text Functions – LEFT, RIGHT, CONCAT, TRIM
• Day 9: Math Functions – SUM, AVERAGE, ROUND
• Day 10: Logical Functions – IF, AND, OR
• Day 11: Lookup Functions – VLOOKUP, HLOOKUP
• Day 12: INDEX & MATCH
• Day 13: Date & Time Functions
• Day 14: Mini Project – HR Data Analysis

Week 3: Data Analysis Tools

• Day 15: Pivot Tables Basics
• Day 16: Advanced Pivot Tables – Grouping, Slicers
• Day 17: Pivot Charts
• Day 18: Power Query – Data Cleaning Automation
• Day 19: Power Pivot & Data Model
• Day 20: Data Consolidation Techniques
• Day 21: Mini Project – Regional Sales Dashboard

Week 4: Data Visualization in Excel

• Day 22: Bar, Line, Pie, Combo Charts
• Day 23: Advanced Charts – Waterfall, Funnel
• Day 24: Conditional Charts
• Day 25: Dashboard Design Principles
• Day 26: Interactive Dashboards with Slicers
• Day 27: Excel Add-ins for Analytics
• Day 28: Project – Business Dashboard in Excel

Month 2 – SQL for Data Analytics

Week 5: SQL Basics

• Day 29: Introduction to Databases & SQL
• Day 30: Installing MySQL / PostgreSQL
• Day 31: Basic Queries – SELECT, WHERE, ORDER BY
• Day 32: Aliases & DISTINCT
• Day 33: Aggregate Functions – SUM, AVG, COUNT
• Day 34: GROUP BY & HAVING
• Day 35: Mini Project – Retail Sales Queries

Week 6: Joins & Relationships

• Day 36: INNER JOIN
• Day 37: LEFT & RIGHT JOIN
• Day 38: FULL OUTER JOIN
• Day 39: SELF JOIN
• Day 40: UNION & INTERSECT
• Day 41: Subqueries & Nested Queries
• Day 42: Mini Project – Employee Database

Week 7: SQL Advanced Queries

• Day 43: CASE Statements
• Day 44: String Functions
• Day 45: Date & Time Functions
• Day 46: Window Functions – ROW_NUMBER, RANK
• Day 47: Common Table Expressions (CTE)
• Day 48: Views in SQL
• Day 49: Mini Project – Customer Segmentation

Week 8: SQL for Data Analytics

• Day 50: Data Cleaning with SQL
• Day 51: Exploratory Data Analysis (EDA) using SQL
• Day 52: Correlated Subqueries
• Day 53: Advanced Joins with Multiple Tables
• Day 54: Performance Optimization – Indexes
• Day 55: Case Study – Business Data Analysis
• Day 56: Project – Analytics on E-commerce Data

Month 3 – Python Basics for Analytics

Week 9: Python Fundamentals

• Day 57: Installing Python & Jupyter Notebook
• Day 58: Variables, Data Types & Operators
• Day 59: Lists, Tuples & Dictionaries
• Day 60: Conditional Statements
• Day 61: Loops – for, while
• Day 62: Functions in Python
• Day 63: Mini Project – Student Grade Calculator

Week 10: Python for Data Handling

• Day 64: File Handling – CSV, Excel, JSON
• Day 65: Numpy Basics – Arrays, Indexing
• Day 66: Numpy Operations – Math & Statistics
• Day 67: Pandas Basics – Series & DataFrames
• Day 68: Data Cleaning – Missing & Duplicate Values
• Day 69: Data Transformation – Merge, Join, GroupBy
• Day 70: Mini Project – Sales Data Cleaning with Pandas

Week 11: Python Visualization Basics

• Day 71: Introduction to Matplotlib
• Day 72: Line, Bar, Scatter Plots
• Day 73: Histograms & Boxplots
• Day 74: Subplots & Customization
• Day 75: Introduction to Seaborn
• Day 76: Heatmaps & Pairplots
• Day 77: Mini Project – HR Analytics Visualization

Week 12: Python Advanced Visualization & Automation

• Day 78: Time Series Visualization
• Day 79: Advanced Seaborn Plots
• Day 80: Plot Styling & Themes
• Day 81: Automating Reports with Python
• Day 82: Exporting Results to Excel/CSV
• Day 83: Case Study – Financial Data Analysis
• Day 84: Project – Python Data Analytics Dashboard

Month 4 – Advanced Analytics with Python & SQL

Week 13–16

• Day 85–90: Descriptive Statistics, Probability, Hypothesis Testing, Correlation Analysis, Mini Project – Sales Data
• Day 91–96: Exploratory Data Analysis (EDA), Feature Engineering, SQL + Python EDA, Mini Project – E-commerce Dataset
• Day 97–102: Python + SQL Integration, ETL, Automating Reports, Mini Project – Automated Sales Report
• Day 103–110: Data Wrangling, Handling Large Datasets, Regex, Data Transformation Pipelines, Mini Project – Real-world Data Cleaning

Month 5 – Advanced Data Analytics

Week 17–20

• Day 111–116: Time Series Analysis – Trends, Seasonality, Rolling Statistics, Mini Project – Stock Price Analysis
• Day 117–122: Predictive Analytics – Linear & Logistic Regression, Train-Test Split, Mini Project – Sales Revenue Prediction
• Day 123–128: Classification & Clustering – Decision Trees, Random Forest, K-Means, Model Evaluation, Mini Project – Loan Default Prediction
• Day 129–134: Dashboard Building – Excel Dashboards, Python Dash/Streamlit, SQL + Python + Excel Dashboard, Mini Project – Business Insights Dashboard

Month 6 – Capstone Projects & Career Prep

Week 21–24: Capstone Projects

• Day 135–145: Capstone Project 1 – Business Domain (Finance / Retail / HR)
• Day 146: Project Presentation & Review
• Day 147–157: Capstone Project 2 – Real-time Analytics (E-commerce / Marketing / Healthcare)
• Day 158: Project Presentation & Review

Week 25–26: Career Preparation

• Day 159–163: Resume Building
• Day 164–166: Portfolio Building (GitHub + LinkedIn)
• Day 167–169: Mock Interviews – SQL, Python, Analytics
• Day 170: Q&A Session – Career Guidance
• Day 171–175: Revision of Key Concepts (Excel, SQL, Python)
• Day 176–178: Final Assessment
• Day 179: Doubt Clearing & Career Planning
• Day 180: Certification & Graduation

Hands-On Training

• Mini Projects in every module (Excel, SQL, Python)
• Final Capstone Project – Full-scale Analytics Dashboard
• Cloud Deployment (Optional – AWS/Heroku)
• Resume & Portfolio Setup for Job Readiness

Who Can Join?

• Beginners aiming to become Data Analysts
• Python learners exploring SQL and Data Analytics
• Students preparing for IT placements
• Professionals upskilling for analytics roles

Career Opportunities

After completing this Data Analytics using Excel, SQL & Python Training, you can apply for roles like:

• Data Analyst
• Business Analyst
• Python Data Analyst
• SQL Data Analyst
• Analytics Consultant