Data Analytics Professional Course

Master Data Analytics with Python, SQL, Excel, Tableau, and Power BI. Learn data cleaning, visualization, and storytelling to become a job-ready data analyst.

Duration 3 Months (100 Hours)
Mode Live Online / Offline
4,500+ Students
400+ Partners
92% Placement

📈 Your Market Value After This Course

What you'll achieve and how much you can earn after completing Data Analytics

Fresher / Entry Level

₹4 - 6 LPA

0-2 years experience

  • Junior Data Analyst
  • BI Trainee
⭐ Most Common

Mid Level

₹7 - 14 LPA

2-5 years experience

  • Data Analyst
  • Business Intelligence Analyst

Senior / Expert Level

₹15 - 28+ LPA

5+ years experience

  • Senior Data Analyst
  • Analytics Manager

🎯 Job Roles You Can Apply For

Data Analyst
Business Analyst
BI Analyst
Operations Analyst
Marketing Analyst
Financial Analyst

⚡ Skills You'll Master

Excel
SQL
Python
Pandas
Power BI
Tableau
Data Visualization
Statistics
Data Cleaning
Storytelling

📚 Complete Course Syllabus

Master every aspect with our comprehensive curriculum

Module 1: Introduction to Data Analytics

  • What is Data Analytics - Importance & Scope
  • Types of Data Analytics - Descriptive, Diagnostic, Predictive, Prescriptive
  • Data Analytics Lifecycle
  • Data Analyst Roles & Responsibilities
  • Tools Overview - Excel, SQL, Python, Power BI, Tableau

Module 2: Excel for Data Analytics

  • Excel Basics - Formulas, Functions, Referencing
  • Data Cleaning in Excel - Remove Duplicates, Text to Columns, Find/Replace
  • Conditional Formatting & Data Validation
  • Pivot Tables & Pivot Charts
  • Advanced Excel Functions - VLOOKUP, INDEX-MATCH, IF, SUMIFS
  • Power Query for Data Transformation
  • Dashboards in Excel
  • Macros & VBA Basics

Module 3: SQL for Data Analysis

  • Introduction to Databases & SQL
  • SQL Basics - SELECT, FROM, WHERE
  • Filtering Data - AND, OR, IN, BETWEEN, LIKE
  • Sorting & Grouping - ORDER BY, GROUP BY, HAVING
  • Joins - INNER, LEFT, RIGHT, FULL, CROSS JOIN
  • Subqueries & CTEs (Common Table Expressions)
  • Aggregate Functions - COUNT, SUM, AVG, MIN, MAX
  • Window Functions - ROW_NUMBER, RANK, LEAD, LAG
  • Date & String Functions
  • Views & Stored Procedures

Module 4: Python for Data Analytics

  • Python Basics - Variables, Data Types, Operators
  • Control Flow - if-else, Loops (for, while)
  • Functions & Lambda Expressions
  • Data Structures - Lists, Tuples, Dictionaries, Sets
  • List Comprehensions & Generators
  • File Handling - Reading/Writing CSV, JSON, Excel
  • Error Handling & Debugging

Module 5: Data Manipulation with Pandas

  • Introduction to Pandas - Series & DataFrame
  • Reading Data - CSV, Excel, JSON, SQL
  • Data Inspection - head, tail, info, describe
  • Data Cleaning - Handling Missing Values (dropna, fillna)
  • Handling Duplicates & Outliers
  • Data Transformation - apply, map, replace
  • Filtering & Sorting Data
  • Grouping & Aggregation - groupby, agg, pivot_table
  • Merging, Joining, Concatenating DataFrames
  • Time Series Analysis

Module 6: Data Visualization with Matplotlib & Seaborn

  • Introduction to Data Visualization
  • Matplotlib - Line, Bar, Scatter, Histogram
  • Customizing Plots - Labels, Titles, Legends, Colors
  • Subplots & Multiple Plots
  • Seaborn - Statistical Visualizations
  • Heatmaps, Pairplots, Boxplots
  • Plotly - Interactive Visualizations

Module 7: Power BI - Business Intelligence

  • Introduction to Power BI - Components
  • Connecting to Data Sources - Excel, SQL, Web, Cloud
  • Power Query - Data Transformation & Cleaning
  • Data Modeling - Relationships, Calculated Columns
  • DAX (Data Analysis Expressions) - CALCULATE, FILTER, SUMX
  • Creating Visuals - Charts, Maps, Cards, Slicers
  • Interactive Dashboards & Reports
  • Power BI Service - Publishing & Sharing
  • Power BI Mobile & Embedding

Module 8: Tableau - Data Visualization

  • Introduction to Tableau - Products & Features
  • Connecting to Data Sources
  • Data Preparation & Cleaning in Tableau
  • Worksheets & Dashboards
  • Chart Types - Bar, Line, Scatter, Map, Pie
  • Calculated Fields & Parameters
  • Filters, Sets, Groups, Hierarchies
  • Tableau Public vs Desktop vs Server
  • Storytelling with Tableau

Module 9: Statistics for Data Analytics

  • Descriptive Statistics - Mean, Median, Mode, Variance, Std Dev
  • Measures of Spread - Range, IQR, Percentiles
  • Probability Distributions - Normal, Binomial, Poisson
  • Correlation & Covariance
  • Hypothesis Testing - t-test, Chi-square, ANOVA
  • Regression Analysis - Linear & Logistic Regression
  • Sampling Techniques & Confidence Intervals

Module 10: Data Storytelling & Reporting

  • What is Data Storytelling
  • Components of a Data Story
  • Dashboard Design Principles
  • Choosing Right Visualizations
  • Creating Executive Summaries
  • Presenting Data to Stakeholders

Module 11: Real-World Projects

  • Project 1: Sales Data Analysis using Excel & Pivot Tables
  • Project 2: Customer Data Analysis using SQL
  • Project 3: Data Cleaning & Analysis with Python Pandas
  • Project 4: Interactive Dashboard in Power BI
  • Project 5: Sales Performance Dashboard in Tableau
  • Capstone Project - Complete Data Analytics Report

⭐ Why Choose Tekksol Global?

We provide the best learning experience with industry experts

Expert Trainers

Learn from industry professionals with 10+ years of Data Analytics experience

Hands-on Projects

Work on 7+ real-time analytics projects with real datasets

Industry Certification

Get globally recognized Data Analytics certification

100% Placement Support

Tie-ups with 400+ companies for analytics roles

Resume Building

Professional resume & portfolio with analytics projects

Mock Interviews

Regular mock interviews with detailed feedback

💻 Real-Time Projects

Build impressive portfolio with industry-relevant projects

Sales Performance Analysis

Analyze sales data to identify trends, top products, regional performance, and create interactive dashboards.

Excel SQL Power BI Tableau

Customer Segmentation Analysis

Perform customer segmentation using Python to identify customer groups and behavior patterns.

Python Pandas Seaborn Power BI

Financial Data Dashboard

Create a comprehensive financial dashboard in Power BI/Tableau for KPI tracking and reporting.

Power BI Tableau SQL Excel

🚀 Placement Assistance

We're committed to your success beyond the course

Placement Support Includes:
  • Resume & LinkedIn Profile Building
  • Aptitude & Technical Training
  • Mock Interviews with Industry Experts
  • Soft Skills & Communication Training
Our Hiring Partners:
  • 500+ Hiring Partners
  • Unlimited Interview Opportunities
  • Job Portal Access
  • Life-long Placement Support
Our Top Hiring Partners
TCS
Infosys
Wipro
IBM
Capgemini
Accenture
HCL
CTS
Mahindra Tech
Dell
Amazon
Oracle
TCS
Infosys
Wipro
IBM
Capgemini
Accenture
HCL
CTS
Mahindra Tech
Dell
Amazon
Oracle

❓ Frequently Asked Questions

Got questions? We've got answers

What are the prerequisites for Data Analytics course?
Basic computer knowledge is sufficient. No prior programming experience is required.
What is the duration of the course?
The course duration is 3 months (100 hours) with flexible batch timings.
Will I learn both Excel and Python?
Yes, the course covers Excel, SQL, Python, Power BI, and Tableau for complete analytics.
What projects will I build?
You will build 7+ projects including Sales Analysis, Customer Segmentation, and Dashboards.
Is placement assistance provided?
Yes, we provide 100% placement assistance with 400+ hiring partners.

🚀 Ready to Start Your Data Analytics Journey?

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