Data Analytics

Data Analytics

Master Data-Driven Decision Making

Our Data Analytics course is designed to equip you with the skills needed to turn raw data into actionable
insights. This hands-on course covers everything from data collection and cleaning to advanced data
visualization and predictive analytics using real-world tools and techniques.

Course Objectives-

Understand the complete data analysis lifecycle- Learn data cleaning, transformation, and visualization- Gain expertise in Excel, SQL, Python, Power BI, Tableau- Build machine learning models for predictive analytics- Prepare for top Data Analyst, BI Analyst, or Data Scientist roles

Module 1: Introduction to Data Analytics

  • What is Data Analytics?
  • Importance & Applications
  • Types of Data Analytics: Descriptive, Diagnostic,
    Predictive, Prescriptive
  • Career Paths in Data Analytics

Module 2: Excel for Data Analysis

  • Functions, Charts, Pivot Tables
  • Data Cleaning & Formatting
  • Conditional Formatting
  • Advanced Formulas & Macros

Module 3: SQL for Data Manipulation

  • Introduction to Databases & SQL
  • SELECT, JOIN, GROUP BY, HAVING Clauses
  • Subqueries & Nested Queries
  • Data Aggregation & Filtering
  • Hands-on with MySQL/PostgreSQL

Module 4: Python for Data Analytics

  • Python Basics (Variables, Loops, Functions)
  • NumPy & Pandas for Data Wrangling
  • Data Cleaning & Preprocessing
  • Data Visualization with Matplotlib & Seaborn
  • Introduction to Machine Learning with Scikit-learn

Module 5: Data Visualization Tools
Power BI

  • Data import & transformation
  • Creating dashboards & interactive reports
  • DAX formulas and KPIs

Tableau

  • Data connection and filtering
  • Building advanced charts and dashboards
  • Publishing to Tableau Public

Module 6: Statistics for Data Analysis

  • Descriptive Statistics
  • Probability & Distributions
  • Hypothesis Testing
  • Correlation & Regression

Module 7: Introduction to Machine Learning

  • Supervised vs. Unsupervised Learning
  • Regression, Classification Techniques
  • Model Evaluation & Tuning

Module 8: Capstone Projects & Portfolio

  • Real-time industry projects
  • Build dashboards, present insights
  • Portfolio development for job interviews

Tools & Technologies Covered

  • Microsoft Excel
  • SQL (MySQL / PostgreSQL)
  • Python (NumPy, Pandas, Matplotlib, Seaborn, Scikit-learn)
  • Power BI
  • Tableau
  • Google Sheets
  • Jupyter Notebook

Who Can Join?

  • Students & Freshers
  • Working professionals looking to switch to data roles
  • Business Analysts or Managers

Career Opportunities

  • Data Analyst
  • Business Intelligence Analyst
  • Junior Data Scientist
  • Reporting Analyst
  • Marketing Analyst