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Data Analyst Course Analytics

Batch Name

CDA

Course Start

1-March-2026

Course duration

90 Hours

Eligibility

12th

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Data Analyst Course Analytics

Data Analyst Course: Analytics Tools and Techniques

Introduction

This 3-month data analyst course is designed to provide learners with a strong foundation in modern data analytics. Whether you choose to study online or offline, this course will help you explore the full data lifecycle — from data collection methods to visual reporting and machine learning basics.

With a focus on practical learning, industry-standard Analytics Tools, and hands-on projects, you’ll gain the skills needed for high-demand data analyst jobs. The course also prepares you for recognized data analytics certification opportunities, making you job-ready in just three months.

Module-1

Course Papers

  • Foundations of Data Analytics
Course Syllabus

  • What is Data Analytics
  • Why is Data Analytics Important
  • Types of Data Analytics
  • The Role of a Data Analyst
  • Tools Used by Data Analysts
  • Real-Life Applications of Data Analytics
  • Career Path & Opportunities for Data Analysts

  • Introduction to Data
  • Types of Data
  • Sources of Data
  • Data Collection Techniques

  • Overview of Data Analysis Tools
  • Excel for Data Analysis
  • SQL for Managing Databases
  • Python for Data Analysis (Intro level)
  • Tableau and Power BI for Data Visualization (Basics only)

  • Introduction to Data Cleaning
  • Importance of Data Cleaning
  • Common Data Issues and Their Solutions
  • Steps in Data Cleaning Process
  • Tools for Data Cleaning (Excel, Python basic libraries)
  • Best Practices for Data Cleaning

  • What is Exploratory Data Analysis (EDA)
  • Importance of EDA in Data Analysis
  • Key Steps in Exploratory Data Analysis
  • Tools for Performing EDA (Excel, Python – pandas/matplotlib overview)
  • Best Practices for EDAa

  • Introduction to Data Visualization
  • Importance of Data Visualization
  • Types of Data Visualizations (Bar, Pie, Line, Scatter)
  • Tools for Data Visualization (Excel, Power BI basics)
  • Best Practices for Data Visualization

  • Introduction to Data Preparation
  • Importance of Data Preparation
  • Steps in Data Preparation (Data structuring, missing value handling, formatting)

  • Introduction to Statistics in Data Analysis
  • Descriptive Statistics (Mean, Median, Mode, Standard Deviation)
  • Inferential Statistics (Sampling, Basic Probability)
  • Hypothesis Testing (Conceptual intro)
  • Correlation and Regression (Basic overview)
Module-2

Course Papers

  • Data Analysis & Machine Learning
Course Syllabus

  • Introduction to Data Analysis Techniques
  • Descriptive Analysis
  • Diagnostic Analysis (Simple real-life example)
  • Predictive Analysis (Regression overview)

  • Introduction to Data Reporting and Visualization
  • Types of Data Reports
  • Data Visualization Techniques (As per real-world dashboards)
  • Tools for Data Reporting (Excel, Power BI)
  • Best Practices for Data Reporting and Visualization
  • Example Use Case: Data Reporting in Retail (Summarized case only)

  • What is Machine Learning
  • Types of Machine Learning
  • Common ML Algorithms (Linear Regression, Decision Tree – conceptual only)
  • Steps to Perform Machine Learning (High-level workflow)
  • Real-world Applications (Retail, Healthcare – examples only)

  • Exercise: Data Cleaning and Preparation
  • Exercise: Descriptive Statistics
  • Exercise: Data Visualization (Excel or Tableau)
  • Exercise: Predictive Analysis Using ML (Demo model only)
  • Exercise: Real-world Problem Solving (Mini project)
  • Exercise: Building Dashboards
  • Exercise: Ethical and Legal Compliance Checklist (brief intro only)
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Why Choose This Course?

Whether you're switching careers or upskilling, this course offers a practical and industry-ready roadmap to become a professional data analyst. You'll gain hands-on exposure to popular big data tools and learn how analytical big data can drive decision-making in real-world scenarios. With access to both offline training and online data analyst course formats, flexibility meets quality education.

What Will You Learn?

  • Data collection methods and tools
  • Big data analytics and visualization using Power BI and Tableau
  • Basics of Hadoop and big data types
  • Descriptive and predictive analytics
  • Introductory machine learning and deep learning concepts
  • Building dashboards and analytical reports


Opportunities After This Course

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


You’ll be prepared to work in industries such as finance, healthcare, retail, and e-commerce, or pursue freelance and internship opportunities in data analysis and reporting.

Who Can Enroll?

  • Fresh graduates and final-year students
  • Professionals looking to shift to data roles
  • Anyone searching for a data analyst course near me
  • IT and business background learners interested in analytics


Enroll Now

Enroll in our 3-month data analyst course today and step confidently into a world of insights, analytics, and decision-making. Available both online and offline, this program offers everything you need to become industry-ready.

👉 Start your journey in data analytics—Enroll Now!