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Certificate in Data Analyst (CDA)

Data Analyst Course: Analytics Tools and TechniquesIntroductionThis 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 …

Duration 3 Months Mode Online / Offline Eligibility 12th CITC Certified Placement Support

Data Analyst Course Analytics (CDA)

Start Date 1 October 2026
Duration 3 Months
Mode Online / Offline
Certification CITC Certified
Batch / Course CDA
Enroll Now

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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.

Course Papers / Subjects

What you will study in this programme

01
Introduction to Data Analytics
02
Understanding Data Types and Data Sources
03
Tools and Technologies for Data Analysis
04
Data Cleaning and Preprocessing
05
Exploratory Data Analysis (EDA)
06
Data Visualization
07
Data Preparation for Analysis
08
Statistical Concepts for Data Analysis
09
Data Analysis Techniques
10
Data Reporting and Visualization
11
Machine Learning for Data Analysis
12
Practical Exercises in Data Analysis

Syllabus (Module-wise)

Expand each topic for details

Module 1

Course Papers

  • Foundations of Data Analytics

  • 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

  • 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)

What You Will Learn & Career Scope

Details from the course content

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!

Enroll Now

Frequently Asked Questions

Common questions about this course

A Data Analyst course teaches you how to collect, clean, analyze, and visualize data to generate useful insights.

Students, graduates, beginners, and professionals interested in data analysis and business intelligence can join.

No. Beginners can start with the basics and gradually develop practical data analysis skills.

You can learn Excel, SQL, data cleaning, data visualization, statistics, dashboards, and tools such as Power BI.

Depending on the course curriculum, you can learn Excel and SQL for organizing, querying, and analyzing data.

Yes. Practical projects can help you work with datasets and apply data analysis techniques to real-world scenarios.

Yes. The course can introduce concepts step by step, starting with basic data handling and progressing to analysis and visualization.

Yes. You can learn to create interactive dashboards and reports using appropriate data visualization tools.

You can explore roles such as Data Analyst, Junior Data Analyst, Reporting Analyst, or Business Intelligence Analyst.

Data Analytics helps you develop skills for understanding data, identifying patterns, and supporting data-driven business decisions.

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