Become expert in Data Science & Business Analytics Project Management
Data Analyst Course
The Data Analyst Course teaches you how to analyze and interpret data using various tools and techniques. It covers data visualization, statistical analysis, and problem-solving skills for real-world applications.
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Updated 11/2025
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Course Description
This online data analyst course will transform you into a data analytics expert. In this master’s course, you’ll learn the latest analytics tools and techniques, work with SQL, R, and Python, create impactful data visualizations, and apply statistics and predictive analytics to real business challenges.
1. Introduction to Data Analytics
4 Lectures
Overview of Data Analytics and Its Applications
Data Types, Sources, and Collection Methods
Data Analytics Process and Lifecycle
Tools and Technologies in Data Analytics
2. Excel for Data Analysis
4 Lectures
Introduction to Excel for Data Analysis
Data Cleaning and Preparation in Excel
Using Formulas and Functions for Analysis
Data Visualization with Charts and Pivot Tables
3. SQL for Data Analysts
4 Lectures
Introduction to SQL and Relational Databases
Basic Data Retrieval with SELECT Queries
Filtering, Sorting, and Aggregating Data
Joining Tables and Advanced Query Techniques
4. Python for Data Analysis
4 Lectures
Introduction to Python for Data Analysis
Working with Data Structures: Lists, Dictionaries, and DataFrames
Data Cleaning and Transformation with Pandas
Exploratory Data Analysis (EDA) with Python
5. Data Visualization and Business Intelligence (BI) Tools
4 Lectures
Introduction to Data Visualization and BI Concepts
Fundamentals of Dashboards and Reporting
Exploring BI Tools: Power BI, Tableau, and QlikView
Data Storytelling and Insight Communication
6. Statistics and Probability for Data Analytics
5 Lectures
Introduction to Statistics and Probability Concepts
Descriptive Statistics: Summarizing and Visualizing Data
Probability Distributions and Random Variables
Inferential Statistics: Sampling, Hypothesis Testing, and Confidence Intervals
Correlation, Regression, and Predictive Insights in Data Analytics
7. Data Cleaning and Preparation
4 Lectures
Introduction to Data Cleaning and Its Importance
Handling Missing, Duplicate, and Inconsistent Data
Data Transformation and Standardization Techniques
Feature Engineering and Data Enrichment
8. Exploratory Data Analysis (EDA)
4 Lectures
Introduction to Exploratory Data Analysis (EDA)
Understanding Data Distributions and Summary Statistics
Visualizing Data Patterns with Charts and Plots
Identifying Outliers, Trends, and Correlations
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Frequently Asked Questions
This course provides comprehensive knowledge with practical examples for
beginners and professionals.
No prior experience required. We start with basics and progress to
advanced topics.
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₹50,000
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