Curriculum
14 Sections
142 Lessons
10 Weeks
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Module 1: Introduction to Data Analytics
8
1.1
What is Data Analytics?
1.2
Why Data Analytics is Important for Businesses
1.3
Role of a Data Analyst
1.4
Types of Data Analytics
1.5
Data Analytics vs Data Science
1.6
Data Analytics Career Roadmap
1.7
Industries Hiring Data Analysts
1.8
Course Overview and Learning Outcomes
Data Analytics Fundamentals
8
2.1
Data Types and Data Structures
2.2
Structured vs Unstructured Data
2.3
Data Collection Methods
2.4
Data Cleaning Concepts
2.5
Data Transformation Basics
2.6
Data Visualization Fundamentals
2.7
Business Analytics Concepts
2.8
Analytics Lifecycle
Microsoft Excel for Data Analytics
14
3.1
Introduction to Excel
3.2
Excel Interface and Navigation
3.3
Data Entry and Formatting
3.4
Sorting and Filtering Data
3.5
Conditional Formatting
3.6
Data Validation
3.7
Text Functions
3.8
Logical Functions
3.9
Date and Time Functions
3.10
Lookup Functions
3.11
Pivot Tables
3.12
Pivot Charts
3.13
Dashboard Creation in Excel
3.14
Excel Data Analytics Project
Advanced Excel for Data Analysis
10
4.1
Advanced Formulas
4.2
INDEX and MATCH
4.3
Advanced Data Validation
4.4
Dynamic Reports
4.5
Power Query Introduction
4.6
Data Cleaning with Power Query
4.7
Excel Automation Basics
4.8
Advanced Dashboard Design
4.9
KPI Reporting
4.10
Business Reporting Project
SQL for Data Analytics
18
5.1
Introduction to SQL
5.2
Database Fundamentals
5.3
Installing MySQL
5.4
Creating Databases
5.5
Creating Tables
5.6
SQL Data Types
5.7
Insert, Update and Delete
5.8
SELECT Statement
5.9
Filtering Data
5.10
Sorting Records
5.11
Aggregate Functions
5.12
GROUP BY and HAVING
5.13
Joins in SQL
5.14
Subqueries
5.15
Views
5.16
Stored Procedures
5.17
SQL Optimization Basics
5.18
SQL Analytics Project
Advanced SQL for Business Analytics
8
6.1
Window Functions
6.2
Common Table Expressions
6.3
Ranking Functions
6.4
Data Warehousing Basics
6.5
ETL Concepts
6.6
Real World SQL Analytics
6.7
Sales Analysis Project
6.8
Customer Analytics Project
Python Programming for Data Analytics
14
7.1
Introduction to Python
7.2
Installing Python and Jupyter Notebook
7.3
Variables and Data Types
7.4
Operators
7.5
Conditional Statements
7.6
Loops
7.7
Functions
7.8
Lists
7.9
Tuples
7.10
Dictionaries
7.11
Sets
7.12
Modules and Packages
7.13
File Handling
7.14
Exception Handling
Python Libraries for Data Analytics
10
8.1
NumPy Fundamentals
8.2
Pandas Basics
8.3
DataFrames
8.4
Data Cleaning with Pandas
8.5
Data Transformation
8.6
Exploratory Data Analysis
8.7
Matplotlib Visualization
8.8
Seaborn Visualization
8.9
Statistical Analysis
8.10
Python Data Analytics Project
Statistics for Data Analytics
9
9.1
Introduction to Statistics
9.2
Mean Median Mode
9.3
Probability Concepts
9.4
Standard Deviation
9.5
Variance
9.6
Correlation
9.7
Regression Basics
9.8
Business Statistics
9.9
Statistical Analysis Project
Power BI Fundamentals
10
10.1
Introduction to Power BI
10.2
Installing Power BI Desktop
10.3
Connecting Data Sources
10.4
Data Transformation
10.5
Data Modeling
10.6
Relationships
10.7
Power Query
10.8
Basic Visualizations
10.9
Interactive Reports
10.10
Power BI Dashboard Project
Advanced Power BI
10
11.1
DAX Fundamentals
11.2
Calculated Columns
11.3
Measures
11.4
Time Intelligence
11.5
Advanced DAX
11.6
KPI Dashboards
11.7
Business Intelligence Reporting
11.8
Publishing Reports
11.9
Power BI Service
11.10
Advanced Dashboard Project
Real-World Data Analytics Projects
8
12.1
Retail Sales Analytics Project
12.2
Customer Segmentation Project
12.3
HR Analytics Project
12.4
Marketing Analytics Project
12.5
Finance Analytics Project
12.6
Healthcare Analytics Project
12.7
E-Commerce Analytics Project
12.8
Capstone Data Analytics Project
AI Tools for Data Analysts
7
13.1
Introduction to AI in Analytics
13.2
ChatGPT for Data Analysis
13.3
Microsoft Copilot
13.4
AI Powered Reporting
13.5
Prompt Engineering for Analysts
13.6
Automating Analytics Tasks
13.7
AI Analytics Project
Career Preparation & Placement Support
8
14.1
Resume Building for Data Analysts
14.2
LinkedIn Optimization
14.3
Git & GitHub for Data Analysts
14.4
Portfolio Development
14.5
Mock Interviews
14.6
Data Analytics Interview Questions
14.7
Case Study Interviews
14.8
Internship Preparation
Data Analytics Course with Python, SQL, Excel & Power BI
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