Equip students with foundational and advanced data analysis skills.
Provide practical knowledge and hands-on experience with tools like Excel, SQL, Power BI, Python, and Tableau.
Enable students to develop dashboards, perform data modeling, and visualize data effectively.
Prepare students for self-employment opportunities and enhance their career growth in data analysis.
Course Overview
This one-year part-time course is designed to provide students with comprehensive skills in data analysis, focusing on practical applications and self-employment opportunities. The course is divided into five modules, each covering essential tools and techniques in data analysis.
Course Teaching Methodology
Interactive Lectures: Theoretical understanding of concepts.
Hands-on Practice: Practical exercises and real-world projects.
Case Studies: Analysis of industry-specific data scenarios.
Assignments & Quizzes: Regular assessments to track progress.
Guest Lectures: Insights from industry experts.
Peer Discussions: Collaborative learning and problem-solving.
Importance for Learner
Career Growth: Equips students with in-demand skills for better job opportunities.
Self-Employment: Provides the knowledge needed to start a data analysis consultancy.
Practical Skills: Focuses on real-world applications to enhance employability.
Adaptability: Skills applicable across various industries and job roles.
Course Modules and Syllabus
Semester 1
Module 1: Excel for Data Analysis
Basics of Excel
Introduction to MS Excel
Beginner's Guide
Basic Functions of Excel
Data Validation in Excel
Data Connectors in Excel
Using Conditional Formatting
Cleaning Data in Excel
Basics of Formatting in Excel
Sorting and Filtering Data
Dealing with Null and Duplicate Values
Trimming Whitespace
Fixing Column Formats
Functions in Excel
Text Functions
IF, AND, and OR Functions
Date & Time Functions
COUNTIF, COUNTIFS, SUMIF, SUMIFS
Xlookup
Data Transformation in Excel
Power Query Basics
Cleaning and Transformation
Dealing with Text, Numerical, and Date Tools
Combining Files
Data Modeling in Excel
Importing Data in Power Pivot
Cardinality and Filter Direction
Creating Hierarchies
Visualization in Excel
Pivot Tables and Charts
Slicers and Buttons
Recorded Macros
Module 2: Advanced Excel and SQL Basics
Dashboards in Excel
Using ChatGPT for Excel
Creating Dashboards
Utilizing ChatGPT for Insights and Storytelling
SQL Basics
Introduction to Data, Databases, and SQL
Querying and Filtering Data
Conditional Expressions and Joining Tables
Aggregating Data and Subqueries
Window Functions
Data Visualization with Python
Semester 2
Module 2: Advanced SQL (continued)
Advanced SQL
Complex Joins, Stored Procedures, and Common Table Expressions
Using ChatGPT for SQL Queries
Module 3: Power BI for Data Analysis
Introduction to Power BI
Power BI Dashboard and Connectors
Table Transformations
Basic Transformations, Formatting, and Pivoting
Adding Conditional Columns
Data Modeling
Merge and Append Queries
Managing Data Relationships
AI Visuals in Power BI
Working with AI Visuals
DAX Functions
Introduction to DAX and Creating Calculated Columns
Understanding DAX Syntax and Functions
Dashboard Creation
Visualization Charts and Filtering Options
KPI Visuals and Custom Power
Module 4: Python for Data Analysis
Introduction to Python
Basics of Programming, Interpreter, and Installation
Writing and Running Python Code
Python Variables, Data Types, and Operators
Variables, Data Types, User Input, and Operators
Control Statements and Loops
Conditional Statements and Types of Loops
Python Data Structures
Strings, Lists, Sets, Tuples, and Dictionaries
Functions and Methods for Each Data Structure
Module 5: Tableau
Introduction to Tableau
BI Concepts and Tableau Overview
File Types and Extensions
Tableau Products and Data Connections
Desktop, Server, Publisher, Public, Reader
Data Connections and Types of Joins
Data Blending and Extract Creation
Tableau Charts
Various Chart Types (Area, Bar, Bubble, etc.)
Tableau Dashboards
Creating and Formatting Dashboards
Device Preview and Dashboard Filters
Calculations in Tableau
String, Date, Arithmetic, Aggregation, and Custom Calculations
Organizing and Simplifying Data
Filters, Sorting, Grouping, Sets, Hierarchies, Bins, and Parameters
Creating Cross Tabs and Dual Axis Visuals
Customization Based on Learner or Location
The course content can be adapted to meet specific requirements based on the learner's background, local industry demands, and career goals. Practical projects and case studies can be tailored to reflect regional business contexts and opportunities.
Course Title: Data Analyst
Course Duration: 1 Year (Part-Time)
Course Objectives
Equip students with foundational and advanced data analysis skills.
Provide practical knowledge and hands-on experience with tools like Excel, SQL, Power BI, Python, and Tableau.
Enable students to develop dashboards, perform data modeling, and visualize data effectively.
Prepare students for self-employment opportunities and enhance their career growth in data analysis.
Course Overview
This one-year part-time course is designed to provide students with comprehensive skills in data analysis, focusing on practical applications and self-employment opportunities. The course is divided into five modules, each covering essential tools and techniques in data analysis.
Course Teaching Methodology
Interactive Lectures: Theoretical understanding of concepts.
Hands-on Practice: Practical exercises and real-world projects.
Case Studies: Analysis of industry-specific data scenarios.
Assignments & Quizzes: Regular assessments to track progress.
Guest Lectures: Insights from industry experts.
Peer Discussions: Collaborative learning and problem-solving.
Importance for Learner
Career Growth: Equips students with in-demand skills for better job opportunities.
Self-Employment: Provides the knowledge needed to start a data analysis consultancy.
Practical Skills: Focuses on real-world applications to enhance employability.
Adaptability: Skills applicable across various industries and job roles.
Course Modules and Syllabus
Semester 1
Module 1: Excel for Data Analysis
Basics of Excel
Introduction to MS Excel
Beginner's Guide
Basic Functions of Excel
Data Validation in Excel
Data Connectors in Excel
Using Conditional Formatting
Cleaning Data in Excel
Basics of Formatting in Excel
Sorting and Filtering Data
Dealing with Null and Duplicate Values
Trimming Whitespace
Fixing Column Formats
Functions in Excel
Text Functions
IF, AND, and OR Functions
Date & Time Functions
COUNTIF, COUNTIFS, SUMIF, SUMIFS
Xlookup
Data Transformation in Excel
Power Query Basics
Cleaning and Transformation
Dealing with Text, Numerical, and Date Tools
Combining Files
Data Modeling in Excel
Importing Data in Power Pivot
Cardinality and Filter Direction
Creating Hierarchies
Visualization in Excel
Pivot Tables and Charts
Slicers and Buttons
Recorded Macros
Module 2: Advanced Excel and SQL Basics
Dashboards in Excel
Using ChatGPT for Excel
Creating Dashboards
Utilizing ChatGPT for Insights and Storytelling
SQL Basics
Introduction to Data, Databases, and SQL
Querying and Filtering Data
Conditional Expressions and Joining Tables
Aggregating Data and Subqueries
Window Functions
Data Visualization with Python
Semester 2
Module 2: Advanced SQL (continued)
Advanced SQL
Complex Joins, Stored Procedures, and Common Table Expressions
Using ChatGPT for SQL Queries
Module 3: Power BI for Data Analysis
Introduction to Power BI
Power BI Dashboard and Connectors
Table Transformations
Basic Transformations, Formatting, and Pivoting
Adding Conditional Columns
Data Modeling
Merge and Append Queries
Managing Data Relationships
AI Visuals in Power BI
Working with AI Visuals
DAX Functions
Introduction to DAX and Creating Calculated Columns
Understanding DAX Syntax and Functions
Dashboard Creation
Visualization Charts and Filtering Options
KPI Visuals and Custom Power
Module 4: Python for Data Analysis
Introduction to Python
Basics of Programming, Interpreter, and Installation
Writing and Running Python Code
Python Variables, Data Types, and Operators
Variables, Data Types, User Input, and Operators
Control Statements and Loops
Conditional Statements and Types of Loops
Python Data Structures
Strings, Lists, Sets, Tuples, and Dictionaries
Functions and Methods for Each Data Structure
Module 5: Tableau
Introduction to Tableau
BI Concepts and Tableau Overview
File Types and Extensions
Tableau Products and Data Connections
Desktop, Server, Publisher, Public, Reader
Data Connections and Types of Joins
Data Blending and Extract Creation
Tableau Charts
Various Chart Types (Area, Bar, Bubble, etc.)
Tableau Dashboards
Creating and Formatting Dashboards
Device Preview and Dashboard Filters
Calculations in Tableau
String, Date, Arithmetic, Aggregation, and Custom Calculations
Organizing and Simplifying Data
Filters, Sorting, Grouping, Sets, Hierarchies, Bins, and Parameters
Creating Cross Tabs and Dual Axis Visuals
Customization Based on Learner or Location
The course content can be adapted to meet specific requirements based on the learner's background, local industry demands, and career goals. Practical projects and case studies can be tailored to reflect regional business contexts and opportunities.
