• Overview of Data Science 🌐
• Key Roles & Responsibilities 🧑‍💼
• Essential Tools & Technologies 🛠️.
• Career Path in Data Science Fields 🤑
• Roles in Data Science Field.

Module 1: Exploring Data 🔍📊

• Welcome to Excel: An Overview of the World’s Most Popular Spreadsheet Software 🖥️📈
• Excel Beyond Limits 🚀📊
• Mastering the Basics of Spreadsheet Navigation 🧭📋
• Working on Rows and Columns 📏🔢
• Looking for Exact Matches 🔍✔️
• Trimming Function and Its Usage ✂️📉
• Sorting the Data 🔢🔄
• Nesting Functions 🏗️🔧
• Data Types in Excel 📊🔠
• Type Conversion in Excel 🔄🔢

Module 2: Preparing Data 🛠️📋

• Mastering Text Functions in Excel: CONCATENATE, UPPER, LOWER, and PROPER ✍️🔤
• Mastering Text Extraction in Excel: LEFT, RIGHT, and SUBSTITUTE Functions ✂️🔍
• Mastering Excel’s DATE Function: Effective Techniques for Date Handling 📅🛠️
• Excel DATEDIF Function (Between Two Dates) 📅↔️📅
• How To Use Relative & Absolute Cell References in Excel 🔄🔒
• Harnessing the Power of VLOOKUP for In-depth Insights 🔍🔎
• Unleashing the Power of SUMIF Function in Excel 🔍➕

Module 3: Analyzing the Data 📈🔍

• Mastering the COUNT, COUNTA, and COUNTBLANK Functions 🧮🔢📊
• Unleashing the Power of COUNTIF Function in Excel 📊🔍
• Using Excel’s Core Calculation Functions: A Practical Guide 📈🛠️
• Excel Logic Functions Explained: IF, AND, and OR in Practice 🤔🔄
• Organizing Data with UNIQUE and SORT Functions 🗂️🔄

Module 1: SQL Fundamentals 📚💻

• SQL Installation & Setup 🛠️🔧
• Types of SQL Commands 📜🗂️
• DDL Commands for Database and Tables 🏗️📋
• SQL Constraints 🚫📊

Module 2: Data Manipulation with SQL (DML) ✏️🔄

• Modifying Data in Tables ✍️📋
• Retrieving Data with SQL 🔍📊

Module 3: Intermediate SQL Queries 🔍📈

• Selecting Columns 📋🔢
• Filtering Rows 🔍🗂️
• Aggregate Functions 📊➕
• Sorting & Grouping 🔢📊
• Null Values ❓📉
• Date and Time Functions 📅⏰
• Working with Expressions 🧮🔢
• Order of Execution of SQL Commands 🔄🗂️

Module 4: Joining & Combining Data 🔗🔄

• Types of Joins 🔍🔗
• Left & Right Join ⬅️➡️
• Inner Join and Full Join 🔄🔁
• Cross Join and Self Join 🔄👤
• Understanding Table Relationships 🗂️🔗

Module 5: Data Preprocessing & Analysis 🔧📊

• Handling Missing Values ❓📉
• Handling Duplicates 🔄🚫
• Data Transformation 🔄🛠️
• Working with Dates and Times 📅⏳
• Data Filtering and Selection 🔍📋
• Analyzing Time Series Data 📈⏳
• Performance Optimization ⚡🔧
• Working with JSON and XML Data 📄🔢
• Data Blending 🥤🔄

Module 6: Advanced SQL 🚀📊

• SQL Views 👁️📋
• Triggers 🚨🔄
• Performance Tuning ⚙️🚀
• Backup and Recovery 💾🔄
• Advanced Joins 🔗🔍
• Dynamic SQL 🌀🔢
• Materialized Views 🗂️🔍
• Database Administration Tasks 🛠️📋

Module 7: Window Functions in SQL 🪟🔢

• Introduction to Window Functions 📚🪟
• Analytical Functions 🔍📈
• Aggregating Data Using Window Functions 📊🔢
• Partitioning Data and Applying Window Functions 📋🔄

Module 1: Data Preprocessing with Google Play Store 📱🔧

• Introduction to EDA 📊🔍
• Data Cleaning 🧹🗃️
• Data Visualization 📈🎨
• Data Analysis 🔍📉

Module 2: Advanced Data Preprocessing with Google Play Store 📱🔍

• Data Preprocessing – Removing Null Value Rows 🚫📋
• Data Analysis – Numeric 🔢📊
• Data Analysis – Categorical 🗂️🔍
• Data Analysis – Automatic Categorical 🤖🗂️
• Null Values Handling – Numeric 🔢❓
• Null Values Handling – Categorical 🗂️❓
• Null Values Handling Overall 🗃️❓

Module 3: Introduction to EDA 📊🔍

• Introduction to EDA 📚🔎
• Understanding Your Data 🤔📈

Module 4: Data Cleaning 🧹🔧

• Dealing with Missing Values ❓🔍
• Dealing with Duplicate Data 🔄🚫
• Outliers 🚨📊
• Outlier Removal Using Z-Score 🔢📉
• Outlier Removal Using IQR 📏🔄
• Outlier Removal Using Percentile 📈🔢
• Correction of Data Type 🔄📊

Module 5: Data Visualization 📊🎨

• Univariate Analysis (Non-Graphical) 📋🔍
• Univariate Visualizations (Categorical) 🗂️📈
• Univariate Visualizations (Numerical) 🔢📉
• Bivariate Analysis (Numerical-Categorical) 🔢🗂️
• Bivariate Visualizations (Categorical) 🗂️🔍
• Bivariate Visualization (Numerical) 🔢🔍

Module 6: Data Analysis 🔍📊

• Data Analysis with Multiple Columns 📊🔢
• Data Analysis Using Conditions 🔄🔍
• GroupBy in Pandas 📊🔗

📘 Section 1: Power BI – Introduction & Setup

• 🧠 What is Business Intelligence?
• 📊 What is Power BI and Why Power BI in Data Analysis
• 🛠️ Power BI Components
• ✅ Practical Applications
• ⬇️ Downloading Power BI & Adjusting Settings
• 👍 Advantages of Power BI, 👎 Disadvantages of Power BI
• 🔌 Types of Data Connectors in Power BI Desktop
• 🔄 Differences Between Microsoft Power BI and SSRS
• 💰 Power BI Free vs Power BI Pro vs Power BI Premium

📐 Section 2: Power BI – Query Editor

• ✏️ Edit Power BI App
• 🔄 Query Editor in Power BI for Data Transformation
• 🔢 Working with Numbers in Power BI
• 🕒 Working with Date & Time Tools
• 📆 Creating a Rolling Calendar in Power BI
• 🎛️ Conditional Columns in Power BI
• 📚 Grouping & Aggregating Records
• 🔗 Merge and Append Queries in Power BI
• 🔒 Manage Data Source Settings and Permissions
• 🔄 Data Refresh in Power BI
• 🏷️ Power BI Data Types
• 🌲 Explain Power BI Hierarchy, and How to Use it
• 🔗 Power BI – Excel Integration

📊 Section 3: Power BI Dashboard and Visualization

• 🖥️ Power BI – Dashboard
• 🎯 Power BI – Dashboard Actions
• 🎨 Adding Objects to the Power BI Report Canvas and Exploring the “Report” View
• 🔗 Creating Table Relationships & Data Models in Power BI
• 📈 Inserting Basic Charts & Visuals in Power BI
• 🎨 Conditional Formatting
• 📊 How to Add Reports to Dashboards
• 🎛️ Power BI Report Formatting Options
• 🔍 Power BI Report Filtering Options
• 📋 Exploring Data with Matrix Visuals
• 📅 Filtering with Date Slicers
• 📈 Adding Trend Lines & Forecasts
• ✏️ Editing Power BI Report Interactions
• 🔍 Adding Drillthrough Filters
• 📝 Inserting Text Cards
• 🖌️ How to Format a Card?
• 📋 Format Multi-Row Card
• 🗺️ Visualizing Geospatial Data with Maps
• 🎨 How to Format Maps
• 🌳 Visualizing Data with Treemaps
• 🎨 Format Tree Map
• 👥 Managing & Viewing Roles in Power BI Desktop
• 📋 Creating a Simple Table
• 🎨 Power BI – Format Table Chart
• 📊 Create a Stacked Column Chart
• 🎨 Power BI – Format Stacked Column Chart
• 📊 Create a 100% Stacked Column Chart
• 🎨 Format 100% Stacked Bar Chart
• 📊 Create a Stacked Bar Chart
• 🎨 Power BI – Format Stacked Bar Chart
• 📈 How to Create a Stacked Area Chart
• 🎨 Power BI – Format Area Chart
• 🧭 Create a Radial Gauge Chart
• ⭐ Create Key Performance Indicators (KPIs) Chart
• 🎨 Power BI – Format KPIs Chart
• 📊 Format Clustered Bar Chart
• 🎨 Power BI – Format Clustered Bar Chart
• 🌊 How to Create a Waterfall Chart?
• 🎨 Format Waterfall Chart
• 🗺️ Create a Filled Map
• 🎨 Format Filled Map
• 📈 Create a Scatter Chart
• 🎨 Format Scatter Chart
• 📉 Showing Trends with Line Charts
• 🎨 Power BI – Format Line Chart
• 🗺️ How to Create a Shape Map?
• 🍩 Format Donut Chart
• 🥧 Format Pie Chart
• 🎀 Format Ribbon Chart
• 🔣 Create an R Script Visual
• 📊 Line and Stacked Column Chart
• 🎨 Format Line and Clustered Column Chart

🧮 Section 4: DAX Introduction

• 📊 Data Analysis Expressions (DAX)
• ✏️ Intro to DAX Calculated Columns
• 🔢 Creating Measures Using DAX
• ➕ Adding Columns & DAX Measures in Power BI Desktop
• 🔍 Filter Context in Power BI
• 📚 Common DAX Function Categories
• 🕒 Basic Date & Time Functions
• 🔄 DAX Window Function
• 🔀 Conditional & Logical Functions
• 🏷️ DAX Information Functions
• 📝 DAX Text Functions
• 🔢 Index Function in Power BI
• ➗ DAX Trigonometric Functions
• 📅 DAX COUPDAY Financial Function
• 💰 DAX Depreciation Functions
• 🧮 Power BI – Distinct() Function
• ➕ Basic Math in Power BI
• 🔢 Power BI – DAX Trigonometric Functions
• 🔢 COUNT Functions
• 📅 Power BI – DAX Date Functions
• 📊 DAX Aggregate Functions in Power BI
• 📝 Power BI – DAX TEXT Functions
• 💰 Power BI – DAX Depreciation Functions
• 🔣 Power BI – DAX Bitwise Functions

🔗 Section 5: Creating Table Relationships & Data Models in Power BI

• 📋 What is a “Data Model”?
• 📚 Principles of Database Normalization
• 📄 Understanding Data Tables vs. Lookup Tables
• 🔗 Understanding Table Relationships vs. Merged Tables
• 🔄 Creating Table Relationships in Power BI Desktop
• ✏️ Managing & Editing Table Relationships | Power BI
• 🔄 Managing Active vs. Inactive Relationships | Power BI
• 🔗 Connecting Multiple Data Tables in Power BI
• 🔍 Understanding Filters in Power BI
• 🔒 Hiding Tables, Columns, and Fields from Power Pivot

Module 1: Getting Started with Streamlit 🚀🖥️

• Introduction to Streamlit 📚🔍
• Streamlit Setup 🛠️📥
• Basic Output Tags 🏷️📝
• Inspecting the Website 🔍🌐
• Text Input 📝🔠
• Special Input with Buttons 🔘✨
• Forms 📝📋
• Integrating Scripts 🔗📜

Module 2: Page Beautification 🎨🖼️

• Working with Columns 📊🗂️
• Working with Tabs 📑🔄
• Expander & Empty Functionalities 🔽📂
• Advanced Display & Progress Options 📈🔧
• Echo and Stop Commands 🔄⏹️

Module 3: Working with Data 📊🔗

• Working with Media Files 🎥📁
• DataFrames with Streamlit 🗃️📊
• File Uploading ⬆️📂
• Image Converter 🖼️🔄
• Image Rotation 🔄🖼️

Module 4: Introduction to Data Visualization 📈🔍

• Getting Started with Basic Plots with Streamlit 📊🔧
• Plots with Matplotlib and Seaborn 📉🎨
• Visualization with Plotly 📊🔍

Module 5: Deployment 🚀🌐

• Deployment on Streamlit Server 🌐🖥️

Introduction to Statistics 📊🔍

• What is Statistics? ❓📚
• Importance of Statistics 📈🔍
• Applications of Statistics 🏥📉
• Statistical Methods Overview 📋🛠️

Data and Their Types 📊🔢

• Types of Data 🗃️🔠
  • Quantitative Data 🔢📏
  • Qualitative Data 🗂️🔡
• Levels of Measurement 🎚️🔢
  • Nominal 🏷️
  • Ordinal 📈
  • Interval 📅
  • Ratio 🔢📏

Introduction to Descriptive Stats 📊📋

• What is Descriptive Statistics? 📈🔍
• Purpose of Descriptive Stats 🎯🔍
• Types of Descriptive Statistics 📊🔢

Measures of Frequency 📊🔢

• Frequency Distribution 📉📋
• Frequency Tables 📊🗂️
• Histograms 📈🔢
• Frequency Polygons 📉🔗

Measures of Central Tendency 🧮📈

• Mean ➗🔢
• Median 📍🔢
• Mode 🔁🔢
• Comparing Measures of Central Tendency 🔄📈

Measures of Dispersion 📏📊

• Range 🏆🔢
• Variance 📈🔢
• Standard Deviation 📊🔢
• Interquartile Range (IQR) 📉🔢

Measures of Shape 📏📊

• Skewness 🏞️🔢
• Kurtosis 🏔️🔢
• Symmetry of Distribution 🔄📈

• Machine Learning Introduction 🤖📚
• Machine Learning Advanced 🚀📊
• Introduction to AI and Deep Learning 🤖🔍
• Natural Language Processing 🗣️🔍
• Generative AI 🧠🎨
• ChatGPT 🗨️🤖

• What is AI.
• What is Machine Learning?.
• Understanding Data and Terminology.
• Types of Learning
  Regression vs Classification.
• Subset Of AI

• Introduction – Neurons vs Artificial Neural Networks.
• Learning of ANN.
• How to Implement and Visualize a Perceptron in Artificial Neural Networks?

• Getting Started with NLTK and Tokenization.
• Stemming & Lemmatisation.
• StopWords Removal from Scratch.
• Corpus & Vocabulary
  Vocabulary with Keras