Basics of Python programming

Data structures and libraries (NumPy, Pandas)

Data Cleaning and Preprocessing

Introduction to Data Cleaning and Data Types

Exploring and Visualization the missing values

Advanced-Data Cleaning Concepts

Introduction to Feature Engineering

Feature Extraction and Transformation

Feature Selection and Dimensionality Reduction

Data imputation techniques

Data visualization with Matplotlib and Seaborn

EDA techniques and best practices

Introduction to SQL and MySQL

Data Creation and Retrieval

Data Filtering

Data Analysis using aggregate functions and group by

Joins and Keys

MySQL Joins

Subqueries and Views

Window/Analytical Functions

Entering and formatting data

Data validation and cleaning

Essential functions for data analysis (SUM, AVERAGE, COUNT, etc.)

Data Manipulation in Excel

Sorting and Filtering Data:

Sorting data in Excel

Using filters for data analysis

Data Tables and PivotTables:

Creating and utilizing data tables

Introduction to PivotTables for data summarization

Data Consolidation and Linking:

Consolidating data from multiple sheets

Linking data between sheets

Advanced Functions (VLOOKUP, HLOOKUP, INDEX-MATCH):

Summarizing and Forecasting

Macros and Dashboarding

Introduction to Tableau and Power BI

Navigating the interface

Importing data

Visualizing Data in Tableau and Power BI

Creating different chart types

Using filters and sorting

Combining visualizations into dashboards

Advanced Features in Tableau and Power BI

Using calculations and parameters

Building interactive visualizations

Integrating with other data sources

Regression Analysis

Linear regression

Multiple regression

Classification Algorithms

Logistic regression

Decision trees and random forests

Clustering Algorithms

K-Means clustering

Hierarchical clustering

Time Series Analysis

Time series concepts

Forecasting techniques

Introduction to Natural Language Processing (NLP)

Text processing

Sentiment analysis