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Data Analyst Full Course - Comprehensive Guide for 2024

Great Learning via YouTube

Overview

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Embark on a comprehensive 11-hour journey into the world of data analytics. Explore the role and skills of a Data Analyst, delving into key statistical concepts, SQL fundamentals, and Python programming. Master essential libraries like NumPy, Pandas, Matplotlib, and Seaborn for data manipulation and visualization. Learn to leverage Excel for data analysis, create impactful visuals with Tableau, and build machine learning models. Discover how to integrate Generative AI and ChatGPT to enhance your data analytics capabilities. Gain hands-on experience with real-world applications, including HR database management, salary expectation analysis, credit card fraud detection, and diabetes prediction. Cover a wide range of topics from basic data cleaning to advanced clustering techniques and generative AI applications in data analysis. By the end of this extensive course, acquire the skills and knowledge necessary to kickstart or advance your career as a proficient Data Analyst in 2024 and beyond.

Syllabus

Introduction
Who is Data Analyst and their Key Roles
Real-world Applications
Introduction to Data Analytics
What is Statistics?
Inter-quartile Range
Box-plot - 5 number summary
Data cleaning using Excel
Functions in Excel
Types of Functions in Excel
Sort and Filter
Data Validation in Excel
Pivot Table in Excel
Data Visualization using Excel
SQL - Introduction and Installation
Data Types in SQL
Hands-on based on HR Database Management System
Python Numpy Array
Numpy Methods
Numpy Array Mathematics
Numpy Matrix
Numpy Save and Load
Pandas- Introduction
Pandas Series Object
Pandas- Changing Index
Pandas- Series object from Dictionary
Pandas- Dataframe in-built Function
Pandas- iloc and loc function
Pandas- Dropping Rows and Column
Matplotlib Library
Matplotlib Line Plot
Matplotlib- Barplot
Matplotlib- Scatter plot
Matplotlib Histogram
Seaborn Line plot
Seaborn Barplot
Seaborn Scatterplot
Seaborn Histogram/Distplot
Tableau- Introduction
Tableau Architecture
Tableau Dashboards
Regression and its Use cases
Types of Regression [Linear Regression and Multiple Linear Regression]
Hands-on Linear Regression and MLR
Case study on Salary Expectation
Logistic Regression and its use cases
Credit card fraud detection using Logistic Regression
Naive Bayes Algorithm
Diabetes Prediction using Naive Bayes
Decision Tree
Decision Tree - CART
How are Decision Tree built?
Hands-on Decision Tree
Bagging and Random Forest
Hands-on Random Forest
Hierarchical Clustering
Types of Hierarchical Clustering
Agglomerative Hierarchical Clustering- Working
Distance formulas for Clustering [Eucledian Distance; Manhattan Distance; Minkowski Distance; Jaccard Similarity Coefficient]
Finding Optimal Numbers of Clustering
Generative AI- Introduction
Discriminative vs. Generative AI
How Gen AI Works?
Types of Generative AI
ChatGPT Basics
Introduction of Data Analysis using ChatGPT
Loading the Dataset
Data Analysis Project using ChatGPT
Data Analysis Project using Python
Summary

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