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Learn the essentials of Data Analytics with our 11-hour course. This video covers the role and skills of a Data Analyst and its importance. It includes key statistics, SQL, and Python concepts, using libraries like NumPy, Pandas, Matplotlib, and Seaborn. You’ll also see how to use Excel for data analysis, create visuals with Tableau, and build machine-learning models. Additionally, the video shows how Generative AI and ChatGPT can enhance data analytics.
Learn Data Analytics using Excel, understand the key phases of a Data Analytics project, Data Cleaning, and explore essential Excel functions that support your data analytics journey. www.mygreatlearning.com/academy/learn-for-free/courses/data-analytics-using-excel?CPV_YT&Desc&DtAnlystFllCrsin11hrs_2024
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🏁 Topics Covered:
00:00:00 Introduction
00:01:39 Who is Data Analyst and their Key Roles
00:06:36 Real-world Applications
00:07:21 Introduction to Data Analytics
00:07:55 What is Statistics?
00:24:24 Inter-quartile Range
00:30:48 Box-plot - 5 number summary
00:37:49 Data cleaning using Excel
00:43:00 Functions in Excel
00:45:05 Types of Functions in Excel
00:55:16 Sort and Filter
01:01:05 Data Validation in Excel
01:09:52 Pivot Table in Excel
01:19:56 Data Visualization using Excel
01:35:57 SQL - Introduction and Installation
01:38:14 Data Types in SQL
1:41:06 Hands-on based on HR Database Management System
2:37:02 Python Numpy Array
2:43:36 Numpy Methods
2:57:28 Numpy Array Mathematics
3:04:54 Numpy Matrix
3:11:25 Numpy Save and Load
3:13:23 Pandas- Introduction
3:13:54 Pandas Series Object
3:16:08 Pandas- Changing Index
3:17:25 Pandas- Series object from Dictionary
3:27:14 Pandas- Dataframe in-built Function
3:30:00 Pandas- iloc and loc function
3:33:42 Pandas- Dropping Rows and Column
3:37:39 Matplotlib Library
3:37:51 Matplotlib Line Plot
3:51:55 Matplotlib- Barplot
3:58:18 Matplotlib- Scatter plot
4:06:11 Matplotlib Histogram
4:12:54 Seaborn Line plot
4:21:17 Seaborn Barplot
4:29:01 Seaborn Scatterplot
4:34:16 Seaborn Histogram/Distplot
4:41:30 Tableau- Introduction
4:47:37 Tableau Architecture
4:49:10 Tableau Dashboards
5:05:41 Regression and its Use cases
5:08:30 Types of Regression [Linear Regression and Multiple Linear Regression]
5:18:20 Hands-on Linear Regression and MLR
5:37:43 Case study on Salary Expectation
6:11:35 Logistic Regression and its use cases
6:17:38 Credit card fraud detection using Logistic Regression
6:53:01 Naive Bayes Algorithm
7:02:16 Diabetes Prediction using Naive Bayes
7:28:03 Decision Tree
7:31:16 Decision Tree - CART
7:35:27 How are Decision Tree built?
7:42:04 Hands-on Decision Tree
8:14:49 Bagging and Random Forest
8:19:40 Hands-on Random Forest
9:07:56 Hierarchical Clustering
9:20:56 Types of Hierarchical Clustering
9:26:10 Agglomerative Hierarchical Clustering- Working
9:34:52 Distance formulas for Clustering [Eucledian Distance; Manhattan Distance; Minkowski Distance; Jaccard Similarity Coefficient]
9:50:37 Finding Optimal Numbers of Clustering
9:54:44 Generative AI- Introduction
9:57:12 Discriminative vs. Generative AI
9:59:40 How Gen AI Works?
10:00:43 Types of Generative AI
10:01:26 ChatGPT Basics
10:02:06 Introduction of Data Analysis using ChatGPT
10:15:05 Loading the Dataset
10:24:15 Data Analysis Project using ChatGPT
11:26:09 Data Analysis Project using Python
11:37:28 Summary
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