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Modern Data Analyst: SQL, Python & ChatGPT for Data Analysis

Modern Data Analyst: SQL, Python & ChatGPT for Data Analysis

Loại khoá học: Business Analytics & Intelligence

Data Analyst Course: SQL, Python, NumPy, Pandas, Data Visualization, Cleaning and ChatGPT

image
50.000 VND
1.149.000 VND
Đầy Đủ Bài Giảng
Học Online Tiện Lợi
Kích Hoạt Nhanh 2-5 Phút
Thanh toán tự động
Được phép tải xuống

Tổng quan

Nội dung khoá học

Đánh giá

Mô tả

Welcome to Modern Data Analyst. The role of the data analyst has evolved and now it’s not enough to know Excel to be a data analyst. In this course, we will learn how to use SQL, Python & ChatGPT for Data Analysis.

First, we'll learn SQL from scratch. SQL is a programming language that will help us work with data. We’ll use a free database for this course: MySQL. Here are some of the SQL concepts this course covers.

- Basic SQL commands and clauses (SELECT FROM, WHERE, INSERT, HAVING, UPDATE, etc)

- Aggregate functions with GROUP BY commands

- SQL Joins

- Logical operators

- Subqueries. temporary tables, rank, etc

- Projects, exercises, and more!

Then we’ll learn Python from zero. Python is used for data analysts to collect data, explore data, and make visualizations. Here's what the Python section covers.

- Python Crash Course: We'll learn all the Python core concepts such as variables, lists, dictionaries, and more.

- Python for Data Analysis: We'll learn Python libraries used for data analysis such as Pandas and Numpy. We'll use them to do data analysis tasks such as cleaning and preparing data.

- Python for Data Visualization: We'll learn how to make visualizations with Pandas.

Finally, we'll learn ChatGPT for data analysis. We’ll learn how to use ChatGPT’s code interpreter to analyze data, extract data from websites, automate Excel reports, and more.

What makes this course different from the others, and why you should enroll?

  • This is the most updated and complete data analysis course. 3-in-1 bundle (SQL, Python and ChatGPT)

  • You'll learn traditional tools as well as modern tools used in data analysis

  • We'll solve exercises and projects to put into practice the concepts learned

Join me now and become a data analyst.

Bạn sẽ học được gì

Learn SQL to create queries and work with databases

Learn Python to collect data, explore data and make visualizations

How to use ChatGPT for data analysis

Exercises and data analysis projects

Yêu cầu

  • Internet Access

Nội dung khoá học

18 sections

PART 1 - SQL

5 lectures
Welcome! (+ Resources for the course)
00:24
What is SQL MySQL?
02:06
What's a table?
01:10
What's a Primary Key?
02:35
What's a foreign key?
01:51

Installation MySQL

3 lectures
Section Overview
00:08
How to install MySQL on Windows
05:57
How to install MySQL on macOS
04:40

Data Types

2 lectures
Section Overview
00:08
Data Types
04:09

Commands

22 lectures
Section Overview
00:09
Part 1 - Creating a database and table
05:54
Part 2-Creating a database and table
17:01
Importing Data with MySQL
08:00
The SELECT Command
09:45
Insert
07:39
Min
08:24
Max
04:14
Group by
12:39
Where
11:22
Sum
06:56
Average
07:50
Count
07:32
And
05:10
Or .
06:40
In .
08:05
Like
08:26
Between
08:08
Order by
11:15
Having
10:44
Update + Set
05:48
Distinct
04:58

Functions

11 lectures
Section Overview
00:08
Left and Right
11:56
Length
06:43
Upper Lower
05:57
Repeat
02:26
Replace
08:20
Trim
08:22
Cast + Convert
05:40
Concat
06:13
Curdate, day, month
06:32
Date add
06:51

Other Important Concepts

6 lectures
Section Overview
00:04
Temporary Table
08:04
Joins
16:22
Subqueries
08:52
Case
07:56
Dense Rank
07:26

SQL Project

4 lectures
Section Overview
00:15
Part 1
23:56
Part 2
18:30
Part 3
26:54

PART 2 - Python

4 lectures
Installing Python and Jupyter Notebook through Anaconda
03:43
Jupyter Notebook Interface
10:00
Cell Types and Modes in Jupyter Notebook
07:35
Popular Keyboard Shortcuts in Jupyter Notebook
05:03

Python Basics

9 lectures
Hello World
03:48
Data Types
08:37
Variables
07:40
Lists
24:18
Dictionary
10:34
If Statement
06:12
For Loop
05:42
Function
07:08
Modules
03:40

Introduction to Pandas and Numpy

13 lectures
Introduction to Pandas
06:24
How to Create a Dataframe
16:23
How to show a dataframe: head(), tail() and pd.options.display
06:48
Basic Attributes, Functions and Methods
11:50
Selecting One Column from a Dataframe
05:53
Selecting Two or More Columns from a Dataframe
05:35
Add New Column to a Dataframe (Simple Assignment)
09:59
Add New Column to a Dataframe with assign() and insert()
06:41
Operations in dataframes
08:10
The value_counts() method
04:10
Sort a DataFrame with the sort_values() method
09:37
The set_index() and sort_index() methods
06:56
Rename Columns and Index with rename()
05:58

Filtering Data

8 lectures
Filter a Dataframe Based on 1 Condition
14:14
Creating a Conditional Column from 2 Choices: np.where()
10:29
Filter a Dataframe Based on 2 or More Conditions: &, |
12:07
Creating a Conditional Column from More Than 2 Choices: np.select()
12:51
The isin() Method
07:17
Find Duplicate Rows with the duplicated() method
17:55
Drop Duplicate Elements with the drop_duplicates() method
10:17
Get and Count Unique Values with the unique() and nunique() methods
03:54

Data Extraction

11 lectures
loc() vs iloc()
07:15
First Look at The Dataset: Setting Index and Selecting Columns
05:32
Selecting elements by index label with .loc()
20:20
Selecting elements by index position with .iloc()
13:02
Set New Value for a Cell In a Dataframe
09:47
Drop Rows or Columns from a DataFrame
09:36
Create Random Sample with the sample Method
07:44
Filter A DataFrame with the query method
12:29
The apply() method
06:09
Lambda function + apply() method
17:52
Make a Copy of a Dataframe with copy() (Deep Copy vs Shallow Copy)
07:18

Reshaping and Pivoting Dataframes

3 lectures
Introduction to Pivot Tables in Pandas
04:43
The pivot() method
06:05
The pivot_table() method
08:08

Visualizations in Python

8 lectures
First Look at The Dataset and Making Pivot Table
09:35
Lineplot
04:25
Barplot
07:45
Piechart
03:41
Boxplot
03:34
Histogram
01:29
ScatterPlot
04:44
Save Plot and Export Pivot Table
03:06

GroupBy and Aggregate Function

7 lectures
Dataset Overview
06:50
The agg() method
14:50
The Split-Apply-Combine Strategy
07:09
The GroupBy Method
13:43
The groupby() and agg() method
10:58
The groupby() and lambda function
09:46
The filter() method
07:37

Merging and Concatenating Dataframes

7 lectures
Intro dataset
05:38
Concatenate Vertically
12:04
Concatenate Horizontally
11:58
Inner Joins
09:21
Full Join and Exclusive Full Join
18:31
Left Join and Exclusive Left Join
24:11
Right Join and Exclusive Right Join
19:40

Data Cleaning

9 lectures
Dataset Overview
03:47
Identify Missing Data with the isnull() Method
10:28
Dealing with Missing Data: Remove a column or row with .drop, .dropna or .isnull
12:35
Dealing with Missing Data: Replace NaN by the mean, median, mode with .fillna()
14:06
Extracting data with split() and extract() and changing data type with astype()
15:44
How Identify and Deal with Outliers
17:26
Dealing with inconsistent capitalization with lower(), upper(), title()
04:52
Remove blank spaces with strip(), lstrip(), and rstrip()
04:41
Replace strings with replace() or sub()
08:14

PART 3 - ChatGPT

10 lectures
ChatGPT for Coding - First Look
10:58
ChatGPT for Data Analysis - First Look
09:54
Automate Excel with ChatGPT
13:23
Automating Web Scraping with a Plugin
09:21
What's The Code Interpreter?
06:38
How to work with ChatGPT Code Interpreter
04:14
Code Interterpreter File Uploads
09:04
Data Analysis with Code Interpreter
08:28
Web Scraping with Code Interpreter
12:30
Automate Excel Reporting with Code Interpreter
09:07

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