[Last updated 12/2023] The Data Analyst Course: Complete Data Analyst Bootcamp (Udemy – Vietsub and Engsub)

About Course

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What you’ll learn:
The course provides the complete preparation you need to become a data analyst
Fill up your resume with in-demand data skills: Python programming, NumPy, pandas, data preparation – data collection, data cleaning, data preprocessing, data visualization; data analysis, data analytics
Acquire a big picture understanding of the data analyst role
Learn beginner and advanced Python
Study mathematics for Python
We will teach you NumPy and pandas, basics and advanced
Be able to work with text files
Understand different data types and their memory usage
Learn how to obtain interesting, real-time information from an API with a simple script
Clean data with pandas Series and DataFrames
v.v…
Time video:
20.5 hours (277 Lessons + Documents)
Teacher:
365 Careers
Total weight:
8.89 GB

Original link:
https://www.udemy.com/course/the-data-analyst-course-complete-data-analyst-bootcamp/

+ Nếu các bạn xem online gặp tình trạng “Không thể phát video do quá tải” (Google Drive) thì các bạn nên tải về nhé. Lưu ý nên tải từng thư mục nhé hoặc 1-5 thư mục cùng lúc (lúc đó google drive sẽ nén file và tự động tải xuống). Không nên tải thư mục cha vì file nặng google sẽ nén thiếu nhé.

Course Content

14 – Data Cleaning and Data Preprocessing

001 Data Cleaning and Data Preprocessing.mp4

05:26

27 – Conclusion

26 – Data Visualization

028 Scatter Plot – How to Make a Good Scatter Plot.mp4

02:56
020 Histogram – Introduction – General Theory. Getting to Know the Dataset.mp4

04:39
021 Histogram – How to Create a Histogram Using Python.mp4

05:43
022 Histogram – Interpreting the Histogram.mp4

02:11
023 Histogram – Choosing the Number of Bins in a Histogram.mp4

05:27
024 Histogram – How to Make a Good Histogram.mp4

04:43
025 Scatter Plot – Introduction – General Theory. Getting to Know the Dataset.mp4

02:29
026 Scatter Plot – How to Create a Scatter Plot Using Python.mp4

08:39
027 Scatter Plot – Interpreting the Scatter Plot.mp4

02:42
019 Line Chart – How to Make a Good Line Chart.mp4

06:30
029 Regression Plot – Introduction – General Theory. Getting to Know the Dataset.mp4

03:03
030 Regression Plot – How to Create a Regression Scatter Plot Using Python.mp4

07:08
031 Regression Plot – Interpreting the Regression Scatter Plot.mp4

04:35
032 Regression Plot – How to Make a Good Regression Plot.mp4

03:14
033 Bar and Line Chart – Introduction – General Theory. Getting to Know the Dataset.mp4

03:10
034 Bar and Line Chart – How to Create a Combination Bar and Line Graph Using Python.mp4

07:39
035 Bar and Line Chart – Interpreting the Combination Bar and Line Graph.mp4

02:36
036 Bar and Line Chart – How to Make a Good Bar and Line Graph.mp4

04:04
010 Pie Chart – Interpreting the Pie Chart.mp4

01:32
002 Why Learn Data Visualization.mp4

06:08
003 Choosing the Right Visualization – What Are Some Popular Approaches and Framewor.mp4

06:58
004 Introduction into Colors and Color Theory.mp4

08:56
005 Bar Chart – Introduction – General Theory and Getting to Know the Dataset.mp4

01:29
006 Bar Chart – How to Create a Bar Chart Using Python.mp4

11:27
007 Bar Chart – Interpreting the Bar Graph. How to Make a Good Bar Graph.mp4

02:50
008 Pie Chart – Introduction – General Theory and Dataset.mp4

04:04
009 Pie Chart – How to Create a Pie Chart Using Python.mp4

06:39
001 What Is Data Visualization and Why Is It Important.mp4

04:31
011 Pie Chart – Why You Should Never Create a Pie Graph.mp4

07:32
012 Stacked Area Chart – Introduction – General Theory. Getting to Know the Dataset.mp4

03:16
013 Stacked Area Chart – How to Create a Stacked Area Chart Using Python.mp4

07:47
014 Stacked Area Chart – Interpreting the Stacked Area Graph.mp4

02:30
015 Stacked Area Chart – How to Make a Good Stacked Area Chart.mp4

03:52
016 Line Chart – Introduction – General Theory. Getting to Know the Dataset.mp4

02:03
017 Line Chart – How to Create a Line Chart in Python.mp4

08:05
018 Line Chart – Interpretation.mp4

03:11

25 – Solution to the Absenteeism Exercise

009 Grouping the Reason for Absence Columns.mp4

08:35
018 Final Remarks on the Absenteeism Exercise.mp4

01:40
017 Modifying the ‘Education’ Column.mp4

04:38
016 Understanding the Meaning of 5 More Columns.mp4

03:17
015 Creating the ‘Day of the Week’ Column.mp4

03:36
014 Extracting the Month Value from the ‘Date’ Column.mp4

06:59
013 Working on the ‘Date’ Column.mp4

07:48
011 Reordering Columns in a DataFrame.mp4

01:43
010 Concatenating Columns in a pandas DataFrame.mp4

04:35
001 How to Complete the Absenteeism Exercise.mp4

01:57
008 Working with Dummy Variables – A Statistical Perspective.mp4

01:28
007 Splitting the Reasons for Absence into Multiple Dummy Variables.mp4

08:37
006 Analysis of the ‘Reason for Absence’ Column.mp4

05:04
005 Dropping the ‘ID’ Column.mp4

06:27
004 Using a Statistical Approach to Solve Our Exercise.mp4

02:17
003 Note Programming vs the Rest of the World.mp4

03:27
002 Eyeball Your Data First.mp4

05:53

24 – The Absenteeism Exercise – Introduction

23 – A Loan Data Example with NumPy

001 Setting Up Introduction to the Practical Example.mp4

04:50
002 Setting Up Importing the Data Set.mp4

04:09
003 Setting Up Checking for Incomplete Data.mp4

04:35
004 Setting Up Splitting the Dataset.mp4

05:27
005 Setting Up Creating Checkpoints.mp4

02:50
006 Manipulating Text Data Issue Date.mp4

05:26
007 Manipulating Text Data Loan Status and Term.mp4

07:08
008 Manipulating Text Data Grade and Sub Grade.mp4

08:54
009 Manipulating Text Data Verification Status & URL.mp4

05:19
010 Manipulating Text Data State Address.mp4

06:01
011 Manipulating Text Data Converting Strings and Creating a Checkpoint.mp4

03:28
012 Manipulating Numeric Data Substitute Filler Values.mp4

07:51
013 Manipulating Numeric Data Currency Change – The Exchange Rate.mp4

06:32
014 Manipulating Numeric Data Currency Change – From USD to EUR.mp4

08:22
015 Completing the Dataset.mp4

06:46

22 – NumPy – Preprocessing

001 Checking for Missing Values in Ndarrays.mp4

09:23
002 Substituting Missing Values in Ndarrays.mp4

08:29
003 Reshaping Ndarrays.mp4

06:31
004 Removing Values from Ndarrays.mp4

04:20
005 Sorting Ndarrays.mp4

09:45
006 Argument Sort in NumPy.mp4

05:48
007 Argument Where in NumPy.mp4

11:12
008 Shuffling Ndarrays.mp4

06:51
009 Casting Ndarrays.mp4

06:13
010 Striping Values from Ndarrays.mp4

04:43
011 Stacking Ndarrays.mp4

10:31
012 Concatenating Ndarrays.mp4

06:27
013 Finding Unique Values in Ndarrays.mp4

05:04

21 – Statistics with NumPy

20 – Generating Data with NumPy

19 – Working with Arrays

18 – NumPy DataTypes

17 – NumPy Fundamentals

16 – pandas DataFrames

15 – pandas Series

01 – Introduction to the Course

13 – APIs (POST requests are not needed for this course)

001 Overview of APIs.mp4

03:10
002 GET and POST Requests.mp4

02:35
003 Data Exchange Format for APIs JSON.mp4

02:24
004 Introducing the Exchange Rates API.mp4

04:57
005 Including Parameters in a GET Request.mp4

03:17
006 More Functionalities of the Exchange Rates API.mp4

04:39
007 Coding a Simple Currency Conversion Calculator.mp4

04:52
008 iTunes API.mp4

04:41
010 iTunes API Structuring and Exporting the Data.mp4

02:10
011 Pagination GitHub API.mp4

04:21

12 – Data GatheringData Collection

11 – Must-Know Python Tools

10 – Working with Text Data

09 – Working with Text Files

014 Importing Data with the index_col Parameter.mp4

02:35
029 Working with Text Files – Conclusion.mp4

00:42
027 Saving Your Data with NumPy – np.savetxt().mp4

03:57
026 Saving Your Data with NumPy – np.savez().mp4

05:12
025 Saving Your Data with NumPy – np.save().mp4

05:23
024 Saving Your Data with pandas.mp4

03:11
023 A Note on Importing Files in Jupyter.mp4

03:10
022 Importing Data with the pandas’ Squeeze Method.mp4

03:23
021 An Important Exercise on Importing Data in Python.mp4

05:43
020 Working with Excel Data (the .xlsx Format).mp4

01:55
019 Prelude to Working with Excel Files in Python.mp4

03:40
018 Importing .json Files.mp4

05:14
016 Importing Data with NumPy – Partial Cleaning While Importing.mp4

07:21
015 Importing Data with NumPy – .loadtxt() vs genfromtxt().mp4

10:43
001 Working with Files in Python – An Introduction.mp4

03:46
013 Importing .csv Files with pandas – Part III.mp4

05:57
012 Importing .csv Files with pandas – Part II.mp4

02:37
011 Importing .csv Files with pandas – Part I.mp4

05:35
010 Importing Text Files in Python ( with open() ).mp4

04:52
009 Importing Text Files in Python ( open() ).mp4

09:00
008 Common Naming Conventions Used in Programming.mp4

03:49
007 Fixed-width Files.mp4

01:25
006 More on Text Files (.txt vs .csv).mp4

04:33
005 Principles of Importing Data in Python.mp4

04:49
004 Data Connectivity through Text Files.mp4

03:06
003 Structured vs Semi-Structured and Unstructured Data.mp4

03:10
002 File vs File Object, Read vs Parse.mp4

02:52

08 – Pandas – Basics

001 Introduction to the pandas Library.mp4

05:41
002 Installing and Running pandas.mp4

05:57
006 Introduction to pandas Series.mp4

08:40
017 Working with Attributes in Python.mp4

05:22
025 Using an Index in pandas.mp4

04:00
031 Label-based vs Position-based Indexing.mp4

04:31
034 More on Working with Indices in Python.mp4

05:37
038 Using Methods in Python – Part I.mp4

04:55
039 Using Methods in Python – Part II.mp4

02:36
042 Parameters vs Arguments.mp4

04:35
045 The pandas Documentation.mp4

09:54
046 Introduction to pandas DataFrames.mp4

05:23
047 Creating DataFrames from Scratch – Part I.mp4

05:56
050 Creating DataFrames from Scratch – Part II.mp4

05:03
054 Additional Notes on Using DataFrames.mp4

01:58

07 – NumPy Basics

06 – Mathematics for Python

001 What Is Ð° Matrix.decrypted.mp4

03:37
001 What Is а Matrix.mp4

03:37
002 Scalars and Vectors.mp4

02:58
003 Linear Algebra and Geometry.mp4

03:06
004 Arrays in Python.mp4

05:09
005 What Is a Tensor.mp4

03:00
006 Adding and Subtracting Matrices.mp4

03:35
007 Errors When Adding Matrices.mp4

02:01
008 Transpose.mp4

05:13
009 Dot Product of Vectors.mp4

03:48
010 Dot Product of Matrices.mp4

08:23
011 Why is Linear Algebra Useful.mp4

10:10

05 – Fundamentals for Coding in Python

04 – Python Basics

119 Sequences – Tuples.mp4

03:10
080 Functions – Another Way to Define a Function.mp4

02:35
082 Functions – Using a Function in Another Function.mp4

01:49
084 Functions – Combining Conditional Statements and Functions.mp4

03:06
086 Functions – Creating Functions That Contain a Few Arguments.mp4

01:16
087 Functions – Notable Built-in Functions in Python.mp4

03:55
098 Sequences – Lists.mp4

04:02
105 Sequences – Using Methods.mp4

03:19
111 Sequences – List Slicing.mp4

04:30
077 Functions – Creating a Function with a Parameter.mp4

03:49
124 Sequences – Dictionaries.mp4

04:03
132 Iteration – For Loops.mp4

02:56
136 Iteration – While Loops and Incrementing.mp4

02:25
138 Iteration – Create Lists with the range() Function.mp4

03:49
143 Iteration – Use Conditional Statements and Loops Together.mp4

03:11
147 Iteration – Conditional Statements, Functions, and Loops.mp4

02:26
149 Iteration – Iterating over Dictionaries.mp4

03:07
048 Basic Python Syntax – Indentation.mp4

01:44
007 Types of Data – Numbers and Boolean Values.mp4

03:05
014 Types of Data – Strings.mp4

05:40
021 Basic Python Syntax – Arithmetic Operators.mp4

03:23
031 Basic Python Syntax – The Double Equality Sign.mp4

01:33
034 Basic Python Syntax – Reassign Values.mp4

01:08
040 Basic Python Syntax – Add Comments.mp4

01:34
042 Basic Python Syntax – Line Continuation.mp4

00:49
044 Basic Python Syntax – Indexing Elements.mp4

01:18
001 Python Variables.mp4

03:37
051 Operators – Comparison Operators.mp4

02:10
057 Operators – Logical and Identity Operators.mp4

05:35
065 Conditional Statements – The IF Statement.mp4

03:01
069 Conditional Statements – The ELSE Statement.mp4

02:45
071 Conditional Statements – The ELIF Statement.mp4

05:34
074 Conditional Statements – A Note on Boolean Values.mp4

02:13
076 Functions – Defining a Function in Python.mp4

02:01

03 – Setting up the Environment

001 Introduction.mp4

01:24
002 Programming Explained in a Few Minutes.mp4

05:03
004 Jupyter – Introduction.mp4

03:29
005 Jupyter – Installing Anaconda.mp4

04:00
006 Jupyter – Intro to Using Jupyter.mp4

03:10
007 Jupyter – Working with Notebook Files.mp4

06:09
008 Jupyter – Using Shortcuts.mp4

03:07
009 Jupyter – Handling Error Messages.mp4

05:52
010 Jupyter – Restarting the Kernel.mp4

02:17

02 – Introduction to Data Analytics

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About Course

Course Content

14 – Data Cleaning and Data Preprocessing

001 Data Cleaning and Data Preprocessing.mp4

27 – Conclusion

001 Conclusion.mp4

26 – Data Visualization

028 Scatter Plot – How to Make a Good Scatter Plot.mp4

020 Histogram – Introduction – General Theory. Getting to Know the Dataset.mp4

021 Histogram – How to Create a Histogram Using Python.mp4

022 Histogram – Interpreting the Histogram.mp4

023 Histogram – Choosing the Number of Bins in a Histogram.mp4

024 Histogram – How to Make a Good Histogram.mp4

025 Scatter Plot – Introduction – General Theory. Getting to Know the Dataset.mp4

026 Scatter Plot – How to Create a Scatter Plot Using Python.mp4

027 Scatter Plot – Interpreting the Scatter Plot.mp4

019 Line Chart – How to Make a Good Line Chart.mp4

029 Regression Plot – Introduction – General Theory. Getting to Know the Dataset.mp4

030 Regression Plot – How to Create a Regression Scatter Plot Using Python.mp4

031 Regression Plot – Interpreting the Regression Scatter Plot.mp4

032 Regression Plot – How to Make a Good Regression Plot.mp4

033 Bar and Line Chart – Introduction – General Theory. Getting to Know the Dataset.mp4

034 Bar and Line Chart – How to Create a Combination Bar and Line Graph Using Python.mp4

035 Bar and Line Chart – Interpreting the Combination Bar and Line Graph.mp4

036 Bar and Line Chart – How to Make a Good Bar and Line Graph.mp4

010 Pie Chart – Interpreting the Pie Chart.mp4

002 Why Learn Data Visualization.mp4

003 Choosing the Right Visualization – What Are Some Popular Approaches and Framewor.mp4

004 Introduction into Colors and Color Theory.mp4

005 Bar Chart – Introduction – General Theory and Getting to Know the Dataset.mp4

006 Bar Chart – How to Create a Bar Chart Using Python.mp4

007 Bar Chart – Interpreting the Bar Graph. How to Make a Good Bar Graph.mp4

008 Pie Chart – Introduction – General Theory and Dataset.mp4

009 Pie Chart – How to Create a Pie Chart Using Python.mp4

001 What Is Data Visualization and Why Is It Important.mp4

011 Pie Chart – Why You Should Never Create a Pie Graph.mp4

012 Stacked Area Chart – Introduction – General Theory. Getting to Know the Dataset.mp4

013 Stacked Area Chart – How to Create a Stacked Area Chart Using Python.mp4

014 Stacked Area Chart – Interpreting the Stacked Area Graph.mp4

015 Stacked Area Chart – How to Make a Good Stacked Area Chart.mp4

016 Line Chart – Introduction – General Theory. Getting to Know the Dataset.mp4

017 Line Chart – How to Create a Line Chart in Python.mp4

018 Line Chart – Interpretation.mp4

25 – Solution to the Absenteeism Exercise

009 Grouping the Reason for Absence Columns.mp4

018 Final Remarks on the Absenteeism Exercise.mp4

017 Modifying the ‘Education’ Column.mp4

016 Understanding the Meaning of 5 More Columns.mp4

015 Creating the ‘Day of the Week’ Column.mp4

014 Extracting the Month Value from the ‘Date’ Column.mp4

013 Working on the ‘Date’ Column.mp4

011 Reordering Columns in a DataFrame.mp4

010 Concatenating Columns in a pandas DataFrame.mp4

001 How to Complete the Absenteeism Exercise.mp4

008 Working with Dummy Variables – A Statistical Perspective.mp4

007 Splitting the Reasons for Absence into Multiple Dummy Variables.mp4

006 Analysis of the ‘Reason for Absence’ Column.mp4

005 Dropping the ‘ID’ Column.mp4

004 Using a Statistical Approach to Solve Our Exercise.mp4

003 Note Programming vs the Rest of the World.mp4

002 Eyeball Your Data First.mp4

24 – The Absenteeism Exercise – Introduction

001 An Introduction to the Absenteeism Exercise.mp4

002 The Absenteeism Exercise from a Business Perspective.mp4

003 The Dataset.mp4

23 – A Loan Data Example with NumPy

001 Setting Up Introduction to the Practical Example.mp4

002 Setting Up Importing the Data Set.mp4

003 Setting Up Checking for Incomplete Data.mp4

004 Setting Up Splitting the Dataset.mp4

005 Setting Up Creating Checkpoints.mp4

006 Manipulating Text Data Issue Date.mp4

007 Manipulating Text Data Loan Status and Term.mp4

008 Manipulating Text Data Grade and Sub Grade.mp4

009 Manipulating Text Data Verification Status & URL.mp4

010 Manipulating Text Data State Address.mp4

011 Manipulating Text Data Converting Strings and Creating a Checkpoint.mp4

012 Manipulating Numeric Data Substitute Filler Values.mp4

013 Manipulating Numeric Data Currency Change – The Exchange Rate.mp4

014 Manipulating Numeric Data Currency Change – From USD to EUR.mp4